Here are some recommended online courses for various topics in research computing.
They are useful complements to your studies and the various Training Courses we provide here.
Algorithms and Data Structures¶
Introduction to Algorithms, Srini Devadas and Erik Demaine, MIT 6.006, 2011.
Research Software Engineering¶
Research Software Engineering with Python, The Alan Turing Institute.
Computational and Inferential Thinking: The Foundations of Data Science, Data 8: Foundations of Data Science course, UC Berkeley.
Causal Diagrams: Draw Your Assumptions Before Your Conclusions, Miguel Hernan, Harvard University.
Introduction to Causal Inference, Brady Neal.
Machine learning, Coursera, Andrew Ng.
Video lectures, CS229, Standford University.
Machine Learning for Intelligent Systems, Kilian Weinberger, 2018.
CS4780, Cornell: Video lectures.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition, Aurélien Géron, 2019, O’Reilly Media, Inc.
Maths for Machine Learning¶
Linear Algebra, Gilbert Strang, MIT 18.06, 2005.
Essence of linear algebra, 3Blue1Brown.
Essence of calculus, 3Blue1Brown.
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Gilbert Strang, MIT 18.065, 2018.