Harvard CS50’s Artificial Intelligence with Python - Full University Course
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- Опубліковано 28 тра 2024
- This course from Harvard University explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like large language models, game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs.
This course has been updated for 2023 to include an in-depth section on large language models.
✏️ Course developed by Brian Yu for Harvard University. Learn more about Brian: brianyu.me/
🔗 Course resources: cs50.harvard.edu/ai/2020/
⭐️ Course Contents ⭐️
⌨️ (00:00:00) Introuction
⌨️ (00:02:26) Search
⌨️ (01:51:55) Knowledge
⌨️ (03:39:39) Uncertainty
⌨️ (05:34:08) Optimization
⌨️ (07:18:52) Learning
⌨️ (09:04:41) Neural Networks
⌨️ (10:46:00) Language
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Professor Yu is in his mid-twenties and teaches one of the most subscribed courses at Harvard. Amazing!
The AI branch. David Malan still teaches cs50x. Impressive nonetheless
@@coldfire6869 Don’t be petty
Everyone wants to get in on the groundfloor
Brian Yu, Senior Preceptor in Computer Science, Harvard University
thats what happens when you have passion
Stop reading comments , and follow the lesson
😂😂
Guilty 😅
Stop focussing on comment box👊
😮😂
Stop writing the comment 😅
Listing some subchapters for future reference
01:07:41 - A* Algorithm - "heuristc search" for a singleagent
01:14:27 Adversarial Search (Tic-Tac-Toe)
01:39:07 Optimization - Alpha-Beta Prunning
01:46:53 Chess -Depth Limited Minimax
02:14:05 Inference Algoritms -Model Checking
02:32:42 Knowledge Ingeneering - Clue
02:43:04 Logic Puzzles - Harry Potter
02:56:16 Inference Rules
03:22:26 Inference by Resolution
03:39:39 Uncertainty - Probability theory
03:49:16 Conditional Probability
04:05:58 Bayes Rule
04:13:40 Joint Probability
thanks
Written in description
@@muhammadfaheem5213 Yes and No. I added some chapters not included there :)
When i did my Masters in mathematics, only one of the professors at my school had solid understanding of these topics. I learned as much as i could, but he was overwhelmed with students. I am grateful for these videos!
Would you like to taught this topic?
@nnbbbbb-jv8yz yes, I also purchased textbooks so I am working through the concepts.
I think you are experienced person. My question is ( is it good to learn code from online or through real physical mentor.) I have this doubt.
@@ShadowMind312 One my senior says books are non sense. He says to me go through UA-cam or other online source. But you are learning from books. Is there any reason to learn from books.
What job are you going for in computer science
What I love about these Harvard CS50 videos is the speed they talk and explain things. It's captivating.
I was watching on 1.5x speed the whole video
Grateful to the Harvard University for providing this course. Thank you brian yu and all of them who are behind to provide this course.
Brian is incredibly organized and polished. If I had professors this good back when I was in school for CS it would have been a vastly more productive experience.
@@unebonnevie I do... but forty years have come and gone since I started my journey with computer science, and the awareness of the computational nature of reality has changed my outlook considerably. It is both more and less interesting to me now.
It's the best thing I have ever seen on UA-cam. Great job, thank you for every minute of this course.
dude i cannot thank you enough, what a time to be alive :)
This is amazing! Both the course and the teacher. Thank you very much for sharing this.
Thank you so much. I don't recall ever enjoying a lecture series as much as this. Great work! I hope to see a follow up in a few years.
Thanks for putting together this course in one video.. Thank you so much for all of the free courses you upload.
I find it fascinating how people are shocked when I tell them that I majored in philosophy and work in AI. Usually, they respond with, "Wow, completely unrelated fields." Little do they know that propositional logic is at the core of both philosophy and AI.
Wow
There are many unique aspects of those videos, but what is really nice is the depth of explaining such concepts. Even in a university, they usually cannot go that deep mostly due to time constraints.
Thank you so much! The only platform who made me take interest in programming after spending 3 years in my 4 year Bachelors degree of CS. CAN'T THANK YOU ENOUGH!🙏🏼
Something I can relate to!!
Please guide me brother.. I'm currently in my semester 3 (2nd year)
I'm done with python programming all the basics and other concepts.
Getting started with javascript
Really? Those years must have been hard for you.
@@divyanshrajput8668 complete paid certification(which has exams) bro it would really help u in resume as well as showing that you have a knowledge in that field during job search to recruiters
This is teaching at its finest. Thank you, Harvard, for your generosity. I am 49 and glad to be living in a time where such precious knowledge is provided for free. It's amazing how one can gain knowledge in abundance, free of charge.
Information/knowledge is one of the most valuable things and if we don't share it. We will get nowhere as a society.
Cierto, que suerte lo que hablas inglés como lenguaje original, la mejores información están en inglés. Pero aquí estoy auque con subtitulos
This is the video that actually gets to the nitty gritty details as to how an AI actually works rather than just explaining its concepts and its history or whatever, really a gem in a coal mine if you ask me .
This is amazing! I'm a beginner with zero coding experience and I'm understanding this with clarity. Professor Yu is stellar!
how can someone with zero coding experience try to learn this?, am really impressed. i mean the concepts are easy to understand but implementing it requires programming knowledges, and not basic programing knowledges in some cases you will need to know not only the language but also third party packages, so im very impressed
@@jaylooppworld381Do you know somewhere to learn full course of AI / ML on internet..
Same
@@jaylooppworld381 this is what I was searching for. Where would you suggest I go as a beginner before I go through this course?
@@jaylooppworld381 yeah but I guess actually it is possible. I don't have any knowledge of coding. But after getting a general view I could understand how to learn the language and what all concepts I have to stress on. 😊
- This course from Harvard University explores the concepts and algorithms at the foundation of modern artificial intelligence.
- The course covers topics such as Graph Search algorithms, classification, optimization, reinforcement learning, and machine learning.
- The course is taught by Brian Yu as part of the CS50 program.
- The course starts with an introduction to how AI can search for solutions to problems, such as playing a game or finding directions.
- The course explores how AI can represent and use information, including uncertain information.
- The course covers optimization problems and how AI can learn from data and experiences.
- The course includes an exploration of neural networks, a popular tool in modern machine learning.
- The course also covers natural language processing, where AI learns to understand and interpret human language.
are you a bot?
Thank you
Are there any prerequisites of statistics, or ML?
I love the way he explains everything. Thanks for the course
Thank you so much for all of the free courses you upload
I can’t afford to miss this. This weekend I’ll go in depth this course. A value bomb! Thank you profesors!
Did you finish it? If so was it worth it and are there parts you suggest to skip? Thanks!
Thanks for putting together this course in one video.
Almost two hours in and it's so good; I understand the concepts really well. Thank you, Mr. Brian. I am really enjoying the course!
What I will be able to do after completing this?
@@Urug01315 IDK but I love the logic part of the course
Did u take notes or just watch
@@superrbx I mean there are already notes on the cs50 website.
@@superrbx Take notes 😂😂😂 are you trying to take a test or trying to learn something?
Had Brian as a TA a few years ago, he’s an amazing guy. Malan is also the best professor I’ve ever had. Amazing to get this stuff for free nowadays! No excuses for anyone
Except for those without access to a computer. There are many such people.
Another excuse is, finding good videos like this in a sea of billions, is like finding a needle in a million haystacks.
@@JH-no8sy that is true. Thank you for humbling me.
This was clear, concise and conclusive course, with a professor that not only knows the topic very well, but does have a way of helping us build the knowledge as a master! Thanks, Brian Yu!!!!
After watching a couple of thousand presentations on youtube, this is hands down number one.. Number one in clarity, fluidity, timing, content and expression. Thank you Mr. Wu, hat is off.
Thank you for mentioning this 😊
So happy to be able to revise this stuff from university thanks so much!
Prof. Brian Yu, Just *amazing*!!! I am at the tail end of my career and viewing this just out of curiosity and cannot stop watching this video! You just have a talent for communicating these concepts! Just amazing, and a very big Thank You!!
I am so glad I found this, am doing an AI Engineering Course with another institute, you've just made it so much easier to understand.
thanks for disponibility this course, i really apreciate the initiative. kisses from brazil
A very much thank you sir for supporting me in this journey. I will look forward to learn more and more.. Thank you
Best course and so perfect explained, thanks Brian Yu
notes: frontier, action function, transition function, depth-first-search, breadht-first-search, greedy-best-first-search (with heuristic closest to goal function), manhattan-distance, A*search=>optimal solution, admissible heuristic never overestimates the true cost, classical search vs adversarial search, minimax
Amazing content, thank you CS50 Team. You are on top of the world
Love the BFS concept
This is unbelievable. Much appreciated.🛐🛐🛐
The way Bryan explained a* search is so much better than the other videos i have watched!
Professor Yu is amazing at imparting knowledge to beginners.
Very useful and informative. The course provides in-depth knowledge. I learned a lot. I am grateful for providing this great course.
Learned a lot from this video. Two thumbs up. For the specific example he gave, the number tile, I think "reverse engineering" approach, couples with the AI process he described, will solve the problem more efficiently. That means I start with the end sequence = numbers in ascending order left to right, top to bottom. Then I map out all possible paths to "chaos" state = all tile arrangements that are not the end sequence. I can determine all possible chaos states = 16! = 2.092279e+13 assuming the hole is also a tile. The possible paths should be much less than 16! because each move along the way to a most "severe" chaos state is a chaos state itself. The map will look like a family tree, starting with the end sequence, and the last progeny of each branch is the most "severe" chaos. When user enters a chaos state, the algo finds where it is on the family tree, follow the reverse path/moves back up to the end sequence. The reverse-engineering approach will only work well when the goal/end is well defined.
I agree with you, btw did you finish it? If so was it worth it and are there parts you suggest to skip?
This is a real piece of art that I have witnessed. Kudos to the professor always impress me with the depth and clarity of his knowledge.
Thanks for this wonderful content. Professor Brian has done an incredibly well done job. I learned much and Thank all the persons involved in producing these lectures. Much grateful to Harvard University for sharing this. Professor Brian, you are a GREAT Communicator!
Thank you for your kind words! We're delighted to hear that you enjoyed the content and found Professor Brian's lectures informative. Your appreciation means a lot to us and to everyone involved in producing these lectures.
This the best delivery I have seen in a longtime
Terrific course. Watched this as part of my sabbatical. I'm an experimentalist (genomics/genetics) and this helps bridge the gap with computational approaches to make sense of large data sets and make functional inferences.
Thank you for imparting this information onto us. ❤❤❤
I wish I could give so much more than just the one thumbs up for this course, it was incredible. Thank you so much
A superb explanation of these concepts, and such a gifted educator and communicator.
Awesome content. Thank you Brain!!
Lupet nito! Ang linaw pa magsalita. Thank you!
Brian yu's speech is really perspicuous and crisp pronunciation
harvard university is really changing the world by giving acceses to the inovative minds all over the world
Thank you! At age 62, loving every video you release!
why are you learning tech at 62 bro
why are you learning tech at all@@fredrickmweu
@@fredrickmweu I started at age 18 and it's been my life's work so no need to stop now. Maybe at 100...maybe.
@@georgejetson9801I'm 104 years old and still learning everyday. 🙏🏼
@@fredrickmweuhe knows more than you lmao 🤡
This is a must watch video for every computer science student!
I am very grateful for the excellent free courses at Harvard. ❤
Wow...this prof really explain his stuff so well!
I am surprised by the complexity of the study it requires, just to develop the AI that plays these games. Kudos to the professor who is just excellent at this concept in the simply digestible form.
Brian is the best lecturer I've ever seen across all my years studying across 4 universities
Alhamdulillah, just finished it for the first round. I unintentionally stopped jotting at 'Inference Algorithms'. Going back for round 2 to understand more and continue jotting. You need notes to understand better bcoz you've to be going back and forth. Love it. Good job Sir Brian.
Have you written any notes?
This is a lot of information. I love it. Thanks for sharing
Thank you for sharing this with the world.
SO AMAZING I WILL BE WATCHING ALL OF THIS ON REPEAT FOR DAYS AND THEN IM MAKING MY LITTLE MODEL FOR MY IDEAS
This is the best lecture trailer in computer science I have ever seen.
Observe that he started naturally from states and agents(state machines) to gradually reach AI and ML.
I agree, but did you finish it? If so was it worth it and are there parts you suggest to skip?
Que contéudo maravilhoso, era tudo que eu precisava, grata
Olá Valmira! Vc domina o ingles?conseguiu acompanhar de boa ou precisou de legendas em português?
Clear Concise and complete!
Learnt a lot will go for Deep learning from here along with web development with python as it will help to deploy model.... good work!
Prof. Brian Yu, he's got a knack for making even the most complex topics seem like a walk in the park.
Çok teşekkürler Sinan hocam. Emeklerinize sağlık.
This course is amazing. It was my first encounter with an AI lecture, and I enjoyed it. I really enjoyed the Professor's teaching method, when he introduces new concepts, he starts with the easy to understand components and increases the complexities of the contents gradually. Each segment is accompanied with numerous real-life examples that make understanding the concept easier. Keep up the good work.
This is a great course for me to though ML after my 12week online course from MIT!
I have an exam tomorrow in chemistry, and I can't seem to stop watching this lecture today! Man, I'm gonna be screwed!
I love your channel and I wish your courses help me up in developing my career, thanks a lot
Great course, excellent presenter. I highly recommend this course.
Getting to know the search problem is actually very helpful to educators.
A very informative course, i learnt a lot of new techniques and information thank you.
Section “knowledge”, “uncertainty”, and “optimization” are so interesting. Even though you don’t directly use them much in an industrial setting, they’re still beneficial to problem solving. Nevertheless, they’re always skipped in most MOOCs.
Thank you very much sir for sharing this knowledge ❤🎉
Wonderful production!!
I cant believe it! you are the best !!!
Huge respect, love you ❤
Thank You very much Professor.
GOAT. Im from Argentina, so im not speak emglish naturally, and in every spanish video that i watched, about neural networks aididnt understand it as well as i did it here. thank u
Great course, just deep enough so to be not superficial. 😊
Most of the introductory topics of this AI course remind one of the statistical methods we used in my second year, called Hypothesis Testing, basically making calculations to make a conclusion / infererences about a fact. Still bunge watching, halfway there, thanks for sharing!
I'm 104 years old and I'm loving this. Thank you 🙏🏼
If you 104 years old then you should love oldness intelligence not Artificial Intelligence.
im 420 years old
I am 2023 years old😊
@@sigma_rool369 Ok, Jesus
@@Abdullah-fn1kz I'm not old, just experienced 😅
thank you professor Yu👍👍👍👍
9:14:08 Isn't it better to work with bias of -0.5 in case of the OR unction
9:16:51 and bias of -1.5 in case of the AND unction
Lectures with clear pronunciation are very easy to listen to and understand
This is amazing! Thank you
Absolutely amazing!!!
I really thank you guys for the content hope all the best to you and the team, people who put so much effort into these course.
I love this, haven't been able to fall asleep that easily in ages.
Wow amazing. Thank you so much
The reason why Python is the most popular with AI developers is that it's the easiest or versatile programming language among all the current known programming languages. Additionally, it has such a large library. If you have got fundamental concepts of CS shared across all programming languages, it will take from only 1 days to a few days to master Python's syntax
I am planning to complete this course within a week, I'll update each time I complete for each day with the time stamp:
Day 1: I just finished Search functions fully 1:51:56
Day 2: knowledge completed (I forgot to edit the comment because I actually went to Harvard website and registered for the course and studied there)
Day 3: half way through probability
Day 4: I'm done with probability and now i'll continue back in few days
Day n: Idk what day is this but It's been more than a month I think so, but finally completed the course and now I need to start making projects.
Let's go. Commented so that I can see your progress. 👨🎓
@@preythapp He won't stick to it. People who talk about their plans rarely do it because talking about it already gives them their dopamine hit.
@@Pclub4ever nooo. Please don't say that 😬. I hope he stands by his plan.
cmon bro, only one day missed don't give up, good luck
@@Pclub4ever why are you being like this? I legit went to their website and paid for a certification and studied through their website, I forgot to update it on UA-cam :/
thx Yu and Havardforthis free course
11:44 It is like useReducer in ReactJS, you pas state and and dispatch action
Professor Yu is stellar!
This brought good memories of a course I took in 1989 while doing my computer science degree. We did the same algorithm and many similar ones. For the first one, the maze, we used a recursive algorithm or loops, traversing graphs and trees. I did not know we were doing AI at that time :) In fact, this is not AI, but without the AI attached to the name, people may not watch the video.😁
This video is fantastic as it illustrates the power of optimizing algorithms to improve performance. The time complexity of such an algorithm as the maze is exponential.
The guy seems cooking a good AI vinaigrette
I'm only an hour into the lesson, but I'm clueless as to how this could be related to AI in anyway. This just seems like standard coding problems. I hope it clicks at some point.
Excelente explicação!