- R Shiny Tutorial - Building Interactive Web Apps in R using Shiny,
- R Statistics Programming - Bioinformatics - Lectures,
- Introduction to Programming in R Statistical Software,
- R Statistics Essential Training,
- R Tutorial Videos,
- R Programming Tutorials Playlist,
- R tutorial - Learn R Programming,
- R Programming Software and Statistics Tutorials (All Videos),
- YaRrr! Course,
- Introduction to R Programming,
- Analytics on R,
- D& R for the Analysis of Big Data by William S. Cleveland,
- Introduction to Machine Learning by Dale Schuurmans,
- PURDUE Machine Learning Summer School 2011,
- Large-scale ML and Stochastic Algorithms by Leon Bottou,
- Optimization for Machine Learning by S.V.N Vishwanathan,
- Reinforcement Learning by Satinder Singh Baveja,
- DeepLearningBook,
- Deep Learning,
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Mathematics - Advanced Matrix Theory and Linear Algebra for Engineers
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Leveraging Computer Vision and MATLAB for Advanced Driver Assistance Systems (ADAS)
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Python Q&A with Dan – Your Python/Career questions answered | #PythonQA,
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1-7: Foundations of Programming in JavaScript - p5.js Tutorial,
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C++ Programming Tutorial for Beginners (For Absolute Beginners),
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C++ Programming Video Tutorials For Beginners [ Complete Series ],
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MIT 10.34 Numerical Methods Applied to Chemical Engineering,
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Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017),
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MIT RES.10-001 Making Science and Engineering Pictures: A Practical Guide to Presenting Your Work,
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MIT 6.0002 Introduction to Computational Thinking and Data Science,
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Great Ideas in Theoretical Computer Science at CMU (incomplete),
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MIT Course 9.520 - Statistical Learning Theory and Applications,
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Algebra II (Core Course Jan - Apr 2014) By Prof. K. N. Raghavan,
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NNMCB Course on Mathematical and ComputationalBiology - Computers,
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6.0001 Introduction to Computer Science and Programming in Python. Fall 2016,
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Approximate Dynamic Programming Lectures by Dimitri P. Bertsekas,
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2016 Argonne Training Program on Extreme Scale Computing (ATPESC),
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CPython internals: A ten-hour codewalk through the Python interpreter source code,
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UC Berkeley CS10 Beauty and Joy of Computing Fa10 (1080p HD),
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18.409 Algorithmic Aspects of Machine Learning Spring 2015 MIT,
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Making Control System Development Easier with MATLAB and Simulink,
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6.041 Probabilistic Systems Analysis and Applied Probability,
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Mini-course: ""Introduction to Analytic Number Theory"" by Ram Murty [2015]",
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Learning medical statistics with python and Jupyter notebooks,
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Make Better Software: The Training Series (Complete Series),
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Finite element Method by Mr. Ravi Pratap Singh e-content for AKTU,
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RSS Workshop ""Are the sceptics right? Limits and Potentials of Deep Learning in Robotics""",
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MIT 8.333 Statistical Mechanics I: Statistical Mechanics of Particles,
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[ANSYS Workbench Tutorial : thermal,](https://www.youtube.com/watch?v=pw1Tcjfb0Vo&list=PLCaeQHGbPOQBHt37XPTKe6OeLkKOwVt0e, transient, fluent, frictional contact for beginner and advance level)
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HyperMesh | Pre processing | 2D | 3D | Meshing | ANSYS | Tutorial |,
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Spring 2015 -- Computer Architecture Lectures -- Carnegie Mellon,
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Delft University-Aerospace Engineering\Introduction to Aerospace Engineering II,
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Delft University-Aerospace Engineering\Introduction to Aerospace Engineering I,
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[Coursera] Neural Networks for Machine Learning — Geoffrey Hinton 2016,