Just watch the first lecture and you won't be able to not watch the rest. It starts with making your own autograd engine in 100 lines of python, similar to PyTorch and then builds up to a GPT network. He's one of the best in the field, founder of OpenAI, then Director of AI at Tesla. Nothing like the scam tutorials that just copy-paste random code from the internet.
The "Let's build GPT: from scratch, in code, spelled out." demystifies so much of machine learning and chatbots. It's so cool to see how simple python code can be leveraged into something so amazing.
I did not know that. It is amazing how perception of HN changes drastically once you turn this flag on. It is not as extreme as "turning into a completely different website" but certainly it becomes less interesting. There is a sizeable amount of toxicity.
Yes. That's one cost of having a large, open, optionally-anonymous internet forum. We can't stop such posts but consigning them to a separate partition seems to work ok.
Let me help you there. Have you considered writing: "I think this lecture series is overrated, because $SERIES_A and $SERIES_B is much better, because ..."
Or you could explain why you dislike the communication style, the pace or anything else that others could also relate to.
This way we can just guess, and guessing includes bad options like "dev_0 just had a petty conflict with the lecturer" or "dev_0 tried themselves to teach this and did worse so it is envy".
So if you want to provide value, please explain yourself or just don't comment with one word in the future. If you don't want to provide value, consider commenting on youtube instead.
YouTube’s default comment sort appears to do sentiment analysis to decide what to show - even remotely negative comments and replies I’ve made simply do not show up unless you switch to “New”
It appears to work - nearly all videos appear chock full of only positive feedback.
I think the comment provided value. I was about to start watching it but now I won't and I don't really care why they think that. The fact that someone thinks it's so overrated that they need to comment on it is enough.
That would be great. My ever-expanding backlog gives me anxiety so I'm always looking for an escape hatch. A small comment like that is enough to give me peace and lose the FOMO.
Alright, I'll bite. What makes you feel that way, and what do you prefer for the same subject matter instead? I don't know of many people posting this type of content in a raw format to youtube.
The best lecture series I have seen till date ( and I have seen lectures by top professors across great institutions in multiple countries) is Classical Physics by V. Balakrishnan from IIT Madras, India [1]. Only people who have thought about concepts deeply over a lifetime can deliver such truly delightful lectures. If you have an hour to spare, just listen to the first lecture [2] and it will profoundly impact your outlook on science (and physics in particular)
His entire family has had storied research careers and highly regarded in their fields. Radha Balakrishnan, his wife, is a retired theoretical physicist, their son Hari Balakrishnan is a professor of CSAIL at MIT and daughter Hamsa Balakrishnan is a professor of aeronautics at MIT.
For those not in the know NPTEL has a boatload of high quality STEM content. Often they will be the only place you can find the more advanced courses on certain less popular STEM courses.
Not sure best ever, but I really enjoyed “The Other Side of History” (available from Great Courses Plus now Wonderium). I found the deep dive into daily life through history helped me better understand the common threads that all humans experience.
Course Description:
Imagine you're a Greek soldier marching into battle in the front row of a phalanx. Or an Egyptian woman putting on makeup before attending an evening party with your husband. Or a Celtic monk scurrying away with the Book of Kells during a Viking invasion. Welcome to the other side of history, the 99% of ordinary people whose names don't make it into the history books—but whose lives are no less fascinating than the great leaders whose names we all know. Here you'll encounter such diverse individuals as:
a Mesopotamian hunter-gatherer making a living in one of the world's earliest permanent settlements;
an Egyptian craftsman decorating the pharaoh's tomb in the Valley of the Kings;
a Minoan fleeing the island of Santorini during a volcanic eruption;
a Greek citizen relaxing at a drinking party with the likes of Socrates;
a Roman slave captured in war and sent to work in the mines; and
Thanks for this recommendation. It sounds like something I'd be interested in and I just found the audiobook for free as part of my Audible membership.
Gilbert Strang's lectures on Linear Algebra [1]. Prof Strang is an amazing lecturer with a unassuming style. He's the expert on Linear Algebra and makes the topic so much approachable.
Ken Joy's lectures on Computer Graphics [2]. Prof Joy is another amazing lecturer, making the Computer Graphics topics seeming easy.
Stanford CS221 Learn AI (2019) by Percy Liang and Dorsa Sadigh. Both professors are great lecturers. Andrew Ng's ML class was great, but it was more academically tuned. CS221 is more on the practical side and is more updated as ML is progressing fast.
Micromouse 2021-2022 by UCLA [4]. It's a short series taught by graduate students and probably it's incomplete, but the content and teaching are amazing. I wish I had this kind of class when I was in school. The teaching and materials are very approachable and easy to understand. It shows how basic electronic components and basic circuitry work. It shows how to put them together and how to write simple programs to control the components. The end result is a robotic mouse that can traverse mazes with seemingly intelligence.
Can you articulate on the first one? In the last semester I tutored for a Linear algebra course which used his book and it was a nightmare. Ideas seems to be presented in reverse order and a lot of students ended up having trouble understanding basic concepts.
So strange. It was the best book I’ve read about the topic. It’s been a while, but I don’t recall anything not presented in the right order. Going from linear equations to a geometric interpretation of the rows, then to linear combination of the columns. Then Gauss-Seidel to LRU.
I liked his approach of “ideas first, rigor later”. I think after reading this book, you can easily grab a book with more formalism, if you feel lacking rigor.
I’m interested to understand where you felt the order was wrong?
A bit everywhere. One thing that really bothered me is that you have to wait until chapter 3 to introduce the notion of vector spaces. I know that it is not an easy concept to grasp, but once you manage to understand it a lot of previous things become trivial.
When I was first introduced to the idea of solving linear equations, we already had the idea of space vectors and basis, so solving a system of equations was just an application of finding the coefficients of the linear combination.
> I liked his approach of “ideas first, rigor later”. I think after reading this book, you can easily grab a book with more formalism if you feel lacking rigor.
This sentence made me think. Maybe there was a disconnect between my experience (Physics background, bottom-up approach) and the one taught in the course (Data science for Linguistic, top-down). Each time I tried to use the notion and examples I had in mind with the students I found myself hitting a wall because they had not covered the topics yet.
You probably already know about them, but just in case: have you watched 3b1b's videos about Linear Algebra? Those did open my mind and improved my understanding of linear algebra.
I tried Strang in uni and it was about the worst linear algebra book I tried. Kostrikin on the other hand was perfect — he struck the right balance between geometric intuition and formal rigour.
I haven't used his book, just watched the Youtude videos. His teaching went slowly with simple examples. He explained them really well.
There're a lot of materials, much more than one would care. He covered many topics. I just jumped to the ones I needed to learn at the time. I had Linear Algebra background so most were just a refresher for me. As a student attending the class the first time, it might be overwhelming to learn all those material in a semester.
I think for someone more interested in the formal side of things, Strang is definitely a little weird. I bounced right off it, and to this day don't really know what the rows are supposed to be about. Axler was perfect for me. But for developing an intuition for the nitty gritty operations, I think Strang is probably pretty good.
Human Behavioral Biology, a Stanford course taught by Robert Sapolsky. It's a thorough look on some of our behaviors through the lens of hormones, neural/nervous system, and how evolution shaped us. Also, Pr Sapolsky is a great speaker with a complete deadpan humor.
This would be my choice too. He's a good storyteller.
Although like all good storytellers, don't believe everything he says. I looked up a couple of his more bizarre anecdotes, and they usually turn out not to be true. The one example I can remember is women living close together sync'ing up their menstrual period. That turned out to be probably a case of the researchers underestimating the intricacies of the statistics necessary to show that cyclic phenomenon of not quite the same length adjust towards each other.
I have this thing when lecturers are engaging that I have even more trouble believing them going forward if they make an error.
I came to that point about the cycle synchronization in his lecture series and I had to stop. Not entirely because of the error, but because the phenomenon he cited was controversial well before he gave those lectures. That tells me he was not one to a) update his beliefs b) predisposed to falsifying his beliefs/seeking out contrary evidence or c) acknowledge disagreement about a phenomenon
Any one or combination of those qualities makes me skeptical when one is teaching a "science". So rather than spend the rest of the series second guessing everything he said, I stopped watching. It's a shame, he's really a great lecturer.
This is one of the great disconnects between computer scientists and biologists. Computers are man-made, and fundamentally knowable - answers will be definitively, provably, right or wrong.
Biology is different. Sure, at a molecule level, you can make definite conclusions. "This drug binds to that receptor."
But the kind of biology that is immediately useful to humans - where it touches on psychology or sociology - is too complex to get 100% right. So how do you do 'science' in these fields?
The answer is that you make up some cohesive theory based on existing research and do studies in that direction. You try to prove yourself right.
And it works! Theories that come out of this sort of research can turn out to be 100% true. Or 90% true - where they are wrong under some conditions, but still very useful. Or they can be complete bunk - not predictive, and a waste of time.
When anyone presents a cohesive theory of a complex system, they are probably not 100% right. Doesn't make them entirely wrong, though, and certainly not useless.
I have trouble trusting information from sources that aren't self-critical or aware of the conversation associated with the research they're citing.
And probably hypocritically, I also want to kick back, turn off the critical side of my brain and enjoy the lectures and get some learning for free while not questioning every claim. Edutainment so to speak. But that requires a lot of trust, and if that trust seems threatened, I can't in good conscience continue my lazy learning.
That’s a common misconception, especially among people who have only shallow acquaintances with really complex computer systems, amplified by deeper exposure to biological systems.
Any sufficiently complex system, be it biological or man made, exhibits characteristics of difficult predictability, even to the point of unpredictable.
Anything I have watched from Open Yale has been fantastic too. I feel like they have done a great job of curation and not just creating a list of random new class recordings.
Extremely clear and satisfying lectures that covers all of basic physics. Much of it is accessible to anyone with some spare time and first year university!
Timothy Snyder: The Making of Modern Ukraine. [0] gives you invaluable understanding about much more than just Ukraine.
MIT 16.885J Aircraft Systems Engineering, Fall 2005 [1] - the aircraft they focus on is the Space Shuttle. Amazingly demystifying. Some of the actual early designers talk there.
The Aircraft Systems Engineering lectures are great, I'm listening to them now.
It should be noted that the lecturer, Aaron Cohen, contradicts everything that has made SpaceX successful. From reusability, to innovation, to cost-cutting measures, to sticking with traditional contractors. But that is only testament to the challenges that faced SpaceX, it detracts nothing from Professor Cohen's brilliance. It's too bad that he never got to see how both cargo and manned spaceflight had progressed only a decade after his 2010 passing.
I was going to post MIT 16.885J Aircraft Systems Engineering, Fall 2005, really amazing, would be nice to have something like that for modern day systems
Sorry, can't resist: you probably mean pi radians (and by convention you don't even need the word radians). Pi degrees would imply your outlook barely changed at all.
Yeah this one is so much fun. I feel like I really grew as a programmer from this course. Scheme is the perfect teaching language because each concept being taught can be demonstrated in its pure form so you really “get it”. I had been a professional developer for 10 years or so when I went through this course, and it profoundly changed how I thought about code.
By Jeremy, who is the founding researcher at fast.ai.
Three things I love about this series
1. Jeremy seems like a power user of Jupyter notebook and uses them beautifully to run the lectures. The book on fastai is also written in Jupyter notebooks.
2. The lectures are super hands on - Jeremy actually fires up a jupyter notebook and runs code which often surprises him
3. I love how he describes he deep dives into a specific Kaggle competition. Describes in great detail his own attempts at getting up the leaderboard. It's almost like watching a poker player reveal her decision process before they make a move.
Highly recommend both of these. In particular the Distributed Systems one has an amazing format (read a paper each week, the lecture goes into detail about the nuances). Also implementing raft was challenging and frustrating but incredibly fun.
Geoff Hinton's legendary Coursera course on neural nets. It came out around the same time as AlexNet winning the ImageNet competition which sparked the current deep learning revolution.
At the time it was cutting edge to the point where he introduced a previously undescribed optimization method (RMSProp) that was subsequently used in papers, citing the lecture slides as their reference! But still accessible to anyone with basic college math. Of course it doesn't have any of the new stuff like transformers or diffusion models, but I still consider it as giving a good foundation for understanding backprop and neural nets.
Unlike every other AI course at the time it didn't try to teach you about all the other types of machine learning. Neural nets only. After taking it I was able to apply neural nets at work with pretty great results. Also, it gave me one of my favorite quotes: "To deal with hyper-planes in a 14-dimensional space, visualize a 3-D space and say 'fourteen' to yourself very loudly. Everyone does it."
Somewhere on Hinton's webpage, there's a series of mp4 lectures. They introduce general neural networks, and then lead into restricted boltzman machines, which he worked on. Probably one of the best introductions to RBMs.
The video series made by 3Blue1Brown are fantastic. He crafts visual math videos using an animation engine he has developed to provide great explanations for understanding concepts more deeply. Beyond the technical, his presentation style and insight makes them very motivational to follow.
CS193p - Developing Apps for iOS, by Paul Hegarty.
It's a course taught at Stanford University, some of which they've released publicly for free. Here's the latest incarnation, which covers SwiftUI:
https://cs193p.sites.stanford.edu
Building a prototype with Dan Gelbart [0]. An engineer and inventor, he has an 18 episode playlist of every aspect of using a machine shop to build prototypes. It teaches machining. Shop use, thinking though physical creation where order of operations is paramount. Really just a great learning experience even if you never plan on doing machining.
Not exactly a lecture series, but Andrei Alexandrescu has had some fantastic keynote presentations at CppCon. I don't even program in C++ any more, but I've watched these more than once, they're entertaining, approachable, and inspiring:
It’s a podcast (or started as one) but is much like a lecture series - The History of Philosophy Without Any Gaps. It is both as brief as possible yet as thorough as needs be, and is truly gap-less. Peter Adamson does a fantastic job explaining the historical context and progression of philosophy along with the interplay between philosophy, science, politics, religion, and society. I find the episodes consistently both informative and amusing.
His geometry-centric approach to linear algebra was exactly what I needed to finally grok the subject. Topics like matrix multiplication and discriminants went from "why are they defined like this? it makes no sense?" to "of course that's how you multiply matrices because it's the only logical answer".
It's only later that I discovered Wildberger has some ~strange~ very interesting ideas regarding imaginary numbers, but these ideas don't detract one bit from his presentation of linear algebra. Highly recommended viewing for anyone who is keen on neural networks and machine learning but struggles with understanding the underlying mathematics.
It covers many different fields in a shallow, introductory way (which keeps it quite approachable to non-experts). It's following a textbook, but he of course gives his own idiosyncratic takes on things.
It's not just imaginary numbers, the ultrafinitist rabbit hole runs deep. But there's nothing inherently wrong with it, it's just a different set of axioms than everyone else uses. With those constraints you can still do meaningful things by other means (checkout his rational trigonometry stuff), at the expense of more cumbersomeness.
Washington Street Studios' pottery playlist. Taught me a ton about ceramics. Sadly the lecturer Phil Berneburg has since passed away, but it's more or less the equivalent of the theoretical side of an undergraduate degree in ceramics.
Anything by Bryan Cantrill, which arguably isn't a "lecture" in the intended sense of the word (i.e. professor, college, university, etc), but it is one wild ride of a lecture nonetheless.
An hour with Bryan will teach you more about computer history and system design than most anything else.
I particularly like the monktoberfest series, and the Joyent years.
Sw Sarvapriyananda's discourse on The Gita has been life changing for me. His approach is quite traditional but he also references many contemporary works. I started it because I wanted to learn more about consciousness. I'm halfway through it and I'm already a committed Nondualist!
I'm currently doing an MIT OCW course called 'The Film Experience'. I've not seen someone talk about and analyze a work of art like this in a long time. Supreme lectures and the course material (assigned reading, videos) is wonderful as well.
It's almost a trite recommendation because his tidbits are sampled all the time in electronic or meditation music, but they're sampled all the time because he's known for opening western minds up to eastern mysticism in a very down-to-earth approachable, comparative, compassionate, and often humorous way. Who knew that philosophy can make you laugh.
His lectures just show you a different way of looking at the world, and it's a breath of fresh air for the soul.
It starts with very basic, and cute blobs. And builds simulations around how they evolve. But as they explain the simulations, they explain how mutations might arise. It is explain how mutations can become advantageous to the point of driving predecessors extinct, or nearly extinct. And they show you how to derive math formulas for the outcome of the simulations in a very intuitive way. Also, it's entertaining as hell. I've watched the whole series at least 4 times by now. It's short, it's punchy, it's brilliant. I'd very highly recommend it.
This series teaches you so much about how a computer works from the ground up. Although I had already learned that you can build a CPU with only NAND-gates, this is what really made it click. It's also densely packed with facts and techniques (debugging, using an oscilloscope, ...). It's quite refreshing compared to other youtube content where every little fact needs a ten minute video.
Couldn't agree more. His series on networking is also fantastic. Hugely leveled-up my understanding of how computers talk to each other. It's almost Euclidean how he builds it up, with each segment applying the principles from the previous one.
He's a fantastically gifted teacher and has a very deep understanding of the material, which is just a killer combination.
I’m building that one now. I did the 6502 project first which was a long weekend project. That also gets you familiar with making ROMs without needing to build the programmer yourself. (Then again building the programmer is also educational, and you could use that skill to program the ROM for the 6502 without buying the programmer and using their suspicious looking but totally fine software that goes with it.)
I’m on the output module of the 8-bit computer, adding a register so you can store the number being output. Next is adding the bus to connect all the modules. (I end up listening to something else while making a bunch of wires, and that will take a lot of wires. I’m trying to make it look nice like Ben does.)
It got me to set up a dedicated electronics workstation and I went ahead and got myself a soldering station (more for future projects but it was useful for making a USB power cable and adding resistors to LEDs to save space) and oscilloscope (useful for seeing the glitches I’m currently having; plus it’s fun).
I’m getting into PCB design (KiCad). Started designing one for the 6502 project but I’m pausing that while I work on the 8 bit cpu project. There are definitely issues with the 8 bit project being on breadboards and/or how it’s currently hooked up such as the fact that some parts have some glitches due to poor power distribution and floating input pins that I’ll be working on. There are some good tips on /r/beneater subreddit.
I also just picked up the book he based the lectures on, to round things out. Of course, learning from Ben Eater and doing it in real life is the point where theory meets practice and you start making things in the real world.
https://www.youtube.com/@weirdboyjim James Sharman is probably worth a look for taking a home brew CPU to the next level, like his pipelined CPU which is also moved to PCBs. He also works on other things such as audio, video, etc.
There are also a ton of other system builders on YouTube making home brew Z80 and other CPU projects. Ben talks about SPI interface but I also found out how to use SPI to read/write from SD cards (John’s Basement: https://youtube.com/@JohnsBasement )
This channel is adding a cassette interface to Ben Eater’s 6502 project. I want to do that and is what actually made me decide to get an oscilloscope. https://youtube.com/@GregStrike
+1 on the eigenchris stuff. They start a little rough as he’s still learning how to present online, but improve quickly, and he has that knack for explaining things clearly that some people seem to be born with.
Second this one, I remember being enthralled in undergrad just going through these lectures. I should give it another watch through since there was a lot I didn't understand the first go around
I have always been fascinated by how better to communicate ideas. I swear 90% of the brilliant Ideas I have seen go to waste because the idea wasn't convincingly presented. It drives me insane when I know exec teams will ignore things because a presenter missed the mark a bit.
"Human Behavioral Biology" lecture serise by Robert Sapolsky at Stanford.
As a engineer with huge interest in learning how something works, understanding human brain and behavior, was a logical next step for me. The lectures are more about learning ways of analyzing the mind rather than learning any specific facts.
Not the most sexy topic but it goes to a low level and gives you a clear picture of how memory is laid out, how functions translate to instructions from C, C++, then goes on to use Scheme and Python to show further paradigms.
The presentation is clear and it simplifies in just the right places to give you the foundations.
I quite enjoyed John Searle's Philosophy of the Mind course. [1] Searle obviously has strong opinions on the subject, but he does a good job of going through the history from Descartes onward about the big problems in the philosophy of mind and how various philosophers have grappled with them, and he's enjoyable to listen to. The lectures midway through on functionalism and computational theories of the mind would probably be especially interesting to the HN audience. Towards the end he explains his own ideas about consciousness (though I found them to be less compelling than the earlier lectures in the course).
I took this course as an undergrad. It was in fact required for anyone studying CogSci.
Can you imagine being a religion major and being forced to take a class from an atheist scientist? It was like that. Searle believes that General AI is impossible from a philosophical prospective, and the final exam requires you to defend or argue against that position. But if you argue against it you get no better than a B.
Kevin Ahern's Biochemistry courses BB 350/2017 [1], BB 451/2018 [2], Problem Solving Videos [3]. Having a mechanistic/romanticism-infused worldview based mainly on Descartes' mind/body dichotomy trying to tie together Plato's idealism with Aristotle's empiricism is no longer possible after witnessing how polypeptide chains develop affinity for oxygen, in the least the worldview will be closer to La Mettrie's L'homme Machine [4] rather than Descartes' res duality.
Most people think they are good communicators because they talk all the time, but talking is not communicating. The truth is that good communication is the hardest thing you will ever do.
This course literally changed how I think, write, and speak. It was so good that I listened to it twice. I even had to restart on the second attempt because my wife got hooked on it as well so we would listen to it on long road trips and discuss.
Some key lessons (taken from the website):
* How early cultural learning and deeply learned patterns of reaction in our unconscious mind affect how you see, think, and feel about other people and enhance or undermine your ability to communicate effectively
* How your sense of self develops in everyday talk during your childhood and the ways in which your subconscious is built to sustain and defend your self-esteem, shaping how you think and speak to others for the rest of your life
* The specific styles of talking you use in most situations, including different types of control talk -- the unproductive and needlessly aggressive mode that almost always dooms a conversation to a fatal downward spiral -- and the more desirable alternative of dialogue talk
I'm enjoying the Milewski series too. For a couple months I've been plowing through some books on Category Theory. It isn't easy for me. A disproportionate number of aha moments have happened while re-re-watching one of his presentations.
A long time ago I found a free UC Berkeley class, I think it was Psych 117: Drugs and Human Behavior that was absolutely phenomenal, but I can’t seem to find it anymore.
More recently, the course was called "Drugs and the Brain". It was intended as a survey course so maybe slightly different topics than the one linked here.
Ivan Godard is a pretty good speaker, and his discussion of how the Mill CPU works is very insightful if you are at all interested in modern CPUs work.
I don't know that we'll ever see Mill CPUs in wide use (I've been focusing on RISC-V), but there are so many interesting ideas presented in this video series. Ideas that will leave you asking: "Why do we do things the way we do now?" over and over again. One of the most interesting ideas is how the Mill CPU architecture takes into account the 2D nature of silicon lithography.
Ajahn Brahm's videos on the Buddhist Society of Western Australia (BSWA) Youtube channel. From what I remember of them (I watched them mostly around 2010 time frame): his talks aren't religious, rarely touch on spirituality, and are more very logically laid out conversations and anecdotes about being happier by embracing things like unconditional love and kindness. A few months of listening to his videos really made a massive difference in how I view the world, and a big difference in my own happiness because I am better at accepting people for all their flaws and difficulties and poor actions.
A series on the Peloponnesian War from the Great Courses. Heard but not seen. I had been listening to some series on Greek history that seemed to culminate with this "civil" war. There are fascinating lessons about how democracies can fail. The lecturer (Ken Harl) is amazing and gets excited to the point he's almost shouting (not in a bad way) by the end of lectures. Some highlights include the Athenian democracy voting itself out of existence, multiple betrayals, and a cameo from Socrates.
I got a copy from my local library at the time ~ 2014.
https://www.thegreatcourses.com/courses/peloponnesian-war
He helped me understand what money really is. He explains pretty complex things that most people have a hard time understanding, in a very simple way. I got the recommandation from another similar thread here on Hacker News.
+1 to this. I came across this course in a past thread in HN and worked my way through the lectures around end-2020. Took me 3 months but I really enjoyed this series.
I've found the supplementary notes and worked exercises (sometimes introducing material) are a key part.
Herb describes the textbook as the heart/building block of the course. Unfortunately, with the textbook out of print (4ed), and later editions being reorganized, the readings chapter/section don't match up, and don't seem to cover the same content (going by the exercises), It's hard to get full coverage.
Yet, the resources at MIT and Herb himself (commenting on the youtube channel), said that any calculus text will do. I'd just like to sure of not having any gaps (or, worse, misconceptions) - that's my purpose in revisiting calculus.
Dan Boneh's "Cryptography I".
https://www.coursera.org/learn/crypto
Was one of the best basic lecture I have seen on the crypto topic.
I have enjoyed several lectures in my studies but some things I just understood after the good and interesting explanations in this course. Really amazing. Still waiting for the the Crypto 2 course.
If you understand german I recommend you math lessons by
Christian Spannagel https://www.youtube.com/@pharithmetik. Makes some less interesting topics enjoyable.
There are probably more thorough ones out there, but I found his added perspective helpful - he's constantly asking, is this useful today? Today is 30 years ago now, but still. :)
Before listening to the series, I thought I wasn't interested in Nietzsche, but afterwards it feels like he has a point that modern culture still hasn't addressed, au contraire. Especially if you look at the dropping birth rates.
Particularly about human vision and how visual information gets processed, priority and timing, etc. Some cool experiments (upside down face recognition).
He does a good job explaining the crux of a much deeper science; his intent is mainly to provide background knowledge for aspiring doctors, but his own research is full-on neuroscience. It's a good example of topological sorting, building topics up from no-knowledge. And of course any knowledge of neuro-anatomy is humbling :)
Very nicely explains different evolutions of philosophical thought that helps you appreciate human knowledge and the current cultural and philosophical status quo, because the course helps you find the common thread that runs through great thinker’s debates.
His course on the Modern Political Tradition has the same effect on political thought and its the evolution. Both are on Audible as well.
I still occasionally think about the series on Rome, and also the Rise of the Khans series. (Also, apparently, it's pronounced Jenghis - who knew?!). The series on World War I is also phenomenally interesting and really paints the picture of just how brutal and senseless that war was. The section on Verdun is particularly harrowing.
Another one that I think everyone should hear is "Logical Insanity", where Dan talks through the civilian bombing campaigns of WWII. He makes a case that the nuclear bombing of Hiroshima and Nagasaki fit into this wider pattern of bombings in a really interesting way - those two events obviously loom large in our thinking about history, but in the context of WWII they were almost... mundane. Just two more bombings of civilians in a war that was full of the same. (Dan makes the case in a much more fleshed out way, so please don't take my half-assed description as an indicator of the quality of the episode).
These have all fallen behind the paywall at this point but they are well worth the money and time.
I graduated with my CS degree back in 2016, but admittedly really disliked the curriculum at my university and have lacked some crucial knowledge.
One of the series I've picked at and skimmed at times for reference and relearning some concepts is MIT OpenCourseware's 6.006 (and other courses) taught primarily by Erik Demaine. He's much better than any instructor I had at San Jose state university and I've learned things better. Even when I watch his lectures and feel like I'm still missing some points, it's very easy to go back and review examples of his.
true brilliancy expressed in teaching and research BTW. Did he not coauthor quite a revolutionary proof recently? Cannot put my hand on it or remember what it was.
Not sure about best but MIT 9.13 The Human Brain, Spring 2019 by Nancy Kanwisher Congress to mind. It's a broad introduction to "core perceptual and cognitive abilities of the human mind and asks how they are implemented in the brain. Key themes include the representations, development, and degree of functional specificity of these components of mind and brain."
Lots of great answers here. Outside of the usual HN domain, I’ll add James Sheehan’s Stanford course on the history of the international system in the 20th Century:
I come back to it over and over because it’s fractally interesting, from discussions of nation-state grand strategy to how FDR made strategic use of a martini.
I absolutely loved Bob Brier's "The History of Ancient Egypt". It really kindled a love of the subject ever since I saw the lectures. Audible is probably the best legal way to get access to them now, but here's an amazon link https://www.amazon.com/History-Ancient-Egypt-Bob-Brier/dp/15...
>This is one of 18 videos representing lectures on digital photography, from a version of my Stanford course CS 178 that was recorded at Google in Spring 2016.
The great thing about Susskind's lectures is, imho, that he allows himself to get slightly confused by his own explanations, of course, to fully recapture himself and the audience a few moments later.
There are many great suggestions---some that I might argue are better than what I have to add (Lewin, Sapolsky, Sedgewick, Boyd)---but I have some to add that I enjoyed because they were extremely well-taught:
I absolutely with anything by Patrick Winston! I put on his lectures whenever I need to feel inspired about my job. He's so engaging and has a great way of explaining things that leave students feeling motivated and curious. Additionally, his book "Make it Clear" has been a Godsend to my academic and my personal writing.
Sean Carroll's Biggest Ideas in the Universe series [0] is a pretty cool introduction to Physics, somewhere in between math-heavy university level lectures and popular science expositions without any math.
Someone already mentioned Ben Eater's Building an 8-bit computer. Nans2Tetris [1] is a similar course but completely in software, where you start from logic gates and end up with a fully functioning OS. Checkout the cool projects students built on top. [2]
Jim Kurose's video lecture series on "Computer Networking, A top down approach". It follows the format of the book (same name). The video lectures are on youtube[1] and can be accessed from his web page[2] as well
The professor does an excellent job at explaining every detail, and the lectures end up being even fun. I've enjoyed this a lot.
I'm currently hooked up the "Pharmakologie Athlet" [1]. It's a full fledged, german language university lecture on pharmacology by Prof. Dr. rer. nat Stefan Frank. During COVID times, he decided to put his complete curriculum on Youtube.
Althou I have no medical background, I somehow manage to keep the pace with all the old biochemistry knowledge I picked up in grammar school 25 years ago. But it's a tough ride :)
This classic 10 part course, taught by Reinforcement Learning (RL) pioneer David Silver, a popular resource for anyone wanting to understand the fundamentals of RL.
I've only watched about five of the videos on it, but Keenan Crane's intro to computer graphics series is pretty great (he's a CS professor at Carnegie Mellon):
He makes excellent use of visuals and well-crafted examples to get core concepts across without getting bogged down in details that aren't well-suited to a lecture format.
How is it that no one has yet suggested Randy Pausch’s famous “Last Lecture”? (Carnegie Mellon University) It is not a series, but it’s the culmination of a life’s work by an incredible person lost too early.
Steve Brunton's youtube channel hasn't been mentioned yet, it's my favorite math lectures. Very approachable and the guy has perfected writing mirrored. No proofs though, rather he's giving a well explained overview.
It is a very deep dive into the text of the book. A weekly episode that usually gets through less than a page of the book. It has recently passed Episode 250.
Episode so far are all on Youtube or downloadable as podcasts.
Absolutely brilliant and engaging explanations of some difficult to understand topics. Especially lesson 22 on Emergence and Complexity has been an eye opener.
Introduction to Cryptography by Christof Paar: https://www.youtube.com/@introductiontocryptography4223. This is a great introductory cryptography course which is perfect to complement the great textbook from the same author.
The Historical Jesus by Bart Ehrman, on Great Courses. Bart Ehrman has written a number of books on the historical Jesus, and the birth of Christianity, but I found the course to be better than the books.
You might not like it if you are a believer in Jesus, although Bart Ehrman tries not to challenge any belief. The flip side is that you might not like it if you are a non-believer, since he spends a certain amount of time trying to massage the message so that not to offend believers. Still, I think you'd enjoy the course more as a non-believer.
It's a history course. It shows how historians can extract valuable information given little (and often time contradictory, and sometimes forged) historical data. You can take these lessons then and try to apply them everywhere. It's going to change the way you perceive history.
"Understanding the Universe: An Introduction to Astronomy" by Alex Filippenko.
If you have any interest in astronomy, cosmology, astrophysics or just want to understand the world we live in in a greater context, then watch ist.
It is worth your time, and blows every astronomy TV show out of the water.
CS6200 is awesome (currently in it myself this term). The projects alone have been an excellent exercise, mainly because I come from a web development background. The papers we are reading are very interesting. Prof. Gavrilovska does a great job explaining concepts that I found confusing in my undergrad OS course.
i always liked the "Great Ideas of Philosophy" series by Daniel Robinson, for the Teaching Company (now the Great Courses). it's available to purchase from the great courses website or from Wondrium's very good subscription lectures streaming service. Lecture sets from these two companies are generally of the highest standard.
If you would like to sample it before patronising either of those two businesses, it seems to have been uploaded on youtube.
Robert Sapolsky's
Introduction to human behavior course at Stanford is on YouTube and fascinating. He's one of the best lecturers I've ever listened to
Frederick Schuller's Lectures on Geometrical Anatomy of Theoretical Physics, https://www.youtube.com/playlist?list=PLPH7f_7ZlzxTi6kS4vCmv.... A meticulously organized series covering the math concepts needed to understand the ideas of modern physics. Not for the faint of heart, but well worth the effort.
NYU's lectures on Deep Learning by Yann LeCun and Alfredo Canziani is the single best freely available lecture on non-beginner Deep Learning. I highly recommend it [0].
Other people have linked some Feynman lectures, but they are only in written form. These ones you can actually watch (though u may need to blast the volume to max at times)
I like MasterClass lectures, it is not free but it has good courses by famous people like Neil Gaiman, David Lynch, Hans Zimmer, and many others.
https://www.masterclass.com/
I want to watch every single video here but I find it distressing that I don't have time and I am not smart enough. Perhaps if I give up Netflix and procrastinating on the internet I might be able to fit it in.
many great suggestions but i can't believe no one has mentioned the original SICP lectures yet :)! (and a thing i always enjoy in it is the transformation to the expressions of the students as more magic is revealed)
Jordan Peterson’s personality and its transformations. A lecture he taught at the University of Toronto, highly recommended for a densely packed lectures on wisdom.
I'm a bit disappointed as I didn't see some of my favorites here :D
One of them has already been mentioned, but I'll add it anyway.
- Harvard Stat 110: awesome and somewhat challenging lecture series on probability. It goes into all the probability basics, but also goes into problem solving skill very often, so the problem sets tended to be hard as I recall it. But the nice thing is that a lot of it you can find the solutions which are very well written -- and for the exams as well. Also, the lecturer Joe Blitzstein won best professor at Harvard if I'm not mistaken. https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6...
- Statistical Rethinking by Richard Malkreath: man this one will make you relearn statistics. And with a heavy bayesian flavor, which if you hadn't had the chance to learn, will bend your mind as well. You will learn to build models that can describe a lot of situations in the real world, and estimate the parameters from data. Cool stuff if you ask me. https://www.youtube.com/watch?v=BYUykHScxj8&list=PLDcUM9US4X...
- Frank Harrel's Bioistatistics for biomedical reasearch: Frank Harrel is the go to guy to understand how to use data in clinical trials and diagnostics research. His book Regression Modeling strategies is a gem that every data scientist should read. This lecture series is aimed at biomedical researches, ie. people without a strong background in theoretical statistics. In the lectures he talks about the best practices and pitfalls you'll come accross when doing and reading research, and also explain some R code to do a better job. Harrel also wrote some very important R packages i.e. Hmisc and rms. https://www.youtube.com/@bbrcourse6203/videos
- calling bullshit in the era of big data: this is a last year course so it is very laid back in the discussions. I didn't go through the whole thing. But what I watched I remember it was really nice and thought provoking.
https://www.youtube.com/watch?v=A2OtU5vlR0k&list=PLPnZfvKID1...
- Discrete Differential Geometry by Keenan Crane: ok, I didn't see the whole thing, because it was above my understanding. But the graphics and images are so eye catching I almost wanted to just sit there watching. I'm pretty sure this and his computer graphics lectures are aso engaging as hell and hidden gems of the internet.
https://www.youtube.com/watch?v=mas-PUA3OvA&list=PL9_jI1bdZm...
I enjoyed Yuval Harari's course A Brief History of Humankind when it was available on Coursera (it can still be found on youtube, although at low video quality — https://www.youtube.com/watch?v=CGhTQ4iruLc&list=PLE-kxvSEhk...). This was before Harari released his book, Sapiens, largely based on this course; and before he started fantasizing about the future.
Harari gets a lot of flack (I guess having wildly popular books and fame does that), but I found both Sapiens and Homo Deus entertaining.
And, yes, I've read some of the criticisms of his work. They seem to take issue with the tiniest claims, even go so far as labeling his work as "dangerous"[0]. "Harari’s motives remain mysterious". It's hilarious.
Just watch the first lecture and you won't be able to not watch the rest. It starts with making your own autograd engine in 100 lines of python, similar to PyTorch and then builds up to a GPT network. He's one of the best in the field, founder of OpenAI, then Director of AI at Tesla. Nothing like the scam tutorials that just copy-paste random code from the internet.