Harvard University
Data Science: R Basics
4.4273 ratingsBuild a foundation in R and learn how to wrangle, analyze, and visualize data.
- edX
- 8 weeks, 2 - 3 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
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Mathematics courses
Learn Mathematics online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
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Harvard University
CS50's Introduction to Artificial Intelligence with Python
Learn to use machine learning in Python in this introductory course on artificial intelligence.
- edX
- 7 weeks, 7 - 22 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Harvard University
Data Science: Capstone
4.575 ratingsShow what you've learned from the Professional Certificate Program in Data Science.
- edX
- 2 weeks, 2 - 3 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Stanford Online
Cryptography I
4.84,483 ratingsCryptography is an indispensable tool for protecting information in computer systems. In this course you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. The course begins with a detailed discussion of how two parties who have a shared…
- Coursera
- 23 hours
- Self-paced
- Paid · free trial
- Paid certificate
Stanford Online
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
4.85,339 ratingsThe primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
- Coursera
- 4 weeks of study, 4-8 hours/week
- Self-paced
- Paid · free trial
- Paid certificate
- edX
- 4 weeks, 3 - 4 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Stanford Online
Graph Search, Shortest Paths, and Data Structures
4.82,001 ratingsThe primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social…
- Coursera
- 4 weeks of study, 4-8 hours/week
- Self-paced
- Paid · free trial
- Paid certificate
Stanford Online
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
4.81,278 ratingsThe primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
- Coursera
- 4 weeks of study, 4-8 hours/week
- Self-paced
- Paid · free trial
- Paid certificate
Microsoft
Add decision logic to your code in C#
Learn to branch your code's execution path by evaluating Boolean expressions.
- Microsoft Learn
- 45 minutes
- Self-paced
- Free course
- Free badge
- Beginner
Stanford Online
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
4.8832 ratingsThe 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).
- Coursera
- 4 weeks of study, 4-8 hours/week
- Self-paced
- Paid · free trial
- Paid certificate
Harvard University
Data Science: Inference and Modeling
4.454 ratingsLearn inference and modeling, two of the most widely used statistical tools in data analysis.
- edX
- 8 weeks, 2 - 3 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
The Georgia Institute of Technology
Computing in Python I: Fundamentals and Procedural Programming
4.7103 ratingsLearn the fundamentals of computing in Python, including variables, operators, and writing and debugging your own programs.
- edX
- 5 weeks, 9 - 10 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Beginner
MIT OpenCourseWare
Prediction: Machine Learning and Statistics
Prediction is at the heart of almost every scientific discipline, and the study of generalization (that is, prediction) from data is the central topic of machine learning and statistics, and more generally, data mining. Machine learning and statistical methods are used throughout the scientific wor…
- MIT
- Self-paced
- Free course
- Advanced
MIT OpenCourseWare
Advanced Natural Language Processing
This course is a graduate introduction to natural language processing - the study of human language from a computational perspective. It covers syntactic, semantic and discourse processing models, emphasizing machine learning or corpus-based methods and algorithms. It also covers applications of th…
- MIT
- Self-paced
- Free course
- Advanced
Harvard University
Principles, Statistical and Computational Tools for Reproducible Data Science
4.314 ratingsLearn skills and tools that support data science and reproducible research, to ensure you can trust your own research results, reproduce them yourself, and communicate them to others.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Intermediate
MIT OpenCourseWare
Geometric Folding Algorithms: Linkages, Origami, Polyhedra
This course focuses on the algorithms for analyzing and designing geometric foldings. Topics include reconfiguration of foldable structures, linkages made from one-dimensional rods connected by hinges, folding two-dimensional paper (origami), and unfolding and folding three-dimensional polyhedra. A…
- MIT
- Self-paced
- Free course
- Advanced
The University of Michigan
Programming for Everybody (Getting Started with Python)
4.7182 ratingsThis course is a "no prerequisite" introduction to Python Programming. You will learn about variables, conditional execution, repeated execution and how we use functions. The homework is done in a web browser so you can do all of the programming assignments on a phone or public computer.
- edX
- Self-paced
- Free to audit
- Paid certificate
- Beginner
Harvard University
Case Studies in Functional Genomics
4.87 ratingsPerform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.
- edX
- 5 weeks, 2 - 4 hours per week
- Self-paced
- Free to audit
- Paid certificate
- Advanced
IISc Bangalore
Mathematical Foundations of Generative AI
Computer Science and Engineering course by Prof. Prathosh A. P.
- NPTEL
- 12 weeks, 35 lectures
- Self-paced
- Free course
- Paid certificate
- Advanced
IISc Bangalore
Stochastic Approximation: Theory and Applications
Computer Science and Engineering course by Prof. Gugan Chandrashekhar Mallika Thoppe.
- NPTEL
- 12 weeks, 46 lectures
- Self-paced
- Free course
- Paid certificate
- Advanced