Best Machine Learning & AI courses
The 153 Machine Learning & AI courses Redditors recommend to each other on Reddit, ranked by how many people recommended each one, how strongly, in how many separate threads and over how many years (3,024 recommendations). 97 of them are free. How ranking works.
Machine Learning (Andrew Ng)
Coursera · beginner · free
Commenters call it a great introduction that avoids heavy math while still conveying real understanding of the topic, and many say it was their starting point.
Practical Deep Learning for Coders
fast.ai · beginner · free
Commenters repeatedly call it the best practical entry point into deep learning for programmers, praising its focus on building working models quickly without requiring a heavy math background.
Deep Learning Specialization (Andrew Ng)
Coursera · intermediate · paid
Commenters call it excellent and phenomenal, praise its theory-first approach that builds understanding of what happens under the hood, and say the assignments help clarify concepts.
CS229 Machine Learning
Stanford University · advanced · free
Commenters call it one of the best ML courses out there, praised for deriving algorithms from the math and for its clear, rigorous treatment compared with the lighter Coursera version.
CS231n: Convolutional Neural Networks for Visual Recognition
Stanford University · intermediate · free
Commenters repeatedly call it an excellent, hands-on introduction to deep learning and neural networks, praising the course notes, assignments, and Karpathy's teaching.
Neural Networks for Machine Learning (Geoffrey Hinton)
Coursera · advanced · free
Commenters call it an excellent, challenging introduction to neural networks taught by a pioneer, and several say it changed the course of their careers.
Machine Learning Specialization (University of Washington, Carlos Guestrin and Emily Fox)
Coursera · beginner · freemium
Commenters call it well organized with good lectures, and say it explains the math behind the algorithms in a rigorous but approachable way.
CS224N: Natural Language Processing with Deep Learning
Stanford University · advanced · free
Commenters point to it as the go-to deep-learning-focused NLP course, with one calling it a good high-level grounding and another praising its historical perspective and lectures on word vectors.
Learning From Data
Caltech · intermediate · free
Commenters call it an outstanding, rigorous introduction to the theory behind machine learning, more mathematical than Andrew Ng's Coursera class and taught with exceptional clarity.
Python for Data Science and Machine Learning
Udemy · beginner · paid
Commenters describe it as a good hands-on overview of current machine learning topics and praise Portilla's courses for covering the applied aspects well.
Reinforcement Learning (David Silver)
YouTube · intermediate · free
Commenters call it excellent and great, praise Silver as an amazing teacher whose visual explanations make the Bellman equation click, and often pair it with Sutton and Barto.
Python for Everybody
Coursera · beginner · freemium
Commenters call it a great, well-paced structured introduction for complete beginners, with a patient instructor and a free audit option.
Machine Learning A-Z: Hands-On Python & R In Data Science
Udemy · beginner · paid
Commenters call it a practical, straightforward starting point that is well taught and comes with reusable Python and R templates.
6.034 Artificial Intelligence
MIT OpenCourseWare · intermediate · free
Commenters call Patrick Winston's lectures brilliant and say the course is worth doing in full, with one praising OCW's offering as still a great resource.
Probabilistic Graphical Models
Coursera · advanced · free
Commenters call it a very good, rigorous deep dive into graphical models, with several saying it is worth the effort despite rough edges in the first run.
Data Science Specialization
Coursera · beginner · paid
Commenters recommend it as a good way to learn R alongside data science and machine learning fundamentals, though one notes it is good rather than great.
Intro to Artificial Intelligence
Udacity · beginner · free
Commenters call it an excellent, clear introduction to AI, praising Peter Norvig's teaching, though some note errors and a lack of polish.
CS188 Introduction to Artificial Intelligence
UC Berkeley · intermediate · free
Commenters call it one of the best online courses they've taken, praising instructor Dan Klein and the Pacman programming assignments.
6.00x Introduction to Computer Science and Programming Using Python
edX · beginner · free
Commenters call it a great, challenging introduction that teaches a CS foundation more than a specific language, and say it is one of the best free intro courses on edX.
Machine Learning Crash Course
Google Developers · beginner · free
One commenter calls it a good, more interactive alternative to books for getting started with machine learning, noting it leans toward TensorFlow.
CS50's Introduction to Artificial Intelligence with Python
Harvard University · beginner · free
A commenter recommends the 2020 edition and shares their own notes from the course as a companion resource.
Intro to Machine Learning
Udacity · beginner · free
One commenter calls it a really good introduction to SVMs and other basic machine learning concepts.
Deep Reinforcement Learning (CS 285)
UC Berkeley · advanced · free
Commenters call it extremely insightful and highly recommend it, and point out that the slides, lectures, and assignments are all public.
Introduction to Computational Thinking and Data Science
edX · intermediate · free
The only comment that mentions it describes it as a course the author took after MITx 6.00.1x to get better at Python, and calls it a solid class, though the link is truncated.
Introduction to Computer Science and Programming Using Python (6.00.1x)
edX · beginner · freemium
Commenters call it a well-run, high-quality introduction to programming that is difficult but worth it, and note that it is free to audit.
Reinforcement Learning (David Silver)
YouTube · beginner · free
Commenters repeatedly call it a very good, excellent introduction to RL that pairs well with Sutton and Barto, and suggest it as the starting point for beginners.
Statistical Learning
Stanford Lagunita · beginner · free
Commenters call it a light, practical, free intro that explains methods from a statistics perspective and pairs well with the ISL book.
Statistical Learning (Hastie and Tibshirani)
Stanford · beginner · free
Commenters call it a terrific, practical base in classical statistical learning that is worth more than many ML or deep learning courses for data science work and interviews.
Machine Learning
Udacity · beginner · free
Commenters call the Udacity ML and AI courses too good for the price of nothing and a practical, hands-on way to start with machine learning.
Python Course
freeCodeCamp · beginner · free
Commenters call it free, beginner friendly, and a solid fundamentals course, often recommending it over paid Udemy options.
Neural Networks: Zero to Hero
YouTube · beginner · free
Commenters call it a clear, hands-on way to understand backpropagation and transformers, with Karpathy's explanations of attention singled out as especially accessible.
Machine Learning (Andrew Ng)
Stanford University · intermediate · free
Commenters call the Stanford lectures much more meaty and mathematically deep than the Coursera class, and a strong next step after the introductory version.
Introduction to Deep Learning (6.S191)
MIT · beginner · free
Commenters describe it as a very good, gentle introduction that builds from the ground up to transformers and attention.
Intro to Programming
Udacity · beginner · free
Commenters call it their favorite starting point for beginners and say it moves quickly into real-world projects like a search engine.
Programming MOOC
University of Helsinki · beginner · free
Commenters call it an excellent, accessible, free foundation course with a built-in grading tool, many problems to solve, and a helpful Discord community.
Learn Python Programming Masterclass
Udemy · beginner · paid
Commenters call it a well-structured beginner-friendly Python course that is worth buying during Udemy's frequent discounts, and several say it pairs well with the MIT edX Python course.
3Blue1Brown Neural Networks
YouTube · beginner · free
Commenters call it an extremely brilliant, concise high-level overview of how neural networks work and recommend starting there.
TensorFlow in Practice Specialization
Coursera · beginner · freemium
Commenters call it a good way to move from theory to hands-on TensorFlow coding, with the first courses being a gentle introduction and the later ones covering the exam material for the TensorFlow Developer Certificate.
CS224d: Deep Learning for Natural Language Processing
Stanford University · advanced · free
Commenters call it a great course on NLP with deep learning, recommended as a companion to cs231n for going deeper into neural networks for language.
Practical Machine Learning
fast.ai · beginner · free
Commenters recommend it for learning the how-to of ML and getting into the nitty gritty of training neural networks, with little time spent on theory.
AI for Everyone
Coursera · beginner · free
Commenters point to it as a good starting course for people who need to understand AI in a business context without coding.
Natural Language Processing Specialization
DeepLearning.AI · intermediate
Commenters point to DeepLearning.AI's resources as very good, based on a prior course from the same provider, and suggest this NLP specialization as a follow-on.
Machine Learning (Washington University)
Coursera · beginner · free
Commenters call it a solid foundation in ML and praise the lecturer as the best they have seen.
Python course
Udacity · beginner · free
Commenters call it a very good Python course that assumes no prior programming experience and lets you work at your own pace.
Deep Learning (ud730)
Udacity · intermediate · free
Commenters recommend it as a hands-on deep learning course, with one calling it the Google deep learning class and another highly recommending it for beginners.
Hugging Face NLP Course
Hugging Face · intermediate · free
Commenters call it a very good, hands-on starting point for NLP and transformer models, and suggest it as the place to start among Hugging Face's courses.
Deep Learning (Andrew Ng)
Coursera · beginner · paid
A commenter recommends it for picking up the principles of deep learning and for exposure to Keras and TensorFlow.
The Complete Python Bootcamp (Angela Yu)
Udemy · beginner · paid
Commenters call it a well-structured, beginner-friendly Python course with lots of projects, and say Angela Yu's graphics make fundamentals easier to grasp than many alternatives.
Elements of AI
University of Helsinki · beginner · free
Commenters call it accessible and a good introduction to AI, and one recommends it to non-technical executives as a less technical alternative to Andrew Ng's Coursera courses.
Introduction to Data Science
Coursera · beginner · free
Commenters call it a practical, reasonably paced starting point that builds real working knowledge and prepares learners for more advanced courses.
Deep Learning Nanodegree
Udacity · intermediate · paid
Commenters call it much better than a university lecture course and say it has the best explanations and notebooks for building neural networks from scratch.
Practical Deep Learning for Coders Part 2
fast.ai · intermediate · free
Commenters point to it as a practical, hands-on route into deep learning that spends very little time on theory and lets learners follow videos at their own pace.
Learning From Data (Yaser Abu-Mostafa)
Caltech / edX · beginner · free
Commenters point to it as a free, accessible glimpse into machine learning taught by an excellent professor.
Neural Networks and Deep Learning
Coursera · beginner · freemium
Commenters call it a good beginner-friendly path into deep learning, with the math taught alongside the material.
6.036 Introduction to Machine Learning
MIT OpenCourseWare · intermediate · free
Commenters praise its clear, well-written notes and interactive exercises with automatic feedback, and say it is free and well put together.
TensorFlow Developer Professional Certificate
Coursera · intermediate · paid
Commenters point to it as the practical way to learn TensorFlow syntax and as preparation for the Google TensorFlow Developer certificate exam, with one saying the course covered everything needed for the exam.
CS224W: Machine Learning with Graphs
Stanford University · advanced · free
Commenters point to it as one of two good graph neural network courses, valued for its focus on ML applied to structured data.
ChatGPT Prompt Engineering for Developers
DeepLearning.AI · beginner · free
Commenters recommend it as a quick, practical entry point for building LLM-based apps, and note it is approachable even with only basic Python skills.
Full Stack Deep Learning
Full Stack Deep Learning · intermediate
One commenter says they took the course several years ago at Berkeley and highly recommends it.
Google Data Analytics Professional Certificate
Coursera · beginner · paid
Commenters point to it as a practical starting point for getting a data analyst job, noting it is affordable and self-paced.
The Analytics Edge
edX · beginner · free
Commenters call it a great MOOC and the best analytics course they've taken, praising its hands-on exercises and above-average MITx quality.
CS188.1x Artificial Intelligence
edX · intermediate · free
Commenters call it a classic and one of the best courses they have taken, and say it builds a useful intuition for how basic AI works.
Machine Learning Engineer Nanodegree
Udacity · intermediate · paid
Commenters say the Udacity platform is well structured, project-based, and gives individual assistance and project critiques, which helps build a portfolio.
IBM Data Science Professional Certificate
Coursera · beginner · paid
Commenters point to it as a practical, hands-on way into data science with Python, often recommended as a first step before Andrew Ng's machine learning course.
Machine Learning with Python
Coursera · beginner · free
Commenters point to it as a practical, hands-on way to learn ML, noting it shows real-world applications and lets learners go straight to practice.
CS234: Reinforcement Learning
Stanford University · advanced · free
One commenter lists it as step two in a recommended sequence of Stanford courses and calls the lectures free and high-quality but demanding.
Self-Driving Car Engineer Nanodegree
Udacity · intermediate · paid
Commenters call it the best hands-on course they have taken and say it lets you build real self-driving software, including a TensorFlow project.
Sequence Models
Coursera · intermediate · freemium
Commenters point to it as a clear, mathematically detailed introduction to LSTMs, GRUs, and sequence models, taught by Andrew Ng.
Introduction to Python
Udacity · beginner · free
Commenters point to it as a solid, practical starting point for absolute beginners, with one calling it excellent and another saying it covers roughly a semester of college material.
Deep Learning A-Z
Udemy · beginner · paid
Commenters describe it as intuitive and hands-on, a practical way to get implementation experience with deep learning without heavy math.
Introduction to Artificial Intelligence
MIT OCW · beginner · free
Commenters call it a great free AI course with video lectures, and one suggests it as the first place to look for a self-study AI route.
Machine Learning Specialization (Andrew Ng Deep Learning Specialization)
Coursera · beginner · freemium
Commenters call it a very famous, industry-respected starting point, with Andrew Ng's courses described as the best option for learners who don't need graduate-level math.
Google IT Automation with Python
Coursera · beginner · freemium
Commenters call it a good foundational Python course for beginners and a solid start for DevOps-type roles, and mention that the Git and GitHub module is useful.
Learning from Data
edX · intermediate · free
Commenters call it far and away the best MOOC they have taken, praising its challenging, mathematically grounded approach over library-API tutorials.
Machine Learning with Python
freeCodeCamp · beginner · free
Commenters call it a free, solid starting point for beginners, with video lessons, projects, and a certification.
Generative AI with Large Language Models
Coursera · beginner · free
Commenters call it a great foundational course on LLMs and a decent survey for newcomers, though one notes it is partly sales material for AWS.
Applied Data Science with Python Specialization
Coursera · beginner · paid
Commenters call it very good and well documented, and recommend it as a practical way into data science and ML using Python, with the first courses covering NumPy, pandas, and matplotlib.
10-701 Introduction to Machine Learning
Carnegie Mellon University · intermediate · free
Commenters call it a fantastic course, especially for its exercises, and note that its lectures and materials are freely available online.
Using Python for Research
Harvard University · beginner · free
Commenters call it an amazing, practical course for applying Python to research, and say its lessons are still useful years later.
Practical Machine Learning
Coursera · intermediate · freemium
Commenters point to it as a practical follow-on to Andrew Ng's course and the Data Science specialization, noting that it requires the prerequisite courses first.
Natural Language Processing (Stanford)
Coursera · intermediate · free
Commenters describe it as an excellent overview that serves as a good entry point into NLP papers and literature.
CS221: Artificial Intelligence: Principles and Techniques
Stanford University · intermediate · free
Commenters call it practical and kept up to date, with strong lecturers, and say it is a required companion to CS 229 for Stanford's AI track.
Reinforcement Learning Specialization
Coursera · intermediate · freemium
Commenters call it a very good set of RL courses and say it closely follows the Sutton and Barto book with quizzes and assignments, unlike pure video courses.
GANs Specialization
DeepLearning.AI · intermediate
One commenter points to it as the place to go after the basics for learning GANs, noting it covers topics through StyleGAN.
Machine Learning (Andrew Ng)
Stanford University · beginner · free
Commenters call it a solid place to start for understanding what is happening in machine learning, and one suggests the Stanford CS 229 lectures as a deeper alternative to the lighter Coursera version.
Computing in Python
edX · beginner · free
Commenters call it the best introductory class they found and an excellent starting point for absolute beginners learning Python.
Data Analyst Nanodegree
Udacity · paid
One commenter says Udacity nanodegrees are more valuable than other MOOCs because they are built with employers in mind and give structure, feedback, and a strong portfolio.
Machine Learning Nanodegree
Udacity · intermediate · paid
A commenter who completed it says it is worth doing for the structure and motivation it provides, though similar materials are available for free.
Artificial Intelligence for Robotics
Udacity · intermediate · free
Commenters call it an accessible, hands-on introduction to probabilistic methods like Kalman filters, with Thrun praised for explaining intuition clearly.
StatQuest Machine Learning
YouTube · beginner · free
Commenters call it a great place to build intuition for ML algorithms before tackling the math, and one calls its playlist a banger.
The Python Bible
Udemy · beginner · paid
Commenters call it a good starting point for absolute beginners, praising the instructor and the clear outline of the basics, though one reviewer found the advanced sections and a promised supplement disappointing.
An Introduction to Interactive Programming in Python (Part 2)
Coursera · beginner · free
Commenters call it an amazing course and a great introduction to programming and computational thinking, and one commenter who took the full sequence highly recommends it.
Machine Learning (Andrew Ng)
YouTube · beginner · free
Commenters recommend it as an accessible way to get the main ideas of machine learning, and one notes it includes the underlying math and motivations rather than flashy visuals.
CS189 Machine Learning
UC Berkeley · intermediate · free
Commenters point to it as one of the good structured courses for getting started in machine learning, alongside Andrew Ng's course.
MLOps Specialization
Coursera · intermediate · freemium
Commenters point to it as the go-to MLOps course for the ML-specific parts of becoming an ML engineer, and note it can be audited for free.
10-601 Machine Learning
Carnegie Mellon University · intermediate · free
Commenters describe it as a rigorous, hard but worthwhile introduction to ML, and one suggests it as the first course to take.
The Complete Tensorflow 2 and Keras Deep Learning Bootcamp
Udemy · beginner · paid
Commenters call it practical and beginner-friendly, saying it builds from the basics and includes challenge exercises, and one says it taught them to build neural networks from scratch.
Intro to TensorFlow for Deep Learning
Udacity · beginner · free
Commenters point to it as a free, practical way to learn TensorFlow, and one notes it goes into sequence-to-sequence learning.
CS230 Deep Learning
Stanford University · advanced · free
Commenters point to it as a rigorous, theory-heavy option, with one noting they took it through Stanford's SCPD program.
Machine Learning (Tom Mitchell)
Carnegie Mellon University · intermediate · free
Commenters say it gives a much better understanding of the algorithms than Andrew Ng's course, which they describe as good for implementation but light on insight.
Introduction to Python (University of San Diego)
edX · beginner · free
Commenters call it a solid intro to Python and a good starting point for beginners, noting the homework and small projects.
Udacity computer science courses
Udacity · beginner · freemium
Commenters like that the courses are free, split into short 1-10 minute video lessons that are easy to pause, and offer a more personal feel than long lectures.
mlcourse.ai
mlcourse.ai · beginner · free
Commenters pitch it as a more modern, Kaggle-oriented complement to Andrew Ng's course, with interesting projects.
Introduction to Computer Science and Programming Using Python
MITx · beginner · free
Commenters call it the easier, more beginner-friendly intro to programming, with challenging problem sets and good pacing, and say it sets you up to write small scripts on your own.
Machine Learning
Udemy · beginner
Commenters suggest it for beginners and for Python users, citing its projects and explanations as stronger than Andrew Ng's course.
AWS Certified Solutions Architect Associate Practice Exams (Jon Bonso)
Udemy · intermediate · paid
Commenters pair it with Stephane Marek's course and call it excellent for exam prep, recommending repeating the tests until scoring above 90%.
Introduction to Python Programming (Georgia Tech)
edX · beginner · free
Commenters recommend it as a gentler first course than CS50, noting it has many built-in exercises and no sudden jumps in difficulty, and that the individual courses can be taken free.
Deep Reinforcement Learning Nanodegree
Udacity · intermediate · paid
Commenters call it well structured and say it was the best overall RL course they tried, with active forums to help when the material gets hard.
Introduction to Computer Vision
Udacity · beginner
Commenters describe it as a great class for getting into computer vision and call it a very good course on the subject.
PyTorch Course
Udacity · intermediate · free
Commenters describe it as a decent free introduction to PyTorch and a gradual step after fast.ai.
CS 685 Advanced Natural Language Processing
University of Massachusetts Amherst · advanced · free
Commenters call it a really good research-oriented course and say it covers pretty much everything needed to understand LLMs.
Statistical Learning
Stanford Lagunita · beginner · free
Commenters call it a free, world-class companion to the textbook, and describe the book as the top intro text in the field.
Introduction to R
DataCamp · beginner · freemium
Commenters describe it as an awesome, easy-to-follow interactive way to start learning R, and note the introductory part is free to try.
Computational Thinking Using Python
edX · beginner · free
Commenters call it a highly regarded intro CS course that works well after Codecademy and is a solid starting point for non-CS people switching into computing.
Advanced Machine Learning
Coursera · advanced
Commenters call it quite good once you get used to the accent and say it takes an industry-level approach, though one commenter had not finished it.
Cryptography II
Coursera · intermediate · free
Commenters call it a strong follow-on to the first course and say Boneh's Coursera crypto material is among the best MOOCs they have taken.
Python for Data Science
DataCamp · beginner · paid
Commenters describe it as a good way to get up to speed with Python for ML and data science, and one learns by doing alongside it.
Intro to Deep Learning with PyTorch
Udacity · beginner · free
Commenters point to it as a free, practical PyTorch introduction, with one noting the built-in virtual machine avoids local setup.
CS 189/289A Introduction to Machine Learning
UC Berkeley · intermediate · free
Commenters describe it as a strong theoretical introduction to machine learning and stress working through its homeworks by hand to build understanding.
Complete Machine Learning and Data Science: Zero to Mastery
Udemy · beginner · paid
Commenters describe it as practical rather than theoretical, and one calls it the best option for hands-on ML/DS projects.
AWS Cloud Practitioner Essentials
AWS Skill Builder · beginner · free
Commenters point to it as the official starting point for learning AWS from zero and as the first certification step on the AWS path.
9.520 Statistical Learning Theory and Applications
MIT OpenCourseWare · advanced · free
One commenter calls the whole course great and points to its slides for an intuitive explanation of why projection onto principal components aids generalization.
Deep Learning with PyTorch
Udacity · intermediate · free
Commenters point to it as a free, direct way to learn PyTorch and deep learning, with one calling it an awesome free option for someone moving into PyTorch.
CS271 Introduction to Artificial Intelligence
Udacity · beginner · free
Commenters call it an excellent, clear introduction to AI taught by Thrun and Norvig, and several point to it as the natural next step after Andrew Ng's machine learning course.
Gentle Introduction to Python
MIT OpenCourseWare · beginner · free
Commenters point to it as a good starting point for absolute beginners, and one says it works well alongside Udacity's Intro to Programming because it covers classes, which Udacity skips.
CS109 Data Science
Harvard University · beginner
One commenter points to it as a current Harvard data science course whose homework used the same kind of relationship analysis as a Show HN project.
Machine Learning A-Z: Hands-On Python & R In Data Science
Udemy · beginner · paid
Commenters call it one of the best Udemy courses they've taken and praise its engaging instructors and practical, implementation-first approach that is easy to follow with minimal Python experience.
Deep Learning for Coders (Practical Deep Learning for Coders)
fast.ai · beginner · free
Commenters recommend it as the place to start, call it beginner-friendly and almost paint-by-numbers, and suggest doing projects from it before going back to the math.
Machine Learning (Yaser Abu-Mostafa, Learning From Data)
Caltech · beginner · free
Commenters point to it as a math-oriented introduction to ML that focuses on fundamentals, and one suggests it as a good complement to self-study alongside other material.
IBM Machine Learning Professional Certificate
Coursera · beginner · freemium
Commenters call it a concise starting point that gives a quick, practical grounding in ML basics and the common terminology.
Kaggle Learn
Kaggle · beginner · free
Commenters point to it as a decent, hands-on starting list for beginners who want to learn machine learning by practicing.
Advanced Machine Learning Specialization
Coursera · advanced
Commenters call it a very good deep introduction that focuses heavily on the maths and works as a follow-up to Andrew Ng's Deep Learning specialization.
Stanford Machine Learning courses
Stanford University · beginner · free
Commenters point to it as a solid starting point for learning machine learning, with one suggesting people work through its syllabus lesson by lesson and another recommending it after building up linear algebra, probability and statistics.
Python for Finance and Trading Algorithms
Udemy · intermediate · paid
Commenters call it a good option for quant interview prep and say they recommend it to anyone serious about the role, noting it was once cheap.
Recommender Systems Specialization
Coursera · intermediate
Commenters point to it as a good dedicated course on recommendation systems and note that it covers model evaluation well, which they say many algorithm-focused posts skip.
TinyML
edX · beginner · free
Commenters point to it as a free starting point for learning TensorFlow and edge ML, noting it covers exactly the constraints of bringing ML to edge devices.
TensorFlow in Practice
Coursera · beginner · freemium
Commenters recommend it as an easier, more practical follow-on to Andrew Ng's courses, and suggest it for beginners who want hands-on TensorFlow work.
CS 182 Designing, Visualizing and Understanding Deep Neural Networks
UC Berkeley · advanced
Commenters describe it as really good for advanced deep learning and point to its assignments as a way to learn implementation, alongside Stanford CS 231N and MIT 6.S191.
Deep Learning Part 2
fast.ai · advanced · free
Commenters point to it as the follow-on to fast.ai's practical introduction for those who already know the basics and want to go further into diffusion models.
Stanford online machine learning course
Stanford · beginner · free
Commenters describe it as a very good introductory online class for getting a clearer picture of machine learning after building the necessary math background.
CS188 Introduction to Artificial Intelligence
UC Berkeley · beginner · freemium
Commenters point to it as the Berkeley AI course to start with, recommending its lectures alongside the Russell and Norvig textbook and noting its MOOC-style structure.
Intro to Machine Learning
Kaggle · beginner · free
Commenters call it a quick, practical starting point that gets you practicing machine learning in Python, and suggest following it with Andrew Ng's course for more rigor.
Neural Networks (3Blue1Brown)
YouTube · beginner · free
Commenters recommend it as a strong visual introduction to neural networks before or alongside a more formal ML course.
Machine Learning (Nando de Freitas)
YouTube · intermediate · free
One commenter says they liked it a lot and suggests it as an alternative for someone struggling with deep learning material.
Data-Centric AI
MIT · intermediate
Commenters point to it as a newer, practical complement to foundational ML study, covering how to ensure good data quality for models.
Recommender Systems
Coursera · intermediate
Commenters point to it as a direct, relevant follow-up to machine learning courses for learning how recommender systems work.
Kaggle Micro-Courses
Kaggle · beginner · free
Commenters suggest them as a practical follow-up to Andrew Ng's course, paired with his Coursera course as a starting point.
Convolutional Neural Networks (Andrew Ng)
Coursera · intermediate
Commenters point to it as the specialised follow-up to Andrew Ng's ML course for learning convolutional neural networks.
PyTorch for Deep Learning
Udemy · beginner · paid
Commenters point to it as a great way to pick up PyTorch, with one saying PyTorch is easier to pick up than TensorFlow and recommending Bourke's course for it.
CS25: Transformers United
Stanford University · intermediate · free
One commenter calls the Stanford courses, including the Transformer one, a safe bet among the many university lectures available online.
An Introduction to Statistical Learning
Stanford Lagunita · beginner · free
Commenters point to it as a free, self-paced companion to the ISLR book that explains what the algorithms are doing under the hood, with R labs included.
Machine Learning (ud262)
Udacity · beginner · free
Commenters suggest it as an accessible MOOC for getting a general idea of machine learning without needing much math background first.
Applied AI Course
AppliedAICourse · intermediate
Commenters call it the best AI course they know of for balancing theory with practical application, and say it explains algorithms with in-depth maths and includes case studies.