Harvard CS50’s Artificial Intelligence with Python - Full University Course

[@0rjuela]

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

[@sriZzZzZ]

thanks

[@muhammadfaheem5213]

Written in description

[@0rjuela]

@@muhammadfaheem5213 Yes and No. I added some chapters not included there :)

[@joch1652]

I am in my 70's. Last time I get excited about programming was Lotus 123 macro in the 1980s. Here we go again.

[@veganath]

Never to old to learn as long as the subject matter wets your appetite, btw I'm in my 60's & going head long into this

[@YerkoMuñoz-q7u]

glad to read this! enjoy the journey

[@Shrimant-ub4ul]

All the best 🎉

[@SweetT3A963]

For Future Reference: Depth First Search 28:47 Breadth First Search 31:37 Uninformed Search 55:42 Informed Search 56:22 Greedy best first search 57:02 A * Search 01:07:45 Code for the maze 44:38

[@ayushplayscs]

.

[@edwardb7811]

Professor Yu is in his mid-twenties and teaches one of the most subscribed courses at Harvard. Amazing!

[@coldfire6869]

The AI branch. David Malan still teaches cs50x. Impressive nonetheless

[@seanbrendangarrette7644]

@@coldfire6869 Don’t be petty

[@MuzixMaker]

Everyone wants to get in on the groundfloor

[@sajidachaudhry1002]

Brian Yu, Senior Preceptor in Computer Science, Harvard University

[@waves42069]

thats what happens when you have passion

[@BangladeshiDuneFan]

Thank You very much Professor.

[@somthingidk-u9l]

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 .

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@morijin5568]

@@fevad1246 bro is a menace in comments. and no one is replying

[@Daniel-Six]

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.

[@Daniel-Six]

@@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.

[@hamidmirza333]

Grateful to the Harvard University for providing this course. Thank you brian yu and all of them who are behind to provide this course.

[@plinketharry7469]

dude i cannot thank you enough, what a time to be alive :)

[@Ary_N_Xic]

Hey, this comment is just to track my progress in this course! Day 0: 1:33:11 Day 1: 2:26:36 # The Minimax algo is a bit confusing rn so i have to revisit it later

[@ClassicalConquests]

Come back chi33a

[@mqtt07]

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

[@obelix_gaul]

1:07:00, Jul 30 1:52:00, Aug 2, 2:46:00, Aug 3, 3:39:00, Aug 6, 5:34:00 Aug 8, 7:18:00 Aug 9, 9:35:00 Aug 14 10:45:00 Aug 15 11:35:00 Aug 17

[@hanslijava]

Add the times matched to each section: 1:07:00, Jul 30: Introduction to AI Concepts: The document starts with an introduction to basic AI concepts, including agents, states, actions, and transition models1. 1:52:00, Aug 2: Goal Tests and Path Costs: It explains how to define goals and evaluate the cost of reaching goal states in AI problems2. 2:46:00, Aug 3: Search Algorithms: Various search algorithms like DFS and BFS are explored, along with the concept of a frontier for solution exploration3. 3:39:00, Aug 6: Heuristics and A* Search: Heuristics and the A* search algorithm are introduced to improve search efficiency and find optimal solutions4. 5:34:00, Aug 8: Game Playing and Adversarial Search: The document discusses game playing in AI, focusing on adversarial search techniques like Minimax and alpha-beta pruning5. 7:18:00, Aug 9: Knowledge Representation and Logic: It covers knowledge representation and propositional logic, including truth tables, logical connectives, and solving logic puzzles6. 9:35:00, Aug 14: Probability and Bayesian Networks: Basic probability concepts and Bayesian networks are introduced, along with methods for constructing and inferring in these networks7. 10:45:00, Aug 15: Markov Chains and HMMs: The document explains Markov chains and Hidden Markov Models (HMMs), their applications, and common tasks performed with HMMs8. 11:35:00, Aug 17: Machine Learning Techniques: It delves into machine learning, covering supervised learning, classification, neural networks, and techniques like gradient descent9. I hope this helps! Let me know if you need any more details.

[@MrSoikafy]

It's the best thing I have ever seen on KZbin. Great job, thank you for every minute of this course.

[@satvalite1854]

hey bud can u help me if this course is for me or not i know python and am quite familiar with OOP concepts idk anything about math used in ML and have built a few mini projects using gemini and langchain I have 2 questions : is this beginner friendly enough for me and what is the end goal of this course

[@hollowskull4666]

What I love about these Harvard CS50 videos is the speed they talk and explain things. It's captivating.

[@tobiassjoholm9325]

I was watching on 1.5x speed the whole video

[@boldkojak2734]

I have been attending and listening to lectures for over 50 years now. You can always speed up the sound if u like. Speed is not a measure of the content of the subject and knowledge

[@D4rkenedskies]

​@@tobiassjoholm9325I'm at 2x 😅

[@du42bz]

​@@tobiassjoholm9325 3x

[@muna6229]

Brian yu's speech is really perspicuous and crisp pronunciation

[@paulmcdevitt2038]

Wow, I have watched several courses on data science and artificial intelligence, but none of the hosts speak as well as Professor Yu. Clean, clear, no ums or ahs, making it easy to listen and follow. The flow makes more sense than the others. Really well done.

[@fevad1246]

Now did you learn anything useful till now ?

[@jeffreebellamy3844]

harvard really is awesome. its great that they just post this online for anyone to learn from, despite having high standards, they give so much information out for free. i started coding with another cs50 class about learning python, and that was great too.

[@ShadowMind312]

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!

[@ShadowMind312]

@nnbbbbb-jv8yz yes, I also purchased textbooks so I am working through the concepts.

[@UKYusei]

What job are you going for in computer science

[@ShadowMind312]

@UKYusei I started my own company; I trade Futures and I offer data science consulting (pricing analysis and trend analysis). But I'm completely focused on futures atm.

[@ShadowMind312]

@nnbbbbb-jv8yz alot of the material covered in books can also be found online. It really depends on the specific task. But certain things should be studied extensively through reading books: such as, data structures and algorithm design. You need thorough understanding of these concepts

[@anarachiteanu1088]

For someone that wants to enter the data science field, what should I learn? Do you recommend any specific books or online courses or at least some general topics that I should cover as a beginner?

[@danialhagos-v6v]

harvard university is really changing the world by giving acceses to the inovative minds all over the world

[@Chinmoy-x5g]

3:30:37 First-Order Logic 2:46:13 Model-Checking Logic Puzzles

[@scarrosi7754]

Stop reading comments , and follow the lesson

[@MaryAchieng-y1b]

😂😂

[@Hawkfeet]

Guilty 😅

[@gayathrichowdary6494]

Stop focussing on comment box👊

[@Mubahila_sz]

😮😂

[@Mubahila_sz]

Stop writing the comment 😅

[@luizabarguil5214]

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!!!!

[@djcardwellai]

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.

[@designhub360customapparel]

Wow

[@scrotumcrusher]

yeah i get it trying make your useless time spent on philosophy look somehow useful

[@Shlwxz]

Same!

[@vansf3433]

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

[@bismmaa]

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!🙏🏼

[@Zaratch]

Something I can relate to!!

[@divyanshrajput8668]

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

[@rumanaislam4758]

Really? Those years must have been hard for you.

[@sreenivas351]

@@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

[@fevad1246]

@@rumanaislam4758 Might be just exaggerating

[@juancruzsaldano8998]

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

[@TheInvestmentCircle]

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

[@JH-no8sy]

Except for those without access to a computer. There are many such people.

[@mcdonamw]

Another excuse is, finding good videos like this in a sea of billions, is like finding a needle in a million haystacks.

[@TheInvestmentCircle]

@@JH-no8sy that is true. Thank you for humbling me.

[@MrSteakMeister]

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.

[@OpenDoorHypnosisHealingTV]

This is amazing! I'm a beginner with zero coding experience and I'm understanding this with clarity. Professor Yu is stellar!

[@jaylooppworld381]

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

[@cpoxkaizer3651]

​@@jaylooppworld381Do you know somewhere to learn full course of AI / ML on internet..

[@chrystionewarren156]

Same

[@immau]

@@jaylooppworld381 this is what I was searching for. Where would you suggest I go as a beginner before I go through this course?

[@funnymemes4471]

​@@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. 😊

[@darkknight8289]

By "YouSum Live" part 3 09:00:00 Process of assigning points to clusters in k-means 09:01:10 Iterative nature of k-means clustering 09:01:24 Re-centering clusters in k-means 09:03:09 Equilibrium and completion of k-means algorithm 09:03:35 Application and significance of unsupervised learning 09:04:41 Transition to neural networks in machine learning 09:05:24 Inspiration from human brain structure for neural networks 09:06:34 Explanation of artificial neural networks and activation functions 09:12:28 Illustration of neural network structure and function 09:14:34 Training a neural network for the OR function 09:15:17 Neural network basics and applications 09:15:23 Understanding activation functions and thresholds 09:16:35 Modeling simple functions like OR and AND 09:20:43 Introduction to gradient descent in training 09:24:51 Trade-offs between gradient descent methods 09:25:18 Mini-batch gradient descent for efficiency 09:29:33 Supervised machine learning and neural networks 09:30:02 Application of neural networks in reinforcement learning 09:31:36 Training neural networks with multiple outputs 09:32:50 Introduction to neural network limitations 09:33:12 Perceptron's linear separability constraint 09:34:43 Multilayer neural network proposal 09:35:46 Hidden layers enhance function complexity 09:37:18 Backpropagation for training hidden layers 09:41:17 Overfitting risk in complex neural networks 09:42:01 Dropout technique to prevent overfitting 09:43:48 TensorFlow for neural network implementation 09:46:39 Hidden layers improve data separation 09:47:55 Impact of hidden layers on decision boundaries 09:49:06 Addressing non-linear data with hidden layers 09:49:48 Understanding neural networks and backpropagation 09:50:02 Importance of hidden layers in learning data structure 09:50:13 Utilizing backpropagation to adjust weights for accurate classification 09:50:26 Training neural networks to classify data categories effectively 09:51:40 Implementing neural networks in Python using TensorFlow 09:53:01 Balancing complexity and overfitting in neural network design 09:53:15 Testing and optimizing hyperparameters for neural network performance 09:57:43 Introduction to computer vision and its applications 10:03:50 Image convolution for feature extraction in computer vision 10:07:15 Applying kernels in image processing for feature extraction 10:07:43 Detecting edges and boundaries using specific filter kernels 10:08:06 Image filtering for edge extraction and feature detection 10:09:33 Utilizing filters to extract valuable information from images 10:11:01 Pooling technique for downsizing image inputs by sampling regions 10:11:23 Max pooling to reduce image dimensions by selecting maximum values 10:13:03 Constructing convolutional neural networks for image analysis 10:14:32 Training CNNs to learn filters for feature extraction 10:17:17 Hierarchical feature learning in CNNs for image recognition 10:24:47 Saving and reusing model in TensorFlow 10:25:33 Training neural networks on handwritten digits 10:25:44 Importance of computational power in training 10:26:20 Iterative improvement of accuracy through training 10:26:49 Learning features and weights in neural networks 10:27:09 Monitoring training progress and accuracy 10:27:56 Testing accuracy on a separate dataset 10:28:13 Applying neural networks for handwriting recognition 10:30:00 Power of neural networks in image analysis 10:32:54 Recurrent neural networks for sequence data processing 10:40:15 Recurrent neural networks for video analysis 10:46:00 Understanding natural language processing challenges 10:48:18 Syntax: Structure of language 10:49:52 Semantics: Meaning of language 10:51:56 Formal grammar: Rules for sentence generation 10:55:23 Context-free grammar: Parsing sentence structure 11:00:46 Statistical approach: Analyzing n-grams for language structure 11:01:14 Analyzing ngrams in text data 11:02:02 Identifying common bigrams and trigrams 11:02:32 Tokenization process for text analysis 11:03:00 Building a Markov chain for language prediction 11:04:23 Generating sentences based on statistical patterns 11:05:09 Introduction to text classification 11:05:51 Applying sentiment analysis to text data 11:07:40 Naive Bayes classifier for text sentiment analysis 11:13:44 Challenges and solutions in text classification 11:17:13 Word representation in neural networks 11:19:24 Representation of word meanings through vectors 11:20:05 Transition from one-hot to distributed representations 11:20:45 Deriving word meanings from surrounding context 11:21:40 Utilizing Word2Vec model for word vector generation 11:23:44 Analyzing word vector distances for similarity 11:24:24 Identifying closest words based on vector representations 11:25:12 Capturing relationships between words using vectors 11:26:37 Application of word vectors in neural networks 11:34:42 Implementing attention mechanism for sequence translation 11:38:30 Attention mechanism in machine learning 11:39:25 Challenges of parallelizing recurrent neural networks 11:40:15 Evolution from recurrent neural networks to transformers 11:40:25 Transformer architecture overview 11:42:51 Importance of positional encoding in transformers 11:43:49 Self-attention for better word representation 11:44:36 Multi-headed attention for comprehensive context 11:44:49 Deep learning repetition for deeper patterns 11:46:48 Decoder's attention to encoded input representations 11:48:39 Transformer's focus on attention for effective results 11:49:04 Advancements in natural language processing

[@sreechandra9738]

Thank You!!

[@Niteshkumar777-n5s]

Is this free

[@samferrer]

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.

[@ameen6768]

I agree, but did you finish it? If so was it worth it and are there parts you suggest to skip?

[@Neur0n97]

His teaching style is incredibly precise and evident. It's a great pleasure to watch these lectures. Well done!

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their timee

[@gurerguncan]

I can’t afford to miss this. This weekend I’ll go in depth this course. A value bomb! Thank you profesors!

[@ameen6768]

Did you finish it? If so was it worth it and are there parts you suggest to skip? Thanks!

[@fevad1246]

@@ameen6768 Lol no one learns watching these videos or atleast not to the enough level where they can apply it in actual life. These are all exaggeration

[@nephilim18]

@@fevad1246 just say you aren't made for it and move on

[@fevad1246]

@@nephilim18 And who are you?An Ai engineer?

[@libbylebyane3681]

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!

[@EricaHill-l8w]

Thanks for putting together this course in one video.. Thank you so much for all of the free courses you upload.

[@drunkmadala]

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.

[@imad1996]

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.

[@Analytix_AI]

His vocabulary is too awesome man anyone can understand what's he teaching . Cool man 😊😉

[@charmsoflove3359]

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.

[@webplethora]

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.

[@dorlock42]

Information/knowledge is one of the most valuable things and if we don't share it. We will get nowhere as a society.

[@deinisperez3838]

Cierto, que suerte lo que hablas inglés como lenguaje original, la mejores información están en inglés. Pero aquí estoy auque con subtitulos

[@fevad1246]

@@dorlock42 Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@alexplaytop]

Best course and so perfect explained, thanks Brian Yu

[@romerozarragossa]

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.

[@gaberoyalll]

Thank you for mentioning this 😊

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their timee

[@johnmo1111]

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.

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@a3gzuy]

This is amazing! Both the course and the teacher. Thank you very much for sharing this.

[@education.online_frevryone]

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!

[@Urug01315]

What I will be able to do after completing this?

[@education.online_frevryone]

@@Urug01315 IDK but I love the logic part of the course

[@superrbx]

Did u take notes or just watch

[@education.online_frevryone]

@@superrbx I mean there are already notes on the cs50 website.

[@T___Brown]

​@@superrbx Take notes 😂😂😂 are you trying to take a test or trying to learn something?

[@letsgetstarted.05]

I have an exam tomorrow in chemistry, and I can't seem to stop watching this lecture today! Man, I'm gonna be screwed!

[@FakitoMusic]

I love the way he explains everything. Thanks for the course

[@roldanduarteholguin7102]

Export the Q*, Chat GPT, Revit, Plant 3D, Civil 3D, Inventor, ENGI file of the Building or Refinery to Excel, prepare Budget 1 and export it to COBRA. Prepare Budget 2 and export it to Microsoft Project. Solve the problems of Overallocated Resources, Planning Problems, prepare the Budget 3 with which the construction of the Building or the Refinery is going to be quoted.

[@mohanaryal4639]

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.

[@TrevorR_333]

Just finished the course, now let's see how it compares to my graduate course that I start next week. Thank you so much for this.

[@avocadoamongos5]

Thank you so much for all of the free courses you upload

[@beegotto]

This guy is a great teacher, I would take any class he offers. Thank you for sharing this. This is very encouraging!

[@haipingwang7075]

This is a great course for me to though ML after my 12week online course from MIT!

[@rameshragavan1762]

Thanks!

[@beepbeepgamer1305]

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.

[@preythapp]

Let's go. Commented so that I can see your progress. 👨‍🎓

[@Pclub4ever]

@@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.

[@preythapp]

@@Pclub4ever nooo. Please don't say that 😬. I hope he stands by his plan.

[@backgroundnoise__]

cmon bro, only one day missed don't give up, good luck

[@beepbeepgamer1305]

@@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 KZbin :/

[@lahearle]

Want to clarify for those hard of understanding on the arc matrixes and sudoku, that (linear programming) Action1 has cost1 because of X1 Math, A2C2X2, etc = A contains: B contains: [ X [ X Y Y Z ] Z ] These are two separate matrices so duplicates are okay, if they are both nested into a single matrix than they cannot contain the same so if A = XYZ, and B = ABC but I want to switch A = X with B = C I have to backtrack to get than switched so that anything afterword can have it's proper Alignment (If I am on D I have to go all the way back to B and switch) This counts as An Action1/Cost1/X1 move for example, if your AI was trying to cycle through all the matrices and properly align them. The reason that you don't want duplicates in a single matrix is the same as in geometry that a straight line is the shortest path between towns, If I start From: X then Y then Z it is in sequence, If I reverse it, it's still in sequence. But if I change X then Z Then Y, (Z) is in the center meaning I must go from X to Y to Z (sequence), then back to Y, because I had to pass through Y to get to Z in the middle anyway. (like I need to go to Walmart, Mcdonalds, and Kohls but I go to kohls first so I have to drive all the way back to Mcdonalds etc etc) Everything else was pretty good for such a long video very precise but that part got a little repeat confusing I think. BTW, since this is all costly one should use both breadth and depth - first searches with A* to get to the goal faster from both directions, so that things like this matrix can be solved with inference (if A = XYZ THEN C must = ABC) faster, in order to produce sequential inference actions faster. It's If, Then logic is what inference means: If A, then B.

[@McDonaldIbekwe]

Thanks for putting together this course in one video.

[@rajcherand]

Thanks

[@georgejetson9801]

Thank you! At age 62, loving every video you release!

[@fredrickmweu]

why are you learning tech at 62 bro

[@msmysticstorytime]

why are you learning tech at all@@fredrickmweu

[@georgejetson9801]

@@fredrickmweu I started at age 18 and it's been my life's work so no need to stop now. Maybe at 100...maybe.

[@sigma_z]

​@@georgejetson9801I'm 104 years old and still learning everyday. 🙏🏼

[@the_excelprofessor]

@@fredrickmweuhe knows more than you lmao 🤡

[@jdlopez131]

min 2:10:36 if Harry didn't visit Hagrid does not imply that it rained. The sentence says that if it doesn't rain, then Harry visited Hagrid. The statement does not suggest that there is a codependancy between not visiting Hagrid and raining. There is not even a dependancy between raining, and doing anything. We know that Harry visited Dumbledore and didn't visit Hagrid. That is a fact. But, we can't conclude that it rained today.

[@hunterwu94]

- [00:00](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🤖 The course explores foundational concepts and algorithms of modern artificial intelligence, covering topics like graph search algorithms, optimization, reinforcement learning, and more. - [03:16](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🛣️ AI aims to solve problems by searching for solutions using various actions and transitions between states in a state space. - [07:00](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🧩 States represent configurations, actions are choices, and transition models define the outcome of actions. Goal tests determine if a state is the goal, while path costs measure the cost of actions. - [11:31](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🔄 A search problem involves exploring states using a frontier, a data structure containing states to be explored next. A loop-based search algorithm iteratively explores the frontier, considering possible solutions. - [19:35](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🕵‍♂ The search algorithm involves removing nodes from the frontier, analyzing their state, parent, action, and path cost to navigate the search space and find solutions. - [33:09](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🔄 Depth First Search (DFS): Explores one path until a dead end is reached, then backtracks and tries another path. Can lead to non-optimal solutions. - [36:24](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 🌐 Breadth First Search (BFS): Explores all possible paths at a given depth level before going deeper. Guarantees optimal solutions but may require more memory. - [38:51](kzbin.info/www/bejne/a3_Kf5yZdrOsp68) 💻 Code Implementation: The video demonstrates code implementation of DFS and BFS for solving mazes, highlighting their exploration strategies and memory usage.

[@masterreacts2.0]

Great

[@KomalMYM]

39:00 code to solve maze problem

[@PrimeFit987]

16:08 search problem summarize 17:30 Node 21:30 Approach 26:30 Revised Approach

[@iseeflowers]

I am very grateful for the excellent free courses at Harvard. ❤

[@paryanatahiri3433]

I am 17mins into this video it’s wonderful. But yet all the best for those without an AI background

[@asit_dixit]

11:44 It is like useReducer in ReactJS, you pas state and and dispatch action

[@mooseydev]

Currently pursuing an MSc in AI, and this video was a great introduction to get a bigger picture. Thank you.

[@belakhdaryoucef2668]

What's next for you ?

[@marchlopez9934]

- 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.

[@StfuSiriusly]

are you a bot?

[@designhub360customapparel]

Thank you

[@user-eb2od4df3l]

Are there any prerequisites of statistics, or ML?

[@tjanos88]

Timestamps for myself to know where to continue tomorrow: 2024.07.23: 04:00:00 2024.07.24: 04:30:00 2024.07.25: 06:41:22 2024.07.29: 07:18:52

[@veganath]

Good idea

[@beechooliang582]

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.

[@ameen6768]

I agree with you, btw did you finish it? If so was it worth it and are there parts you suggest to skip?

[@borisljevar3126]

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

[@raghureddy1746]

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!!

[@lahearle]

Also wanted to say that probability is not calculated in A^^2/[A^^2 + B^^2] but is instead calculated without powers as either 1 with ratios or done Just as A/[A + B] with their associative numerical values, but there is a lot of ways to calculate probability. The reason people put a ^^2 on to it is to mathematically express it has a Min/Max values that varies between themselves and the square is supposed to be the maximum value. Other people will use 1/2 * A^^2 for example which is also pretty irrelevant. Because you are actually just getting the ratio value of 1/[2+5] = 7 and getting the reciprocal which is the same as 1/2 = 0.5 which is the ratio of 1 to 2.

[@MhasAnId]

Prof. Brian Yu, he's got a knack for making even the most complex topics seem like a walk in the park.

[@lilmermaid5239]

Next year I will study AI engineering in college, so I’m educating myself on it and it’s 😮 Wish me luck guys haha

[@abdulrazaqAS]

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.

[@ganagallajoshitha]

Have you written any notes?

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@sigmaboy9431]

@@fevad1246 did you tried it , and make sure to tell that you did learn or not

[@fevad1246]

@sigmaboy9431 do you even realize the point of the reply ??💀

[@sigmaboy9431]

@@fevad1246 I see so you just went to some random videos and posted this , considering you didn't take it

[@bryanwplee9332]

Love the BFS concept

[@nemo6127]

As a student in Aisa, I sincerely appreciate that one of the world's best universities can provide its wonderful courses for free. 回覆

[@mohakgarg161]

10 millions subscribers congratulations...❤

[@Serj1c]

Amazing content, thank you CS50 Team. You are on top of the world

[@yeachanchoi9288]

Getting to know the search problem is actually very helpful to educators.

[@Okwemba3847]

I'll leave this comment so that whenever someone would like it I'll be reminded of my day one of learning CS

[@is-smct26]

how are you doing so far?

[@diogodias_]

thanks for disponibility this course, i really apreciate the initiative. kisses from brazil

[@sigma_z]

I'm 104 years old and I'm loving this. Thank you 🙏🏼

[@Abdullah-fn1kz]

If you 104 years old then you should love oldness intelligence not Artificial Intelligence.

[@rectangler]

im 420 years old

[@mr_saam]

I am 2023 years old😊

[@sitofak]

@@mr_saam Ok, Jesus

[@sigma_z]

@@Abdullah-fn1kz I'm not old, just experienced 😅

[@paulshortridge870]

I wish I could give so much more than just the one thumbs up for this course, it was incredible. Thank you so much

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@Leetauren]

Thank you for sharing this with the world.

[@hernanduquelsky3007]

I use language translator, it is incredible the first comments I read, about the content of the course nothing, they praise the teacher in other areas.

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@mmamh123]

Brian Yu is best, i wish i had half of his talents.

[@imad1996]

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.

[@olegmakarov7877]

The guy seems cooking a good AI vinaigrette

[@mcdonamw]

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.

[@boldkojak2734]

Thank you, i thought i am the crazy old computer guy here.

[@KitsonYeung]

For the Harry Potter Logic Puzzle, I think it might not be clear mentioning what the check_all() function is returning. And I believe it is checking whether the model knowledge and the query entailment got violated

[@ericklasco]

A very informative course, i learnt a lot of new techniques and information thank you.

[@jewkeynoh]

Lupet nito! Ang linaw pa magsalita. Thank you!

[@amono770]

The way Bryan explained a* search is so much better than the other videos i have watched!

[@bradleylarkin5379]

Im just gonna casually put that i learned from Harvard on my resume...❤😊

[@marvellousodili5941]

This man is the Hero

[@cll2598]

Brian is the best lecturer I've ever seen across all my years studying across 4 universities

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their timee

[@cll2598]

⁠@@fevad1246 If you find it to be a waste of your time that’s your opinion dude, and it’s probably a totally valid opinion from your own standpoint 😂. We just all have better things to do than try to make a case to a complete random stranger whether you are wrong or right 😂

[@fevad1246]

@@cll2598 sure... whatever makes you feel better i guess ..,

[@nadirnoorzai7753]

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!

[@wooshbait36]

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.

[@urdujhalak]

Very useful and informative. The course provides in-depth knowledge. I learned a lot. I am grateful for providing this great course.

[@FutureLOKJHI]

This the best delivery I have seen in a longtime

[@fevad1246]

Exaggerations lol. I have yet to meet someone or atleast get a reply in comments from people who are claiming that courses are good,useful etc . They all go silent because they know they learnt nothing and wasted hours of their time

[@piyush_gupta_24]

Any prerequisites for this course especially should we know python before taking this course?

[@raidensh0gun]

Yes it would be helpful if you're familiar with Python and some basic data structures of the language like lists, tuples and dictionaries. It might also be helpful (although not necessary) to know a bit of discrete mathematics and some algorithmic concepts like recursion etc.

[@ArnavPatel-nq2nx]

@@raidensh0gun you definitely need to know recursion and OOP. Also data structures like queues and stacks. I'm only on the first week and all this has popped up with the first two projects, I imagine it would only be getting more complicated as the course goes on. According to harvard, you should know the equivalent of the cs50 intro to programming course, which imo is equivalent to any intro to cs college level course

[@freecodecamp]

You should first be familiar with the concepts from the first CS50 course: kzbin.info/www/bejne/bp6keoeZg9lqZ5I

[@jonsolo4489]

I couldn't even imagine watching this without solid fundamentals.