Algorithms, data structures, competitive programming, LeetCode
66 courses available
Showing 50 courses
Udemy
Beginner-friendly Data Science & Analytics course on Udemy with 2 hours of content. Rated 5.0/5 by 36 learners. Price: $19.99.
Udemy
The powerful K-Means Clustering Algorithm for Cluster Analysis and Unsupervised Machine Learning in R. Beginner-friendly Data Science & Analytics course on Udemy with 3 hours of content. Rated 4.8/5 by 43 learners. Price: $19.99.
Codeforces
Codeforces EDU - Algorithm Courses is a comprehensive advanced-level resource offered by Codeforces, focused on building practical skills in cybersecurity. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a hands-on, project-based learning platform where you learn by doing, not just watching. Instead of passive video consumption, you'll actively write code, solve problems, and build projects from the very first lesson. Research consistently shows that active practice leads to 3-5x better retention compared to passive learning. You'll make mistakes, debug issues, and develop real problem-solving skills that directly translate to workplace performance. This resource covers topics essential for success in cybersecurity, including network security, ethical hacking, penetration testing, and incident response. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Master Go syntax, goroutines, and channels Build concurrent programs with Go's lightweight threading model Create REST APIs and CLI tools in Go Deploy Go binaries to production servers Duration: Estimated duration: 40 hours of content, designed to be completed in 4-8 weeks at a comfortable pace. This is an advanced resource meant for learners who already have solid fundamentals. You should have at least 6 months of hands-on experience or have completed intermediate-level courses in this area. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into cybersecurity Freelancers wanting to add new services to their portfolio Self-learners passionate about cybersecurity and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as Security Analyst, Penetration Tester, SOC Analyst, Security Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 4-9 LPA Mid-level / 2-5 years: Rs 10-22 LPA Senior / 5+ years: Rs 25-50 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Wipro, HCL, Deloitte, PwC, government agencies. India faces a cybersecurity talent shortage of 500,000+ professionals. With increasing digitization and cyber threats (India saw a 300% increase in cyberattacks in 2024), organizations are desperate for security talent. The Indian government's push for data localization and regulations like DPDP Act 2023 have further increased demand. Cybersecurity professionals enjoy some of the highest job security in tech — once skilled, you're virtually recession-proof. Codeforces is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Udemy
Learn How To Crack The Algorithm, Boost Your Content Organically and Create Consistent Viral-Worthy Content on TikTok. Advanced-level Digital Marketing course on Udemy with 1 hour of content. Rated 4.7/5 by 10 learners. Price: $99.99.
Udemy
Various Searching Algorithm Used in AI. Beginner-friendly AI & Machine Learning course on Udemy with 1 hour of content. Rated 4.7/5 by 15 learners. Available for free.
Udemy
Learn how to "Hack" the TikTok algorithm to attract millions of views to your page completely for free (organically). Beginner-friendly Business & Finance course on Udemy with 3 hours of content. Rated 4.7/5 by 8 learners. Price: $34.99.
Udemy
Learn the concepts of the PLS algorithm, reliability and validity, bootstrapping, mediation and moderation. Beginner-friendly Business & Finance course on Udemy with 11 hours of content. Rated 4.7/5 by 344 learners. Available for free.
Udemy
Learn how you can use the Facebook algorithm to your advantage and get more organic reach for FREE. Beginner-friendly Digital Marketing course on Udemy with 1 hour of content. Rated 4.6/5 by 11 learners. Price: $19.99.
Udemy
Bring in a Hyper Targeted Audience, Understand The Instagram Algorithm, & Use Most Efficient Hashtags to Maximize Growth. Beginner-friendly Digital Marketing course on Udemy with 1 hour of content. Rated 4.5/5 by 2 learners. Price: $34.99.
Udemy
Machine learning algorithm (ANN) - simplified. See the use cases with R to understand the application. Beginner-friendly Data Science & Analytics course on Udemy with 1 hour of content. Rated 4.5/5 by 26 learners. Price: $19.99.
Udemy
Complete Guide - Understand how the Facebook Algorithm works, Crucial Newsfeed updates + Facebook approved Strategies. Advanced-level Digital Marketing course on Udemy with 1 hour of content. Rated 4.5/5 by 28 learners. Price: $79.99.
Udemy
Learn to use an evolutionary algorithm to train and evolve efficient artificial neural networks. Beginner-friendly Data Science & Analytics course on Udemy with 1 hour of content. Rated 4.4/5 by 14 learners. Price: $27.99.
Udemy
Develop your Problem-Solving skill! Practical step-by-step guide for resolving Complex Problems. Beginner-friendly Business & Finance course on Udemy with 5 hours of content. Rated 4.3/5 by 232 learners. Price: $94.99.
Udemy
Beginner-friendly Web Development course on Udemy with 2 hours of content. Rated 4.2/5 by 1,989 learners. Available for free.
Udemy
Google's HummingBird update was the biggest change in Google algorithm away from Pagerank. Learn how to rank on it. Beginner-friendly Digital Marketing course on Udemy with 1 hour of content. Rated 4.0/5 by 13 learners. Price: $189.99.
Udemy
Learn how to classify images using KNN algorithm. Beginner-friendly AI & Machine Learning course on Udemy with 2 hours of content. Rated 4.0/5 by 13 learners. Price: $19.99.
Udemy
stacks,queues,Searching Algorithms,Sorting Algorithms,Graphs. Beginner-friendly Cybersecurity course on Udemy. Rated 4.0/5 by 1 learners. Price: $19.99.
Udemy
Learn Data structure and algorithms using C. Beginner-friendly Data Science & Analytics course on Udemy with 2 hours of content. Rated 3.9/5 by 72 learners. Available for free.
Udemy
Watch powerful MTFT indicator generated on any Stock symbol. Signals are based on a Multi-parameter algorithm. Beginner-friendly Business & Finance course on Udemy with 1 hour of content. Rated 3.7/5 by 40 learners. Available for free.
Udemy
Learn Bio Inspired Optimization Methods like Genetic Algorithm and Particle Swarm Optimization. SourceCodes Included. Beginner-friendly AI & Machine Learning course on Udemy with 3 hours of content. Rated 3.5/5 by 11 learners. Price: $149.99.
Udemy
Leverage TikTok algorithm for 2022 GROWTH | practical solutions to account issues. Beginner-friendly Digital Marketing course on Udemy with 1 hour of content. Rated 3.5/5 by 55 learners. Price: $19.99.
Udemy
Discovering the Instagram hidden Algorithm. Beginner-friendly Digital Marketing course on Udemy with 1 hour of content. Rated 3.5/5 by 4 learners. Price: $49.99.
Udemy
Overview of different machine learning algorithms, their pros & cons, and use cases where different algorithms fit. Beginner-friendly AI & Machine Learning course on Udemy with 3 hours of content. Rated 3.5/5 by 12 learners. Price: $49.99.
Udemy
Managing a replicated log. Beginner-friendly Cybersecurity course on Udemy with 1 hour of content. Rated 2.8/5 by 4 learners. Price: $1.
Udemy
Learn How To Become A Highly Profitable Trader Without Losing Time Or Money!. Beginner-friendly Business & Finance course on Udemy with 1 hour of content. Rated 2.8/5 by 3 learners. Price: $149.99.
Udemy
Learn how to solve optimization problem using Genetic Algorithm Optimization Method. Beginner-friendly Data Science & Analytics course on Udemy with 1 hour of content. Rated 2.3/5 by 22 learners. Price: $74.99.
Packt
Unlock the power of algorithms and data structures with this comprehensive course. Begin your journey by mastering essential concepts such as Big O notation, space complexity, and recursion. Through clear explanations and practical examples, you'll learn to analyze algorithm efficiency and optimize solutions for real-world challenges. Dive into fundamental data structures, including arrays, linked lists, stacks, queues, and hash tables. Explore advanced topics like trees, heaps, and tries, with insights into binary trees, AVL trees, and graph structures. Each module builds on the last, blending theory with hands-on coding in Python to solidify your understanding. The course emphasizes a step-by-step approach, making complex concepts accessible. Learn not just the "how" but also the "why," with practical applications such as priority queues, hashing, and dynamic programming. Whether it's mastering sorting algorithms or implementing efficient search methods, you'll gain the skills to solve problems efficiently. Designed for aspiring developers, computer science students, and professionals, this course requires basic programming knowledge. It's perfect for anyone ready to enhance their problem-solving abilities and prepare for technical interviews. With beginner-to-intermediate difficulty, you'll be well-equipped to tackle coding challenges confidently.
Coursera
Discover how YouTube’s powerful algorithm decides what content gets surfaced—and how you can work with it to grow your audience. In this course, you’ll learn how YouTube evaluates videos across key metrics like watch time, click-through rate, and retention. You’ll explore how Shorts, live streams, and long-form content are promoted differently, and how to use YouTube Studio to analyze performance. By the end, you’ll be able to create content that aligns with YouTube’s recommendation systems while staying true to your creative vision.
Massachusetts Institute of Technology (via edX)
Sorting Truth From Fiction: Civic Online Reasoning
Northeastern University (via Coursera)
This course will guide you through the essential principles of algorithms and their significance in computational problem-solving. You'll begin by exploring what an algorithm is, its core characteristics, and how it applies to real-world scenarios—from simple everyday tasks to complex computing challenges. As you progress, you will learn about the critical role algorithms play in improving efficiency and scalability across various fields. We’ll break down key concepts such as algorithmic complexity, helping you evaluate the efficiency of different approaches, which will ultimately guide your decision-making.
Coursera
In this 2 hours guided project, you will discover the art of game development with Cby building a formidable Tic-Tac-Toe agent using the powerful Minimax algorithm. This hands-on project will guide you through the intricacies of game AI development, from understanding the fundamental principles of the Minimax algorithm to implementing it in a practical Tic-Tac-Toe project. To achieve this, you will implement advanced Ctechniques and constructs such as recursion, decision trees, and LINQ to represent the game state, explore possible moves, evaluate outcomes, and make optimal decisions. By the end of this course, you'll have a solid grasp of adversarial search and the ability to build sophisticated game-playing agents. This project is aimed for intermediate Cdevelopers and AI engineers. To succeed in this project, you will need to be comfortable with core Cconcepts such as classes, interfaces, methods, if statements, and loops. You also need to be comfortable in working with VS Code.
University of Colorado Boulder (via Coursera)
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Coursera
Ready to master the art of algorithm efficiency? In today's multimodal AI landscape, fusion algorithms are the backbone of intelligent systems, but poorly optimized code can cripple performance and drain resources. This Short Course empowers ML engineers and AI professionals to systematically analyze computational complexity and memory footprints of fusion algorithms, enabling you to make strategic optimization decisions that dramatically improve system performance. By the end of this course, you will be able to decompose fusion algorithms into fundamental operations, calculate time and space complexity using Big O notation, and propose targeted optimizations like sparse-attention alternatives that can reduce memory usage by 30% or more. This course is unique because it bridges theoretical complexity analysis with hands-on profiling tools like cProfile, giving you immediately applicable skills for real-world optimization challenges. To be successful, you should have experience with machine learning algorithms and basic understanding of computational complexity concepts.
EDUCBA
Learners will develop the ability to explore, visualize, and interpret data using R, ggplot2, and linear analysis techniques to generate meaningful insights. By the end of this course, learners will confidently apply exploratory data analysis (EDA) methods to understand data structure, identify patterns, visualize relationships, and evaluate linear trends. This project-based course guides learners through a complete EDA workflow, starting from understanding datasets and variable types to creating professional-quality visualizations using the grammar of graphics. Learners will analyze univariate and bivariate data, customize plots for clarity, detect outliers, and visually assess linear relationships using regression techniques. Each concept is reinforced through hands-on practice with real-world data scenarios. What makes this course unique is its strong emphasis on practical visualization-driven analysis, not just theory. Learners gain experience producing production-ready plots and interpreting analytical results in a way that supports data-driven decision-making. This course is ideal for aspiring data analysts and professionals who want to strengthen their EDA, data visualization, and analytical storytelling skills using R.
MIT OpenCourseWare
With educators from around the world and faculty from MIT and Stanford University, you will learn quick and effective practices for evaluating online information that you can bring back to your classroom. The Stanford History Education Group has distilled these practices from observations with professional fact-checkers from the nation’s most prestigious media outlets from across the political spectrum. Using a combination of readings, classroom practice lessons, and assignments, you will learn how to teach the critical thinking skills needed for making wise judgments about web sources. At the end of the course, you will be better able to help students find reliable sources at a time when we need it most. This course is part of the Open Learning Library, which is free to use. You have the option to sign up and enroll in the course if you want to track your progress, or you can view and use all the materials without enrolling. Level: Beginner. Free course materials from MIT OpenCourseWare including lecture notes, assignments, and exams.
Udemy
Using the Fast Fourier Transform and the DFT-Goertzel algorithm to detect cycles in noisy data sets (financial markets). Beginner-friendly Business & Finance course on Udemy with 1 hour of content. Price: $49.99.
Northeastern University (via Coursera)
This course will guide you through the essential principles of algorithms and their significance in computational problem-solving. You'll begin by exploring what an algorithm is, its core characteristics, and how it applies to real-world scenarios—from simple everyday tasks to complex computing challenges. As you progress, you will learn about the critical role algorithms play in improving efficiency and scalability across various fields. We’ll break down key concepts such as algorithmic complexity, helping you evaluate the efficiency of different approaches, which will ultimately guide your decision-making.
Tsinghua University (via Coursera)
By learning this course, you will get a comprehensive grasp of vector and list and the ability to use them in solving real problems. By the end of this course, you will be able to evaluate data structures and algorithms in terms of asymptotic complexity, analyze storage/time complexity of iterative/recursive algorithms, implement vector and list, understand/implement basic sorting algorithms such as Bubblesort, Insertionsort, and Selectionsort, understand/implement search algorithms such as Binary Search, Fibonacci Search, and Interpolation Search, use vector and list in problem-solving. 通过学习本课程，你将得到向量和列表的全面理解以及使用向量和列表解决实际问题的能力。 在本课程结束时，你将能够根据渐进复杂度评估数据结构和算法，分析迭代/递归算法的空间/时间复杂度，实现向量和列表， 了解/实现基本排序算法（例如冒泡排序、插入排序和选择排序），理解/实现搜索算法（例如二分搜索、斐波那契搜索和插值搜索）， 使用向量和列表解决问题。
IIT Bombay (via NPTEL)
NOC:Bandit Algorithm (Online Machine Learning) — a free online course offered by IIT Bombay through the NPTEL platform. Taught by Prof. Manjesh Hanawal. This is an intermediate-level course designed for undergraduate and postgraduate students. Estimated duration: 30 hours (~4 days). Category: AI & Machine Learning. Certification available through SWAYAM with a nominal exam fee. All video lectures, assignments, and course materials are freely accessible.
Tsinghua University (via Coursera)
By learning this course, you will get a comprehensive grasp of stack, queue, binary tree, graph and BST structures and algorithms, as well as their applications. By the end of this course, you will be able to understand and implement stack, queue and binary tree, use binary trees to solve problems such Huffman encoding, understand and implement the graph structure as well as related algorithms such BFS, DFS and PFS, understand and implement AVL tree. 通过学习本课程，你将全面了解栈、队列、二叉树、图和二叉搜索树结构、算法及其应用。 在本课程结束时，你将能够理解和实现栈、队列和二叉树，使用二叉树解决霍夫曼编码等问题，理解并实现图结构以及相关算法（例如BFS，DFS和PFS），理解并实现AVL树。
Coursera
By the end of this project you will create an application that uses the CList data structure and the CLinq to process a collection of Employees in a file. Linq, when used with the List data structure, allows the programmer to compare and perform computations on objects without the need to access attributes directly. It simplifies the process of iterating through a list and obtaining data from user-defined objects. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
MIT OpenCourseWare
This is a research-oriented course on algorithm engineering, which will cover both the theory and practice of algorithms and data structures. Students will learn about models of computation, algorithm design and analysis, and performance engineering of algorithm implementations. We will study the design and implementation of sequential, parallel, cache-efficient, external-memory, and write-efficient algorithms for fundamental problems in computing. Many of the principles of algorithm engineering will be illustrated in the context of parallel algorithms and graph problems. Level: Beginner. Free course materials from MIT OpenCourseWare including lecture notes, assignments, and exams.
University of Illinois Urbana-Champaign (via Coursera)
The Unordered Data Structures course covers the data structures and algorithms needed to implement hash tables, disjoint sets and graphs. These fundamental data structures are useful for unordered data. For example, a hash table provides immediate access to data indexed by an arbitrary key value, that could be a number (such as a memory address for cached memory), a URL (such as for a web cache) or a dictionary. Graphs are used to represent relationships between items, and this course covers several different data structures for representing graphs and several different algorithms for traversing graphs, including finding the shortest route from one node to another node. These graph algorithms will also depend on another concept called disjoint sets, so this course will also cover its data structure and associated algorithms.
Johns Hopkins University (via Coursera)
This is part of our specialization on Making Decision in Time. For this third course we start with an intriguing study on SFPark and build new insights into the ideas that flow from this direction. The ending point should bring new code and new algorithm insights into perspective, and use, by many computer and data scientists.
University of Pennsylvania (via edX)
Algorithm Design and Analysis
Johns Hopkins University (via Coursera)
A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.
MIT OpenCourseWare
Wavelets are localized basis functions, good for representing short-time events. The coefficients at each scale are filtered and subsampled to give coefficients at the next scale. This is Mallat’s pyramid algorithm for multiresolution, connecting wavelets to filter banks. Wavelets and multiscale algorithms for compression and signal/image processing are developed. Subject is project-based for engineering and scientific applications. Level: Beginner. Free course materials from MIT OpenCourseWare including lecture notes, assignments, and exams.
Johns Hopkins University (via Coursera)
This Teach Out does not issue certificates of completion. Algorithms – and algorithmic bias – are making regular appearances in the news, and increasingly, are being recognized as a policy issue. But what is an algorithm, exactly? And what does it mean when someone describes an algorithm as biased? This Teach-Out will encourage policy makers, agency leaders, and others in similar positions to identify algorithms that are already in use and make connections to broader ideas about fairness, justice, and equity. After completing the Teach-Out, learners will be able to participate in discussions around algorithmic bias, inform others about how algorithms can perpetuate existing disparities, and take steps to reduce the impact of algorithmic bias on the people and communities they serve.
Udemy
data structure-master the linked lists and solve the interview questions - اجتياز مقابلة العمل - فهم اللوائح المترابطة. Beginner-friendly Web Development course on Udemy with 3 hours of content. Price: $19.99. Taught in Arabic.
Stanford University (via Coursera)
The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).