Imperial College London
Public University • UK
Showing 95 courses from Imperial College London
Global Disease Masterclass: Global Disease Distribution
Imperial College London (via Coursera)
The Global Diseases Masterclass is part of the full-degree Masters of Public Health that the School of Public Health. By the end of this specialisation, our aim is that students will be able to critically apply epidemiological concepts to major global diseases and be able to appraise and recommend policy options to combat them. Global Diseases Masterclass: Global Disease Distribution In this course, we will introduce students to the most important trends and pattern in health and disease on a global scale. We will look at how health has improved over time, examine the trends for the future and look at between and within-country inequality in health. We will look at the methods that lie behind those statistics and think about different ways in which health can be conceptualised and measured. The course ends by considering the reason that might lie behind the patterns that we’ve pointed out and introducing the distinction between direct and structural interventions.The course ends by considering the reasons that might lie behind the patterns that we’ve described and introducing the concept of structural interventions.
Global Disease Masterclass: Non-communicable Diseases
Imperial College London (via Coursera)
Welcome to this course on the aetiology, epidemiology and interventions for non-communicable diseases of the Global Diseases Masterclass. We’ve selected four disease areas and will go through each in turn. The diseases we’ve chosen are: Colorectal Cancer, Cardiovascular Disease (CVD), Dementia, and Diabetes. We have selected these non-communicable diseases because they span a range of different types of disease process and because of the expertise and experience that our School of Public Health has in these areas. This will provide an introduction to a few of the of most important global non-communicable disease challenges while also providing variation in aetiology, epidemiology and interventions to learn from. We hope that by the end of this course you will be able to describe the basics of the disease aetiology, global epidemic trends and the available interventions. We also hope you’ll be able to use this information to critique public health approaches and policy positions for the four non-communicable diseases we’ve covered as well helping you extend to further disease areas.
Mathematics for Machine Learning: Linear Algebra
Imperial College London (via Coursera)
In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning.
A-level Further Mathematics for Year 12 - Course 1: Complex Numbers, Matrices, Roots of Polynomial Equations and Vectors
Imperial College London (via edX)
A-level Further Mathematics for Year 12 - Course 1: Complex Numbers, Matrices, Roots of Polynomial Equations and Vectors
A-Level Further Mathematics for Year 12 - Course 2: 3 x 3 Matrices, Mathematical Induction, Calculus Methods and Applications, Maclaurin Series, Complex Numbers and Polar Coordinates
Imperial College London (via edX)
A-Level Further Mathematics for Year 12 - Course 2: 3 x 3 Matrices, Mathematical Induction, Calculus Methods and Applications, Maclaurin Series, Complex Numbers and Polar Coordinates
A-level Further Mathematics for Year 13 - Course 1: Differential Equations, Further Integration, Curve Sketching, Complex Numbers, the Vector Product and Further Matrices
Imperial College London (via edX)
A-level Further Mathematics for Year 13 - Course 1: Differential Equations, Further Integration, Curve Sketching, Complex Numbers, the Vector Product and Further Matrices
A-level Mathematics for Year 12 - Course 1: Algebraic Methods, Graphs and Applied Mathematics Methods
Imperial College London (via edX)
A-level Mathematics for Year 12 - Course 1: Algebraic Methods, Graphs and Applied Mathematics Methods
A-level Mathematics for Year 12 - Course 2: Calculus, Newton’s Laws and Hypothesis Testing
Imperial College London (via edX)
A-level Mathematics for Year 12 - Course 2: Calculus, Newton’s Laws and Hypothesis Testing
A-level Mathematics for Year 13 - Course 1: Functions, Sequences and Series, and Numerical Methods
Imperial College London (via edX)
A-level Mathematics for Year 13 - Course 1: Functions, Sequences and Series, and Numerical Methods
A-level Mathematics for Year 13 - Course 2: General Motion, Moments and Equilibrium, The Normal Distribution, Vectors, Differentiation Methods, Integration Methods and Differential Equations
Imperial College London (via edX)
A-level Mathematics for Year 13 - Course 2: General Motion, Moments and Equilibrium, The Normal Distribution, Vectors, Differentiation Methods, Integration Methods and Differential Equations
Foundations of Public Health Practice: The Public Health Toolkit
Imperial College London (via Coursera)
The Foundations of Public Health Practice: The Public Health Toolkit builds on public health thinking (introduced in the previous course) and introduces a variety of core public health approaches (the toolkit) to conceptualising problems, conducting analysis and bringing forward recommendations. In this course we cover health needs assessment, evaluation and public health intelligence-approaches.
A-Level Further Mathematics for Year 13 - Course 2: Applications of Differential Equations, Momentum, Work, Energy & Power, The Poisson Distribution, The Central Limit Theorem, Chi Squared Tests, Type I and II Errors
Imperial College London (via edX)
A-Level Further Mathematics for Year 13 - Course 2: Applications of Differential Equations, Momentum, Work, Energy & Power, The Poisson Distribution, The Central Limit Theorem, Chi Squared Tests, Type I and II Errors
A-Level Further Mathematics Year 13 - Course 2: Applications of Differential Equations, Momentum, Work, Energy & Power, The Poisson Distribution, The Central Limit Theorem, Chi Squared Tests, Type I and II Errors
Imperial College London (via edX)
A-Level Further Mathematics Year 13 - Course 2: Applications of Differential Equations, Momentum, Work, Energy & Power, The Poisson Distribution, The Central Limit Theorem, Chi Squared Tests, Type I and II Errors
Building on the SIR Model
Imperial College London (via Coursera)
The other two courses in this specialisation require you to perform deterministic modelling - in other words, the epidemic outcome is predictable as all parameters are fully known. However, this course delves into the many cases – especially in the early stages of an epidemic – where chance events can be influential in the future of an epidemic. So, you'll be introduced to some examples of such ‘stochasticity’, as well as simple approaches to modelling these epidemics using R. You will examine how to model infections for which such ‘population structure’ plays an important role in the transmission dynamics, and will learn some of the basic approaches to modelling vector-borne diseases, including the Ross-McDonald Model. Even if you are not designing and simulating mathematical models in future, it is important to be able to critically assess a model so as to appreciate its strengths and weaknesses, and identify how it could be improved. One way of gaining this skill is to conduct a critical peer review of a modelling study as a reviewer, which is an opportunity you'll get by taking this course.
Bioengineering in action
Imperial College London (via edX)
Bioengineering in action
What Do Viruses Do And How Do We Control Them
Imperial College London (via Coursera)
This course describes how viruses interact with their hosts to infect, replicate, spread and cause disease. It looks at what controls the specificity of viruses for different host species and for different tissues within a host, also how this can lead to outbreaks and pandemics. It seeks to show how virus evolution is driven by the pressures to replicate and spread. Finally, it looks at how we can find antivirals and use them to control infections, distinguishing therapeutic approaches to prophylaxis by vaccination. On successful completion of the course, learners will be able to: 1. Identify key interfaces of virus: host interaction 2. Verify how transmission drives virus pathogenesis and shapes virus evolution 3. Demonstrate an understanding of how virus control with anti-virals differs from protection with vaccines. This is an intermediate series of courses intended for both clinical and non-clinical scientists who want to update their skills for work in clinical, academic, and pharmaceutical/bioscience industries, and is developed and delivered by experts working on viruses and novel vaccines. To be successful in this series of courses, you should have basic knowledge in biology, genetics, microbiology or related fields.
Immunology: Immune System and Infectious Diseases
Imperial College London (via Coursera)
The constant struggle between pathogens and the human immune system has been posing a significant threat to our health for thousands of years. Infectious diseases remain the leading cause of death worldwide. These are typically caused by bacteria (intra- and extracellular), viruses, fungi, parasites (worms/helminths) and prions. Under normal circumstance, the immune response orchestrates a robust protection against these pathogens using both molecular and cellular mechanisms. This usually leads to direct or indirect inactivation of the infectious agent, so the disease symptoms may not appear. However, numerous pathogens have devised immune evasion strategies, which allow them to play ‘hide and seek’ with our immune system. The avoidance of human natural defences may result in host colonisation by a pathogen and thus an infection. This can manifest as disease when the infectious agent replicates and inflicts damage. In this course, you will learn about the different types of pathogens, their confrontation with human immune system, and the dramatic consequences of their evasive strategies.
IETL-Tech Sandpit
Imperial College London (via edX)
IETL-Tech Sandpit
CARE: Nutrition in Ageing
Imperial College London (via edX)
CARE: Nutrition in Ageing
Nutrition in Ageing
Imperial College London (via edX)
Nutrition in Ageing
CARE: Nutrition in Ageing (French)
Imperial College London (via edX)
CARE: Nutrition in Ageing (French)
Coaching Skills for Learner-Centred Conversations
Imperial College London (via edX)
Coaching Skills for Learner-Centred Conversations
Coaching Skills for Educators
Imperial College London (via edX)
Coaching Skills for Educators
Creative Thinking Techniques
Imperial College London (via edX)
Creative Thinking Techniques
Creative Thinking: Techniques and Tools for Success
Imperial College London (via edX)
Creative Thinking: Techniques and Tools for Success
Introduction to Digital health
Imperial College London (via Coursera)
This course introduces the field of digital health and the key concepts and definitions in this emerging field. The key topics include Learning Health Systems and Electronic Health Records and various types of digital health technologies to include mobile applications, wearable technologies, health information systems, telehealth, telemedicine, machine learning, artificial intelligence and big data. These technologies are assessed in terms of the key opportunities and challenges to their use and the evidence of their effectiveness in the field of digital health in relation to public health and healthcare globally. The use and application of digital health for COVID-19 forms a case study demonstrating the use of different types of digital health technologies to address key aspects of the response to the virus globally.
Why Move Towards Cleaner Power
Imperial College London (via edX)
Why Move Towards Cleaner Power
Creating a Pro-Renewables Environment
Imperial College London (via edX)
Creating a Pro-Renewables Environment
Incorporating Renewable Energy in Electricity Grids
Imperial College London (via edX)
Incorporating Renewable Energy in Electricity Grids
Corporate Renewable Procurement: Opportunities in India
Imperial College London (via edX)
Corporate Renewable Procurement: Opportunities in India
IETL-edX SANDBOX course shell
Imperial College London (via edX)
IETL-edX SANDBOX course shell
Empathetic Engineer
Imperial College London (via edX)
Empathetic Engineer
Navigating Clinical Research
Imperial College London (via edX)
Navigating Clinical Research
ReachOut CPD: Lower Primary
Imperial College London (via edX)
ReachOut CPD: Lower Primary
ReachOut CPD: Skills-based
Imperial College London (via edX)
ReachOut CPD: Skills-based
Science Matters: Let's Talk About COVID-19
Imperial College London (via Coursera)
Welcome to ‘Science Matters: Let's Talk about COVID-19’, from the Jameel Institute at Imperial College London. The outbreak of the Novel Coronavirus Disease (COVID-19) is the most significant public health emergency of the 21st century so far. As the epidemic spreads, people around the world want to understand the science behind the most pressing questions: how many people have been infected? How dangerous is the virus? When will a vaccine be available? How can the epidemic be contained, and the damages mitigated? What is the economic impact? What’s the role of social media and local communities in the epidemic response? Researchers at the Jameel Institute and other research institutes at Imperial College London have been at the forefront of the response to the COVID-19 emergency, with clinical, epidemiological and social science analyses informing the outbreak response. They are generating robust empirical evidence that governments and international agencies are using around the world to plan their responses. On this course, you will hear directly from our world-class experts about the theory behind the analyses of COVID-19 and its spread, while learning how to interpret new information using core principles of public health, epidemiology, medicine, health economics, and social science. You will be able to watch regular situation reports about the state of the epidemic, provided by the researchers of J-IDEA and its director Professor Neil Ferguson. If you want to learn even more about these topics, a number of free MOOCs are available from Imperial College London. We also offer a fully online Global Master of Public Health for those of you who want to delve even deeper and join our professional community. Please note: This course was launched in February 2020 and we have continued to develop content as the COVID-19 situation progresses and new insights emerge. While we endeavour to include the most recent information, this is a fast-moving situation and i...
ReachOut CPD: Upper Primary Life Sciences
Imperial College London (via edX)
ReachOut CPD: Upper Primary Life Sciences
Healthcare Entrepreneurship: Taking Ideas to Market
Imperial College London (via Coursera)
This course delves into intellectual property (IP) with an introduction into the innovation landscape within the UK and how that compares with other settings. You'll focus on how intellectual property applies to frugal innovations, compulsory licensing, and when and how to apply for intellectual property. This course teaches you about how innovators can secure funding by exploring the types of funding available, the types of organisations involved, as well as the challenges that surround funding. A key part of this course is a focus on 'pitching' skills - what's involved in pitching well, what content should you include, how can you best deliver a pitch. You'll come away from this course with strong insight into the importance of protecting an innovation's intellectual property, able to identify IP processes and challenges, and able to confidently pitch an innovation.
ReachOut CPD: Upper Primary Physical Sciences
Imperial College London (via edX)
ReachOut CPD: Upper Primary Physical Sciences
edx course shell - test
Imperial College London (via edX)
edx course shell - test
Foundations of Public Health Practice: Health Protection
Imperial College London (via Coursera)
The Health Protection course is the fourth instalment of the wider Foundations of Public Health Practice specialisation from Imperial College London's Global Master of Public Health (MPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners drawing on decades of real-world public health experience as well as deep academic knowledge. Through short video lectures, practitioner interviews and a wide range of interactive activities, learners will be immersed in the world of public health practice. Designed for those new to the discipline, over three modules (intended for three weeks of learning), learners will become familiar with the scope, principles and nuances of health protection in the context of public health practice. Beginning with the basics of Water, Sanitation and Health (WASH) based interventions, the course will introduce learners to the science and principles of practical microbiology, before examining vaccines, incident management and the threat posed by a wide range of manmade and natural environmental threats. By the end of this course, learners will be familiar and conversant with core health protection principles and approaches, and confident in discussing health protection issues when they move into practice.
Getting started with TensorFlow 2
Imperial College London (via Coursera)
Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills. At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop an image classifier deep learning model from scratch. Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning. The release of Tensorflow 2 marks a step change in the product development, with a central focus on ease of use for all users, from beginner to advanced level. This course is intended for both users who are completely new to Tensorflow, as well as users with experience in Tensorflow 1.x. The prerequisite knowledge required in order to be successful in this course is proficiency in the python programming language, (this course uses python 3), knowledge of general machine learning concepts (such as overfitting/underfitting, supervised learning tasks, validation, regularisation and model selection), and a working knowledge of the field of deep learning, including typical model architectures (MLP/feedforward and convolutional neural networks), activation functions, output layers, and optimisation.
Applying Participatory Approaches in Public Health Settings
Imperial College London (via Coursera)
This course specifically explores approaches and tools and how to apply them in public health settings. Students will learn how to critically analyse the power dynamics present between multidisciplinary stakeholders and appreciate the need for reciprocity between those delivering and those receiving health care; between both those conducting and those participating in research. They will also learn how to select and evaluate different participatory approaches to apply these to public health programmes and/or research. Tools with which to do this include undertaking a stakeholder-mapping exercise and needs assessment, including a critical and reasoned narrative to justify the approach. While this course, as with the rest of the specialisation, focuses on public health and ways of involving citizens and patients in programmes and research, these concepts apply to other disciplines too. So, you don't have to be a public health specialist or work in healthcare to gain insight from this course. If you would like to learn more about the theories and core principles of participation within a public health context, we suggest taking Introduction to Participatory Approaches in Public Health. If you're planning a research project and want to learn more about participation in resaerchs, explore our course Public Involvement in Research.
Linear Regression in R for Public Health
Imperial College London (via Coursera)
Welcome to Linear Regression in R for Public Health! Public Health has been defined as “the art and science of preventing disease, prolonging life and promoting health through the organized efforts of society”. Knowing what causes disease and what makes it worse are clearly vital parts of this. This requires the development of statistical models that describe how patient and environmental factors affect our chances of getting ill. This course will show you how to create such models from scratch, beginning with introducing you to the concept of correlation and linear regression before walking you through importing and examining your data, and then showing you how to fit models. Using the example of respiratory disease, these models will describe how patient and other factors affect outcomes such as lung function. Linear regression is one of a family of regression models, and the other courses in this series will cover two further members. Regression models have many things in common with each other, though the mathematical details differ. This course will show you how to prepare the data, assess how well the model fits the data, and test its underlying assumptions – vital tasks with any type of regression. You will use the free and versatile software package R, used by statisticians and data scientists in academia, governments and industry worldwide.
Health Systems Development: Health systems, Policy and Research
Imperial College London (via Coursera)
This specialization is intended for people interested in health systems and how they function. Participants will learn about the global health systems landscape and the challenges and opportunities to achieve better health outcomes. This specialisation is divided into three courses which are offered as massive online open access courses (Courses 1-3), and a fourth course which is offered as part of the Online MPH degree (capstone). The Health Systems Development specialisation is geared toward learners who have no prior knowledge of health systems or those who are starting to explore this area of study. Overall, sessions in this specialisation span 16 week with approximately 96 hours of viewing learning materials per week. Formative assessments in the form of quizzes and activities are incorporated throughout the weeks to help learners gauge their level of depth of understanding and to prepare them for their summative assessments. Participants will have the opportunity to explore a range of areas within health systems. The first course will introduce the main building blocks of health systems and shed some light on key components of well-functioning health systems including how health system performance is assessed. In course two, students will learn how to conduct a health impact assessment and how to assess the impacts of policies, plans and projects, as well as how that support decision-makers make choices regarding alternatives and improvements to prevent disease or injury and to actively promote health. The third course explores human resources for health and service delivery. In this course, students will learn about and analyse country experiences in transforming health services delivery, and interventions and to address human resources for health challenges at a global level. By the end of this specialisation, learners should be able to identify key components of, and critically compare, different health systems; analyse country experien...
Foundations of Public Health Practice: The Public Health Approach
Imperial College London (via Coursera)
The Public Health Approach course is the first instalment of the wider Foundations of Public Health Practice specialisation from Imperial College London's Global Master of Public Health (MPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners drawing on decades of real-world public health experience as well as deep academic knowledge. Through short video lectures, practitioner interviews and a wide range of interactive activities, learners will be immersed in the world of public health practice. Designed for those new to the discipline, over four modules (intended for four weeks of learning), learners will become familiar with the scope, origins, ethics, principles and paradigms of public health practice. But there is also important foundational content for those coming from more experienced practitioner backgrounds. The 'Public Health Approach' is a phrase that is used widely to describe an up-stream, preventive, values-driven and evidence-based approach to improving population health. By the end of this course, learners will be confident with identifying and describing a wide range of public health challenges using the language and reference points of the public health profession. The subsequent courses require the knowledge from this course, as learners will be introduced to the public health toolkit of health needs assessment and evaluation, before taking deeper dives into behaviour change and health protection.
Systematic Creative Thinking: Tools for Success
Imperial College London (via Coursera)
Creativity is a widely acclaimed attribute. A range of creativity tools are available that rely on creativity principles to enable systematic idea generation. This module builds on the first module where various types of brainstorming were introduced along with the creativity diamond framework which provides a guide to which type of creative approach to use. Here we will introduce systematic creativity tools that can be used to provoke a wide range of ideas that might not normally arise and can be used to augment your innate creativity. WHAT YOU WILL LEARN • Familiarity with a range of approaches to creativity • The principles of morphological analysis for generating ideas • the principles of invention • To be able to identify the recommended principles of invention for a given scenario of improving and worsening features • How to use the SCAMPER creative idea provocation tool • Use of the creativity diamond framework to guid what approach to creativity to use SKILLS YOU WILL GAIN • Familiarity with a range of approaches applied to creativity • Systematic idea generation and creativity • Being able to use a morphological chart to develop a range of solutions • How to produce a morphological chart • use of the TRIZ contradiction matrix in identifying principles of invention for resolving contradictions in problem solving • Application of the SCAMPER creative idea provocation tool
3D Graphics in Android: Sensors and VR
Imperial College London (via Coursera)
This course is an ideal introduction into creating virtual environments in Android. This course is unique as it covers a range of tools and techniques to create immersive 3D environments, giving you a rounded skill set in this growing field. By the end of this course, you will really be able to bring your VR ideas to life! The first part of the course covers animation, lighting and reflection. We then move onto textures and handling multiple 3D objects. Finally, we'll look at housing all of this within a binocular view to create a VR experience. There are practical exercises throughout the course to apply your understanding, and there is a summative project which can form part of your professional portfolio. This course assumes a knowledge of Android programming and OpenGL. I recommend completing my two Coursera courses on these topics, as these are the perfect primer.
Mathematics for Machine Learning: Multivariate Calculus
Imperial College London (via Coursera)
This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future.
Types of Vaccine
Imperial College London (via Coursera)
This course explores the different types of vaccine available. This is a useful framework for understanding the scientific understanding that went into vaccine development. It also gives a perspective of how innovation (e.g. fundamental virology, molecular biology) work in a translational medicine context. On successful completion of the course, learners will be able to: 1. Identify features of different vaccine platforms 2. Demonstrate an understanding of the role of microbiological and technological advances in the development of vaccines 3. Recognise how different platforms may provide protection against different pathogens. This is an intermediate series of courses intended for both clinical and non-clinical scientists who want to update their skills for work in clinical, academic, and pharmaceutical/bioscience industries, and is developed and delivered by experts working on viruses and novel vaccines. To be successful in this series of courses, you should have basic knowledge in biology, genetics, microbiology or related fields.
Mathematics for Machine Learning: PCA
Imperial College London (via Coursera)
This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces. Using all these tools, we'll then derive PCA as a method that minimizes the average squared reconstruction error between data points and their reconstruction. At the end of this course, you'll be familiar with important mathematical concepts and you can implement PCA all by yourself. If you’re struggling, you'll find a set of jupyter notebooks that will allow you to explore properties of the techniques and walk you through what you need to do to get on track. If you are already an expert, this course may refresh some of your knowledge. The lectures, examples and exercises require: 1. Some ability of abstract thinking 2. Good background in linear algebra (e.g., matrix and vector algebra, linear independence, basis) 3. Basic background in multivariate calculus (e.g., partial derivatives, basic optimization) 4. Basic knowledge in python programming and numpy Disclaimer: This course is substantially more abstract and requires more programming than the other two courses of the specialization. However, this type of abstract thinking, algebraic manipulation and programming is necessary if you want to understand and develop machine learning algorithms.
Creative Thinking: Techniques and Tools for Success
Imperial College London (via Coursera)
In today’s ever-growing and changing world, being able to think creatively and innovatively are essential skills. It can sometimes be challenging to step back and reflect in an environment which is fast paced or when you are required to assimilate large amounts of information. Making sense of or communicating new ideas in an innovative and engaging way, approaching problems from fresh angles, and producing novel solutions are all traits which are highly sought after by employers. This course will equip you with a ‘tool-box’, introducing you to a selection of behaviours and techniques that will augment your innate creativity. Some of the tools are suited to use on your own and others work well for a group, enabling you to leverage the power of several minds. You can pick and choose which of these tools or techniques suit your needs and interests, focusing on some or all of the selected approaches and in the order that fits best for you. The practical approach of this course enables you to acquire an essential skill-set for generating ideas, with plenty of: Fun e-tivities and exercises; Practical lectures and tips; Video representations of the techniques in action. By the end of this course you should be able to: Pick a type of brainstorming you think will be useful to apply to a challenge Use alphabet brainstorming in tackling a challenge Use grid brainstorming in tackling a challenge Use a morphological chart to synthesise a solution to a challenge Use the TRIZ contradiction matrix to identify recommended inventive principles Apply SCAMPER to a range of challenges The greatest innovators aren’t necessarily the people who have the most original idea. Often, they are people- or teams- that have harnessed their creativity to develop a new perspective or more effective way of communicating an idea. You can train your imagination to seize opportunities, break away from routine and habit, and tap into your natural creativity. Join this course and a...
Migration and health
Imperial College London (via Coursera)
Migration and health is the second instalment of the wider Global Health Challenges and Governance specialisation from Imperial College London's Global Master of Public Health (GMPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners drawing on a wealth of real-world public health experience as well as deep academic knowledge. Through short video lectures, readings and a wide range of interactive activities, learners will be immersed in the intersection of migration and health. Designed for those new to the discipline, over four modules (intended for one week of learning each), learners will become familiar with the relationship between migration and health. Learners will be introduced to key terms and global trends in migrations, the profound impact of crises in non-health sectors on health, and policy instruments addressing migration. By the end of this course, learners will be able to describe international treaties protecting migrants’ right to health and migrant sensitive health systems. Learners will also be able to critically evaluate whether and how their national health system is providing universal health coverage to migrants. The subsequent course in this specialisation requires the knowledge from this course, as learners will take a deep dive into climate change by applying their global health analytical skills and knowledge of multilateral policy instruments to this important global health challenge.
Healthcare Innovation: What Does Success Look Like and How to Achieve It?
Imperial College London (via Coursera)
This course focuses on the factors involved in the adoption of innovation - features, organizations, country of origin, cognitive, normative and affective aspects, change agents. Using real-world health innovations, you'll assess what impacts their scaleability to new contexts, how organizational and human characteristics affect adoption, to what extent diffusion of an innovation is influenced by unconscious bias. You'll also delve into the process of adopting an innovation within a clinical setting and why it's so important to know who your 'change agents' are. As started in the second course of this specialisation, Healthcare Entrepreneurship: Taking Ideas to Market, you'll revisit the skill of pitching, exploring why and how to adapt pitches depending on your audience. By the end of this course, you'll feel able to judge the success of innovation projects; analyse how organizational structure, culture and resources are key in adoption; make recommendations for adoption in relation to organizational contexts; demonstrate how cognitive, normative and affective aspects can influence perception regarding an innovation's attractiveness and scaleability; and apply persuasive techniques to connect to audiences involved in the process of innovation scaling and adoption.
Introduction to Android graphics
Imperial College London (via Coursera)
This course will bring you up to speed with the fundamentals of 2D graphics and 3D graphics in Android. This course provides the ideal primer for more advanced courses and applications, for example, OpenGL, as well as Virtual Reality in Android. This course is unique because it covers the key concepts and theory of 2D and 3D graphics while also showing you how to implement these in Android practically. This provides a solid understanding and grasp of the subject matter which will be applicable in a variety of settings. The final assignment will provide you with an artefact which you can use for your professional portfolio to evidence your skills.
Globalisation and health governance
Imperial College London (via Coursera)
Globalisation and health governance is the first instalment of the wider Global Health Challenges and Governance specialisation from Imperial College London's Global Master of Public Health (GMPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners drawing on a wealth of real-world public health experience as well as deep academic knowledge. Through short video lectures, readings and a wide range of interactive activities, learners will be immersed in the world of global health. Designed for those new to the discipline, over four modules (intended for one week of learning each), learners will become familiar with the scope, history, principles, stakeholders and conceptual frameworks of global health, globalisation and governance. But there is also important foundational content for those coming from more experienced backgrounds, as the course builds upon a strong tradition of advocacy in public health and broad perspective of the global health context by exploring institutional, economic, socio-cultural and ecological determinants of population health. By the end of the course, learners will be able to confidently describe how globalisation impacts health and health governance at local, national and multilateral levels, and craft well-reasoned, evidence-based arguments about global health challenges. The subsequent courses require the knowledge from this course, as learners will take a deep dive into migration health and climate change by applying their foundational global health knowledge and advocacy skills to these important global health challenges.
TensorFlow 2 시작하기
Imperial College London (via Coursera)
TensorFlow 2 시작하기 과정에 오신 것을 환영합니다! 이 과정에서는 순차 API를 사용한 모델 구축, 훈련, 평가 및 예측, 모델 검증, 정규화, 콜백 구현, 모델 저장 및 로딩 등 Tensorflow를 사용하여 딥 러닝 모델을 개발하기 위한 완벽한 엔드-투-엔드 워크플로우를 배우게 됩니다. 배운 개념을 실용적인 실습형 코딩 자습서에서 바로 연습할 것이며 이는 대학원 조교에게 안내를 받게 될 것입니다. 또한 기술을 통합할 수 있는 일련의 자동 채점 프로그래밍 과제가 있습니다. 과정이 끝나면 이미지 분류기 딥 러닝 모델을 처음부터 개발하는 Capstone 프로젝트에 많은 개념을 통합할 것입니다. Tensorflow는 오픈 소스 머신 라이브러리이며 딥 러닝에 가장 널리 사용되는 프레임워크 중 하나입니다. Tensorflow 2의 출시는 초심자에서 고급 수준에 이르기까지 모든 사용자의 사용 편의성에 중점을 둔 제품 개발의 단계적 변화를 나타냅니다. 이 과정은 Tensorflow 1.x에 대한 경험이 있는 사용자뿐만 아니라 경험이 없는 사용자 모두를 대상으로 합니다. 이 과정에서 성공하기 위해서는 파이썬 프로그래밍 언어(이 과정에서는 파이썬 3 사용), 일반적인 머신 러닝 개념(예: 과적합/과소적합, 지도 학습 작업, 검증, 정규화 및 모델 선택), 전형적인 모델 아키텍처(MLP/피드포워드 및 컨볼루션 신경망), 활성화 함수, 출력 레이어 및 최적화를 포함한 딥 러닝 분야의 실무 지식을 갖추고 있어야 합니다.
Logistic Regression in R for Public Health
Imperial College London (via Coursera)
Welcome to Logistic Regression in R for Public Health! Why logistic regression for public health rather than just logistic regression? Well, there are some particular considerations for every data set, and public health data sets have particular features that need special attention. In a word, they're messy. Like the others in the series, this is a hands-on course, giving you plenty of practice with R on real-life, messy data, with predicting who has diabetes from a set of patient characteristics as the worked example for this course. Additionally, the interpretation of the outputs from the regression model can differ depending on the perspective that you take, and public health doesn’t just take the perspective of an individual patient but must also consider the population angle. That said, much of what is covered in this course is true for logistic regression when applied to any data set, so you will be able to apply the principles of this course to logistic regression more broadly too. By the end of this course, you will be able to: Explain when it is valid to use logistic regression Define odds and odds ratios Run simple and multiple logistic regression analysis in R and interpret the output Evaluate the model assumptions for multiple logistic regression in R Describe and compare some common ways to choose a multiple regression model This course builds on skills such as hypothesis testing, p values, and how to use R, which are covered in the first two courses of the Statistics for Public Health specialisation. If you are unfamiliar with these skills, we suggest you review Statistical Thinking for Public Health and Linear Regression for Public Health before beginning this course. If you are already familiar with these skills, we are confident that you will enjoy furthering your knowledge and skills in Statistics for Public Health: Logistic Regression for Public Health. We hope you enjoy the course!
Health Systems Development: Introduction to Health Systems
Imperial College London (via Coursera)
This specialization is intended for people interested in health systems and how they function. Participants will learn about the global health systems landscape and the challenges and opportunities to achieve better health outcomes. This specialisation is divided into three courses which are offered as massive online open access courses (Courses 1-3), and a fourth course which is offered as part of the Online MPH degree (capstone). The Health Systems Development specialisation is geared toward learners who have no prior knowledge of health systems or those who are starting to explore this area of study. Overall, sessions in this specialisation span 16 week with approximately 96 hours of viewing learning materials per week. Formative assessments in the form of quizzes and activities are incorporated throughout the weeks to help learners gauge their level of depth of understanding and to prepare them for their summative assessments. Participants will have the opportunity to explore a range of areas within health systems. The first course will introduce the main building blocks of health systems and shed some light on key components of well-functioning health systems including how health system performance is assessed. In course two, students will learn how to conduct a health impact assessment and how to assess the impacts of policies, plans and projects, as well as how that support decision-makers make choices regarding alternatives and improvements to prevent disease or injury and to actively promote health. The third course explores human resources for health and service delivery. In this course, students will learn about and analyse country experiences in transforming health services delivery, and interventions and to address human resources for health challenges at a global level. By the end of this specialisation, learners should be able to identify key components of, and critically compare, different health systems; analyse country exp...
How Vaccines Work
Imperial College London (via Coursera)
This course describes the underpinning science around vaccines and their development. It will look at the immunological underpinnings of how vaccines induce protection. It will also look at the epidemiological basis of how vaccines are rolled out. Finally it will explore how new vaccines are developed. On successful completion of the course, learners will be able to: 1. Understand how the immune response mediates vaccine protection 2. Explain how vaccines enter public health programs 3. Demonstrate your understanding of the challenges for the generation of a vaccine against disease This is an intermediate series of courses intended for both clinical and non-clinical scientists who want to update their skills for work in clinical, academic, and pharmaceutical/bioscience industries, and is developed and delivered by experts working on viruses and novel vaccines. To be successful in this series of courses, you should have basic knowledge in biology, genetics, microbiology or related fields.
Immunology: Adaptive Immune System
Imperial College London (via Coursera)
In this course, you will learn about the role of immune responses of the adaptive (acquired) immune system which provides specialised immunity against pathogens. Guided by our researchers in the Department of Immunity and Inflammation, we will take a closer look at the lymphocyte subsets and mechanisms involved in this delayed finely tuned response occurring days to weeks after the initial exposure to microbial antigens. We will also focus on the versatile cellular components which can distinguish between self- and nonself antigens and on how age affects the immune responses.
Global Disease Masterclass: Communicable Diseases Epidemiology, Intervention and Prevention
Imperial College London (via Coursera)
This course is all about infectious diseases. We’ve selected four disease areas — HIV, Malaria, Emerging Infectious Diseases (Ebola and Zika), and TB — and we will go through each in turn. We’ve selected these diseases because they span a range of different types of disease and allow us to look at important issues that relevance of other diseases too. We will look at each disease in the same way: we begin by looking at the aetiology and epidemiology of the diseases. We then show how data on this disease can be used to understand important trends and patterns. We then focus on the interventions that can be used to address that disease - typically spanning both prevention and treatment - and consider how policies have been developed to address the disease. We finish by reflecting on the whole topic area of the disease with an external expert.
Advanced Creative Thinking and AI: Tools for Success
Imperial College London (via Coursera)
Creativity is important in nearly every facet of life. Advances in neuro-science, computing and psychology, along with developments in other domains and cross-disciplinary areas have resulted in ever increasing understanding of creativity. This module will explore some advanced approaches to creativity such as the use of analogy and metaphor, various thinking styles and the role of artificial intelligence. A framework called the creativity diamond is used to guide the selection of approach to creativity relevant to your project or activity. WHAT YOU WILL LEARN • Biomimicry and using insights from nature • Use of analogy and metaphor in creativity • A range of creative thinking and reasoning approaches • The use of AI to generate creative outcomes • Attributes of creativity and their assessment • Use of the creativity diamond SKILLS YOU WILL GAIN • Biomimicry • Use of analogy and metaphor in creativity • Accelerated proficiency in creative thinking styles • Use of some AI enabled platforms to generate outputs • Creativity assessment • Use of the creativity diamond in practice to aid in the selection of an approach to creativity relevant to your project or activity
Developing the SIR Model
Imperial College London (via Coursera)
Compartmental modelling is a cornerstone of mathematical modelling of infectious diseases and this course will introduce some of the basic concepts in building compartmental models, including how to interpret and represent rates, durations and proportions. You'll learn to place the mathematics to one side and concentrate on gaining intuition into the behaviour of a simple epidemic, and be introduced to further basic concepts of infectious disease epidemiology, such as the basic reproduction number (R0) and its implications for infectious disease dynamics. To express the mathematical underpinnings of the basic drivers that you study, you'll use the simple SIR model, which, in turn, will help you examine different scenarios for reproduction numbers. Susceptibility to infection is the fuel for an infectious disease, so understanding the dynamics of susceptibility can offer important insights into epidemic dynamics, as well as priorities for control.
Health Systems Development: A Focus on Health Service Delivery and Human Resources for Health
Imperial College London (via Coursera)
This specialization is intended for people interested in health systems and how they function. Participants will learn about the global health systems landscape and the challenges and opportunities to achieve better health outcomes. This specialisation is divided into three courses which are offered as massive online open access courses (Courses 1-3), and a fourth course which is offered as part of the Online MPH degree (capstone). The Health Systems Development specialisation is geared toward learners who have no prior knowledge of health systems or those who are starting to explore this area of study. Overall, sessions in this specialisation span 16 week with approximately 96 hours of viewing learning materials per week. Formative assessments in the form of quizzes and activities are incorporated throughout the weeks to help learners gauge their level of depth of understanding and to prepare them for their summative assessments. Participants will have the opportunity to explore a range of areas within health systems. The first course will introduce the main building blocks of health systems and shed some light on key components of well-functioning health systems including how health system performance is assessed. In course two, students will learn how to conduct a health impact assessment and how to assess the impacts of policies, plans and projects, as well as how that support decision-makers make choices regarding alternatives and improvements to prevent disease or injury and to actively promote health. The third course explores human resources for health and service delivery. In this course, students will learn about and analyse country experiences in transforming health services delivery, and interventions and to address human resources for health challenges at a global level. By the end of this specialisation, learners should be able to identify key components of, and critically compare, different health systems; analyse country experiences in trans...
Health Coaching Conversations
Imperial College London (via Coursera)
Are you a healthcare practitioner or student in a healthcare field? Do you want to learn how to have more empowering conversations with your patients and support them to take control of their own health and wellbeing? Are you looking for a course to start learning these skills that also fits with your busy life? If so, this is the course for you! In this course, you will become much more familiar with some key health coaching principles and skills, and will be equipped to start applying these in your own healthcare contexts with patients and in your own life too.
Design and Implementation of Digital Health Interventions
Imperial College London (via Coursera)
This course covers various themes around design, regulatory approaches, ethics, technology adoption, implementation and strategy as applied to digital health. These session cover areas to include data regulations, examples of data breaches in digital health, the challenges and opportunities of technology adoption and implementation with a focus on the non-adoption, abandonment, scale-up, spread and sustainability framework (NASSS Framework). The strategy part of this course focuses on understanding a simple strategy for digital health through PESTLE and SWOT analysis, and examples of their application in digital health.
Foundations of Public Health Practice: Behaviour & Behaviour Change
Imperial College London (via Coursera)
The Health Protection course is the third instalment of the wider Foundations of Public Health Practice specialisation from Imperial College London's Global Master of Public Health (MPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners drawing on decades of real-world public health experience as well as deep academic knowledge. Through short video lectures, practitioner interviews and a wide range of interactive activities, learners will be immersed in the world of public health practice. Designed for those new to the discipline, over three modules (intended for three weeks of learning), learners will become familiar with the scope, theory and implementation of behaviour change in the context of public health practice. The course begins by challenging learners about their preconceptions about healthy and unhealthy behaviour - seeking to contextualise these ideas within the broader public health approach (the first course of this specialisation). The course thereafter swiftly covers the origins of risk communication and behaviour change through the lens of health psychology and classical economics, before introducing ideas of bounded rationality and the genesis of behavioural insights and so-called Nudges. By the end of the course, learners will be fluent with their use of the Behaviour Change Wheel methodology of intervention development and the application of the COM-B framework to a range of target behaviours and behavioural barriers. The subsequent courses of this specialisation will cover health protection before moving into the final (degree learner) course which where learners will focus on developing the core professional skillset that defines public health practitioners - whether in service or academia.
Immunology: Autoimmunity, Allergy, and Transplants
Imperial College London (via Coursera)
In this course, you will explore the mechanisms and immune responses involved in autoimmune diseases and in hyper-responsive phenomena, such as asthma. You will examine in detail the potential causes and factors behind an overactive immune system and the disorders that might ensue if the response is not adequately controlled. you will also analyse the effects of overactive immune response in transplant rejection.
Android Graphics with OpenGL ES
Imperial College London (via Coursera)
This course will cover the fundamentals of OpenGL and OpenGL ES in Android. This course is unique because it covers the mechanics of how OpenGL works and also more practical applications to draw 2D and 3D objects. This is an ideal primer for more complex courses on VR and AR within Android. We'll begin by covering the OpenGL Pipeline and Shading Language. Then we'll look at drawing simple 2D objects and increasingly complicated 3D objects in OpenGL and OpenGL ES. There are practical exercises throughout the course to apply your understanding, and there is a summative project which can form part of your professional portfolio.
Evaluation of Digital Health Interventions
Imperial College London (via Coursera)
This course focuses on data, evaluation methods and the economic evaluation of digital health interventions. This module focuses on key data considerations for digital health including data management, data visualisation and methods for evaluating digital health interventions. The key focus is on experimental and quasi-experimental design approaches that can be applied to evaluating digital health interventions and key considerations for the economic evaluation of digital health interventions.
Advanced App Development in Android Capstone
Imperial College London (via Coursera)
This capstone project has been designed as an opportunity to practice what you have learned in the first 3 courses of this specialisation. This capstone project consists of 4 assignments. You will have to develop an immersive Android app with the use 3D graphics, sensor control and VR. For the first assignment, you will have to develop a virtual art gallery using the Android Canvas drawing functions introduced in Course 1 "Introduction to Android graphics". The second assignment entails the design and development of a virtual 3D art gallery based on OpenGL ES applying the knowledge and skills acquired in Course 2 "Android Graphics with OpenGL ES". For the third assignment you will create a virtual reality app with your 3D art gallery, using advanced techniques like introducing sensor control, animations, binocular view for VR, lighting effects and texture mapping, based on the knowledge and skills you learned in Course 3 "3D Graphics in Android: Sensors and VR". For the final submission of the capstone project we give you the avenue to combine your creativity with all the knowledge and skills you gained in Android graphics programming from the three first courses. This capstone is intended for learners with basic knowledge in Android app development seeking to develop knowledge in computer graphics and virtual reality in Android. The learners should have completed the 3 courses in this specialisation (i.e. Course 1 "Introduction to Android graphics", Course 2 "Android Graphics with OpenGL ES", and Course 3 "3D Graphics in Android: Sensors and VR") before starting this capstone project.
Introduction to Python for Researchers
Imperial College London (via Coursera)
This course teaches the fundamentals of Python 3 in the context of academic research. Our tutor team support researchers across the whole of Imperial College London, including in science, engineering, mathematics, computing, medicine, and business. We have created this course to help our learners and researchers elsewhere prepare for modern research, which often includes a substantial amount of programming. You'll gain the basic skills needed to produce substantial programming projects which are accurate, professional, scalable, and which perform effectively. This will set you up well for the type of programming you'll need to do as a researcher. In this course, you'll learn: • the basics of Python including variables, types, if-blocks, loops, functions and exceptions. • how to write code using Visual Studio Code, which is a modern, professional tool used by programmers across all disciplines and professions. • best practices and the reasoning behind them, with a focus on developing skills and knowledge to help you become a confident and independent programmer. Projects throughout the course will allow you to practise designing and structuring progressively larger pieces of code - so, by the end, you'll be ready to produce the sort of code expected of a researcher. Throughout the course, you can draw on support from the learning community, sharing with your peers, answering questions, and giving feedback on solutions to exercises. This course is designed to be appropriate for complete novices to programming or learners who may already know another programming language. We hope you enjoy learning Python with us!
Immunology: Immune Failures and Cancer Immunology
Imperial College London (via Coursera)
Our immune system is a powerful network. It protects us from external threats, such as harmful substances and pathogenic agents, as well as cellular changes which could lead to diseases. Complications emerge when our natural defences do not function properly, which can result in immune disorders. These can take the form of less severe issues such as insect allergy. Others are more harmful, such as auto aggressive immune reactions, that lead to localised or systemic tissue damage. In this course, you will learn about immune system failures which can cause insufficient responses to internal or external threats. We will look at immune deficiencies. These weaken an individual’s immunity and leave them unable to effectively fight infections or manage disease. We will examine the consequences of chronic inflammation on the immune system, in the context of ectopic lymphoid organs. We will also examine immune system malfunctions in tumour development, and the role of viral infections in human cancer.
Probabilistic Deep Learning with TensorFlow 2
Imperial College London (via Coursera)
Welcome to this course on Probabilistic Deep Learning with TensorFlow! This course builds on the foundational concepts and skills for TensorFlow taught in the first two courses in this specialisation, and focuses on the probabilistic approach to deep learning. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real world datasets. This is a crucial aspect when using deep learning models in applications such as autonomous vehicles or medical diagnoses; we need the model to know what it doesn't know. You will learn how to develop probabilistic models with TensorFlow, making particular use of the TensorFlow Probability library, which is designed to make it easy to combine probabilistic models with deep learning. As such, this course can also be viewed as an introduction to the TensorFlow Probability library. You will learn how probability distributions can be represented and incorporated into deep learning models in TensorFlow, including Bayesian neural networks, normalising flows and variational autoencoders. You will learn how to develop models for uncertainty quantification, as well as generative models that can create new samples similar to those in the dataset, such as images of celebrity faces. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills. At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop a variational autoencoder algorithm to produce a generative model of a synthetic image dataset that you will create yourself. This course follows on from the previous two courses in the specialisation, Getting Started with TensorFlow 2 and Customising Your Models with TensorFlow 2. The a...
Validity and Bias in Epidemiology
Imperial College London (via Coursera)
Epidemiological studies can provide valuable insights about the frequency of a disease, its potential causes and the effectiveness of available treatments. Selecting an appropriate study design can take you a long way when trying to answer such a question. However, this is by no means enough. A study can yield biased results for many different reasons. This course offers an introduction to some of these factors and provides guidance on how to deal with bias in epidemiological research. In this course you will learn about the main types of bias and what effect they might have on your study findings. You will then focus on the concept of confounding and you will explore various methods to identify and control for confounding in different study designs. In the last module of this course we will discuss the phenomenon of effect modification, which is key to understanding and interpreting study results. We will finish the course with a broader discussion of causality in epidemiology and we will highlight how you can utilise all the tools that you have learnt to decide whether your findings indicate a true association and if this can be considered causal.
Quality Improvement for Population Health
Imperial College London (via Coursera)
Quality improvement methods were first deployed in healthcare in e hospital settings. However, over the past decade particularly, there has been increasing focus on the application of these methods in improving population and public health. In this course, you will apply a combination of both approaches to population health improvement. You will also learn how to study and evaluate large improvement initiatives to capture learning effectively. Learning Objectives: Apply quality improvement methods in combination with population health frameworks to design a population health improvement initiative Understand how the use of geographic information systems contributes to quality improvement Critique different study designs for studying quality improvement initiatives
Introduction to Quality Improvement in Healthcare
Imperial College London (via Coursera)
This course introduces you to the concepts, theories and application of Quality Improvement (QI) in healthcare from a global perspective. You will hear from patients, clinicians and academics what quality improvement means to them, and how they work together to deliver change. Studying the challenges, they faced and strategies they utilised to overcome those challenges, you will learn to apply and critique core QI methods, from experts in the field. By the end of this module you will be able to: 1. Recognise the characteristics of different approaches to quality improvement in order to critique them and make decisions as to when to deploy them. 2. Explain the necessary components of a structured approach to quality improvement in order to apply key quality improvement methods to support the planning, design, implementation and evaluation of improvement efforts.
Measuring Disease in Epidemiology
Imperial College London (via Coursera)
Epidemiological research is ubiquitous. Even if you don’t realise it, you come across epidemiological studies and the impact of their findings every single day. You have probably heard that obesity is increasing in high income countries or that malaria is killing millions of people in low income countries. It is common knowledge that smoking causes cancer and that physical activity is protective against heart disease. These facts may seem obvious today, but it took decades of epidemiological research to produce the necessary evidence. In this course, you will learn the fundamental tools of epidemiology which are essential to conduct such studies, starting with the measures used to describe the frequency of a disease or health-related condition. You will also learn how to quantify the strength of an association and discuss the distinction between association and causation. In the second half of the course, you will use this knowledge to describe different strategies for prevention, identify strengths and weaknesses of diagnostic tests and consider when a screening programme is appropriate.
XR in Healthcare Education and Clinical Practice
Imperial College London (via Coursera)
This course is designed to teach you about Extended Reality (XR) and how it's used in healthcare education and clinical practice. Using lessons from experts in the field and different case studies, this course shows you how to use this innovative technology in a way that creates sustainable, accessible real-world applications. The course considers Extended Reality (XR) from a number of perspectives. First of all, you will learn about the hardware and software considerations, then focus on education structures and frameworks and how Extended Reality is applied appropriately within this context. The final two weeks demonstrate how XR has been applied in real-world clinical practice and how you can best make use of the technology by understanding the impact of interdisciplinary expertise in the field. Overall, this course will help you to advance your use of Extended Reality, whatever your background, in clinical training and technologically-enhanced healthcare education contexts. You will also have the optional pathway of developing a business case alongside fellow learners. The business case can be the first step in promoting your XR idea or project to different stakeholders.
What Are Viruses And How Do We Work With Them?
Imperial College London (via Coursera)
This course describes the basic nature if viruses and basic concepts of how they replicate. It looks at traditional methods for propagating and assaying viruses as well as methods to identify and follow them in individuals and populations. It will also look at how we can use molecular genetics to learn how viruses work in molecular detail. On successful completion of the course, learners will be able to: 1. Recognise unifying principles but diversity of virus structure and function 2. Illustrate how we can detect, identify and track viruses in individuals and populations 3. Recognise the importance of traditional and molecular genetics to understanding viruses This is an intermediate series of courses intended for both clinical and non-clinical scientists who want to update their skills for work in clinical, academic, and pharmaceutical/bioscience industries, and is developed and delivered by experts working on viruses and novel vaccines. To be successful in this series of courses, you should have basic knowledge in biology, genetics, microbiology or related fields.
Public Involvement in Research
Imperial College London (via Coursera)
This course focuses on participatory approaches in research, known as 'public involvement' in the UK. You'll specifically, consider why citizens and patients would be involved in research and explore participatory approaches across and within the research cycle in more detail, diving into questions such as: what kinds of participation can be undertaken at each of the 7 stages of the cycle? how can you utilise participation in research? what examples of using participatory approaches exist in research? While this course, as with the rest of the specialisation, focuses on public health and ways of involving citizens and patients across and within the research cycle, these concepts apply to other disciplines and kinds of research too. So, you don't have to be a public health specialist or work in healthcare to gain insight from this course. If you would like to learn more about the theories and core principles of participation within a public health context, we suggest taking Introduction to Participatory Approaches in Public Health. If you're planning a research project and want to include participatory approaches, explore our course Applying Participatory Approaches in Public Health Settings.
Introduction to Creative Thinking: Tools for Success
Imperial College London (via Coursera)
Creativity concerns the development of new ideas. Throughout human history, the application of ideas has led to transformations of our daily lives and society. Modern business activity thrives on recently developed ideas, and it is through creativity that we address both challenges and opportunities. In this module, we will help you develop your implicit understanding and skills in creativity. You will be introduced to a series of creativity tools that can be used to augment the ideas you might come up with independently. Specifically, we will develop your skills in list, sticky-note, grid and alphabet brainstorming through an introduction to the principles of the tool, along with examples and an opportunity for you to have a go. A framework called the creativity diamond is used throughout the course to guide which approach to creativity to use and when. WHAT YOU WILL LEARN • The principal facets of creativity • Principles of creativity • A framework that can be used to guide which approach to creativity to use • Metrics that can be used in assessing creativity • The importance of managing our thinking • How to use and apply list, sticky note, grid and alphabet brainstorming SKILLS YOU WILL GAIN • Divergent and convergent creativity • Assessing creativity • Principles of brainstorming • List, sticky-note, grid and alphabet brainstorming
Customising your models with TensorFlow 2
Imperial College London (via Coursera)
Welcome to this course on Customising your models with TensorFlow 2! In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow. You will also expand your knowledge of the TensorFlow APIs to include sequence models. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills. At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop a custom neural translation model from scratch. TensorFlow is an open source machine library, and is one of the most widely used frameworks for deep learning. The release of TensorFlow 2 marks a step change in the product development, with a central focus on ease of use for all users, from beginner to advanced level. This course follows on directly from the previous course Getting Started with TensorFlow 2. The additional prerequisite knowledge required in order to be successful in this course is proficiency in the python programming language, (this course uses python 3), knowledge of general machine learning concepts (such as overfitting/underfitting, supervised learning tasks, validation, regularisation and model selection), and a working knowledge of the field of deep learning, including typical model architectures (MLP, CNN, RNN, ResNet), and concepts such as transfer learning, data augmentation and word embeddings.
Using Data for Healthcare Improvement
Imperial College London (via Coursera)
In this course, you will learn about the importance of measuring the quality of care and health outcomes in order to determine whether Quality Improvement(QI ) initiatives have achieved their aims. You will learn about how data is utilised to identify areas of improvement and the importance of using both quantitative and qualitative data in evaluating change. You will learn about the specific methods appropriate for improvement as distinct from methods more suited to research, including how to design measurement schemes suitable for improvement initiatives
Tobacco Control: Agile Policy, Research and Practice
Imperial College London (via Coursera)
This course teaches you about the global health harms caused by tobacco and the efforts underway to combat these. You'll analyse the strategies and tactics used by the tobacco industry, and their allies, to keep people buying their products, and you'll reflect on the role played by public health research in pushing back against this pressure with the ultimate aim of improving health. No matter your previous experience in this area, by the end of this course, you'll be able to describe the global harm to health caused by tobacco use and how policy is responding to this. You'll also be able to critique tobacco industry strategies that undermine tobacco control and discuss ways in which robust and timely research in strengthening tobacco control is key to policy and practice.
Mission Led Innovation: Designing a Sustainable Future
Imperial College London (via Coursera)
Welcome to Mission Led Innovation, a course designed to expand your ability to create impactful, future‑focused solutions to today’s most urgent environmental and societal challenges. Developed by leading academics and practitioners from Imperial College London and the Royal College of Art, and produced by Imperial's Learning Experience Futures team and Digital Media Lab, this course brings together world‑class expertise in design, technology, and enterprise. You will explore the principles, processes, and tools of interdisciplinary, Mission Led Innovation, and apply these new approaches to research, design, prototype, and deliver scalable solutions for people, planet, and nature. Whether you’re a student or graduate in engineering, design, or business, a senior professional or entrepreneur in one or more of these disciplines, or just want to make a difference, this course will elevate your creative confidence and capacity for a more empathetic and systematic approach to innovation that delivers real-world impact.
Introduction to Statistics & Data Analysis in Public Health
Imperial College London (via Coursera)
Welcome to Introduction to Statistics & Data Analysis in Public Health! This course will teach you the core building blocks of statistical analysis - types of variables, common distributions, hypothesis testing - but, more than that, it will enable you to take a data set you've never seen before, describe its keys features, get to know its strengths and quirks, run some vital basic analyses and then formulate and test hypotheses based on means and proportions. You'll then have a solid grounding to move on to more sophisticated analysis and take the other courses in the series. You'll learn the popular, flexible and completely free software R, used by statistics and machine learning practitioners everywhere. It's hands-on, so you'll first learn about how to phrase a testable hypothesis via examples of medical research as reported by the media. Then you'll work through a data set on fruit and vegetable eating habits: data that are realistically messy, because that's what public health data sets are like in reality. There will be mini-quizzes with feedback along the way to check your understanding. The course will sharpen your ability to think critically and not take things for granted: in this age of uncontrolled algorithms and fake news, these skills are more important than ever. Prerequisites Some formulae are given to aid understanding, but this is not one of those courses where you need a mathematics degree to follow it. You will need only basic numeracy (for example, we will not use calculus) and familiarity with graphical and tabular ways of presenting results. No knowledge of R or programming is assumed.
Introduction to Participatory Approaches in Public Health
Imperial College London (via Coursera)
This course will introduce you to participatory approaches to public health. You will learn about the history of participatory health research and why it is essential to solving contemporary public health challenges. The course will help you to understand the social and cultural context of public health, before introducing you to essential concepts for working with communities: knowledge and power. Finally, you will engage with critical analyses of participatory approaches, to help you to determine if and when such strategies are appropriate. Throughout the course you will analyse real-world case studies of community-based health projects, including historical HIV social movements, public health projects with sex workers, and participatory approaches to the COVID-19 pandemic. The course will equip you to practice public health in partnership with local communities. It is followed by a second course, Applying Participatory Approaches in Public Health Settings, which builds upon the theoretical foundations of this introductory course.
Interventions and Calibration
Imperial College London (via Coursera)
This course covers approaches for modelling treatment of infectious disease, as well as for modelling vaccination. Building on the SIR model, you will learn how to incorporate additional compartments to represent the effects of interventions, such the effect of vaccination in reducing susceptibility. You will learn about ‘leaky’ vaccines and how to model them, as well as different types of vaccine and treatment effects. It is important to consider basic relationships between models and data, so, using the basic SIR model you have developed in course 1, you will calibrate this model to epidemic data. Performing such a calibration by hand will help you gain an understanding of how model parameters can be adjusted in order to capture real-world data. Lastly in this course, you will learn about two simple approaches to computer-based model calibration - the least-squares approach and the maximum-likelihood approach; you will perform model calibrations under each of these approaches in R.
A Guide to Healthcare Innovation: Principles and Practice
Imperial College London (via Coursera)
This course reflects on global health challenges and the role of innovative solutions in addressing them. By engaging in this course, you will be able to describe the principles and key types of innovation in order to characterise the fundamental features of new models of care and technologies. This course will review the basic features and principles of healthcare innovation. You'll be examining innovations developed to address global health challenges, ranging from simple low-cost technologies readily deployed in resource constrained settings to more complex combinations of organizational, business model and technology innovations. Throughout this course, you'll also consider how adoption and diffusion is influenced by social, economic and political factors and explore what is required to get an innovation in to practice, effectively, at scale.
Survival Analysis in R for Public Health
Imperial College London (via Coursera)
Welcome to Survival Analysis in R for Public Health! The three earlier courses in this series covered statistical thinking, correlation, linear regression and logistic regression. This one will show you how to run survival – or “time to event” – analysis, explaining what’s meant by familiar-sounding but deceptive terms like hazard and censoring, which have specific meanings in this context. Using the popular and completely free software R, you’ll learn how to take a data set from scratch, import it into R, run essential descriptive analyses to get to know the data’s features and quirks, and progress from Kaplan-Meier plots through to multiple Cox regression. You’ll use data simulated from real, messy patient-level data for patients admitted to hospital with heart failure and learn how to explore which factors predict their subsequent mortality. You’ll learn how to test model assumptions and fit to the data and some simple tricks to get round common problems that real public health data have. There will be mini-quizzes on the videos and the R exercises with feedback along the way to check your understanding. Prerequisites Some formulae are given to aid understanding, but this is not one of those courses where you need a mathematics degree to follow it. You will need basic numeracy (for example, we will not use calculus) and familiarity with graphical and tabular ways of presenting results. The three previous courses in the series explained concepts such as hypothesis testing, p values, confidence intervals, correlation and regression and showed how to install R and run basic commands. In this course, we will recap all these core ideas in brief, but if you are unfamiliar with them, then you may prefer to take the first course in particular, Statistical Thinking in Public Health, and perhaps also the second, on linear regression, before embarking on this one.
Climate change and health
Imperial College London (via Coursera)
Climate change and health is the third and final instalment of the wider Global Health Challenges and Governance specialisation from Imperial College London's Global Master of Public Health (GMPH). The scope and content of this course has been developed from the ground up by a combined team of academics and practitioners in collaboration with experts from Imperial College’s Grantham Institute for Climate Change and the Environment. Through short video lectures, readings and a wide range of interactive activities, learners will be immersed in the intersection of climate change and health. Designed for those new to the discipline, over four modules (intended for one week of learning each), learners will become familiar with the relationship between globalisation, environmental change and health. Learners will be introduced to climate change, its influence on individual and public health and implications for policy: whether new to the topic, or coming with a wealth of experience. By the end of this course, learners will be familiar with planetary health, global climate governance structures and climate policy instruments. Learners will also be able to analyse relevant policies, evaluate their adequacy for tackling global health challenges and recommend alternative approaches where appropriate.
Immunology: Innate Immune System
Imperial College London (via Coursera)
Our immune system relies on an innate and an adaptive arm that communicate and collaborate to provide us with an optimal response against pathogens. This course focuses on our innate immunity which provides us our first, fast and inherited defence against infections. In this course, you will take a closer look at the mechanisms and cellular components involved in this swift response that occurs within minutes of exposure to a threat. Throughout the course, and guided by our active researchers, you will have opportunities to recognise its key protective mechanisms and to explain their importance for our overall health. You will learn about the mechanisms it uses to inform our adaptive immune system of the presence of a threat, and understand how some environmental factors, such as our own internal microbiome, influences it. Finally, you will have opportunities to reflect on current related issues and controversies in this fascinating field of research.
Study Designs in Epidemiology
Imperial College London (via Coursera)
Choosing an appropriate study design is a critical decision that can largely determine whether your study will successfully answer your research question. A quick look at the contents page of a biomedical journal or even at the health news section of a news website is enough to tell you that there are many different ways to conduct epidemiological research. In this course, you will learn about the main epidemiological study designs, including cross-sectional and ecological studies, case-control and cohort studies, as well as the more complex nested case-control and case-cohort designs. The final module is dedicated to randomised controlled trials, which is often considered the optimal study design, especially in clinical research. You will also develop the skills to identify strengths and limitations of the various study designs. By the end of this course, you will be able to choose the most suitable study design considering the research question, the available time, and resources.