YouTube playlists

A curated list of academic courses and lectures that I found on YouTube–I enjoyed learning from them. It started from one of my Twitter threads.

Academic guide

• Short guide on proposal writing from the ERC

Academicians

I think adding videos on scientists to this list makes sense.

• A series where Rob Phillips is interviewed by David Zierler for the Caltech Heritage project. Inspiring and bold!
• A playlist with an extended interview of an intriguing academic: Freeman Dyson.

Biophysics

• Physical Biology of the Cell (Winter 2022) by Rob Phillips. Genuinely inspiring, as Phillips always is.
• Molecular Biophysics by Erik Lindahl. Lots of insider knowledge on biophysical systems.
• Introduction to Neuroscience by Bing Wen Brunton. Very well-organized lectures.
• A very well-produced set of tutorials on PyMOL from Molecular Memory.
• A useful introduction to Proteomics. Great for non-biologists.
• An introductory biophysics by Ali Hassanali. Well-organized lectures.

Computer science

• Introduction to parallel Programming in Open MP NPTEL course by Yogish Sabharwal from IIT Delhi
• A short series on asymptotic notation and analysis of algorithms by David Scot Taylor. Check his YouTube channel, Algorithms with Attitude, for more stuff.
• HPC by Matthew Jacob from IISc
• Improving and optimizing Python by Sebastian Mathôt
• Intro to parallel programming
• Introduction to SLURM
• Pointers in C and C++
• Message-passing programming with MPI
• C++ by iamcanadian

Philosophy

• Karl Popper - Science: Conjectures and Refutations by Victor Gijsbers. He is a good teacher. Check his channel for more playlists, e.g. he is currently (March 2024) teaching epistemology.
• Philosophy of the humanities
• Philosophy of Science by Paul Hoyningen

Quantum mechanics

• Foundations of Quantum Mechanics by Florian Marquardt. Fun slides on an intriguing topic.
• Another really great series on Foundations of Quantum Mechanics. This one is by Rob Spekkens.
• Lectures on Quantum Computing. It's very much worth watching despite the poor recording quality.
• Introduction to Quantum Information Science by Artur Ekert. Ekert is a patient teacher. The accompanying free book is useful, too.
• Quantum entanglement by Mark Wilde

Statistical mechanics

• Non-equilibrium Statistical Mechanics by V. S. Balakrishnan. Slow-paced, careful lectures covering a lot of topics.
• An excellent introductory lectures on statistical mechanics by John Preskill

Statistics and Machine learning

• Deep Learning by Frank Noe. Leisurely paced, meticulous.
• Roman Vershynin has two neat series on probability theory: Undergraduate Probability and High-Dimensional Probability. He teaches with care and patience.
• Singular Value Decomposition by Steven Brunton. Delightful variations on a theme. Exceptionally clear set of lectures.
• Machine learning course by Yaser Abu-Mostafa. Especially useful for its introductory discussion on learnability and VC dimension.
• Bayesian methods by RIchard McElreath
• Statistics for application by Phillippe Rigollet

Writing

• Writing in the Sciences by Kristin Sainani. If you're starting to write scientific prose, watch the series. Seriously.
• The Writer's workshop. Short guides from Ted-Ed.
• Writing Style—An Online Guide. Good solid introduction to English grammar and writing beyond simple definitions. I got to know about this nice book on rhetorical grammar from these lectures.
• Grammar and Stylistics: Writing Clearly by Randall Eggert from University of Utah. Excellent! See, for example, the one on tense and aspect.

Mathematics

• Visual group theory

Visualization

• Inkscape explained by Logos by Nick
• Inkscape tutorials by TJ Free
• Inkscape tutorial for beginners (really good)