Machine Learning Courses and Certifications

Machine Learning with Graphs - Fall 2019

Comprehensive exploration of machine learning with graphs, covering network properties, community structures, graph neural networks, and their applications in various domains.

• YouTube
• 1 day 4 hours
• Self-Paced
• Free Video

Stanford CS229 - Machine Learning Full Course Taught by Andrew Ng - Autumn 2018

Comprehensive machine learning series covering fundamental concepts to advanced topics, taught by Andrew Ng. Includes algorithms, neural networks, and reinforcement learning.

• YouTube
• 1 day 3 hours
• Self-Paced
• Free Online Course

Career Certificate

Data Analyst

63 ratings

Master data analysis: clean messy data, uncover insights, make predictions with machine learning, and effectively communicate findings using Python, NumPy, pandas, Matplotlib, and Seaborn.

• Udacity
• 43 hours
• Self-Paced
• Paid Course

University of Helsinki;  MinnaLearn

Elements of AI

962 ratings

The elements of AI is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required.

• Independent
• 6 weeks, 5-10 hours a week
• Self-Paced
• Free Certificate

• Best of All Time

Neural Networks and Deep Learning

16 ratings

Explore neural networks and deep learning fundamentals, from building and training models to applying them in real-world scenarios. Gain practical skills for AI development and machine learning applications.

• Coursera
• 1 day 35 minutes
• Self-Paced
• Paid Course

Alexander Amini;  MIT

Visualization for Machine Learning - Google Brain

1 rating

Explore data visualization techniques for machine learning, including high-dimensional data, multilingual systems, and language models, with insights on biases and user intent.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Steve Brunton

Physics Informed Machine Learning: High-Level Overview of AI and ML in Science and Engineering

1 rating

Explore how to integrate physics into machine learning, enhancing model accuracy and efficiency in engineering applications. Learn to leverage prior physical knowledge across all stages of the ML process.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

Valerio Velardo - The Sound of AI

AI, Machine Learning and Deep Learning

1 rating

Explore AI, machine learning, and deep learning concepts, including supervised, unsupervised, and reinforcement learning paradigms. Learn when to use traditional ML or deep neural networks for audio applications.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

CS50's Introduction to Artificial Intelligence with Python

38 ratings

Learn to use machine learning in Python in this introductory course on artificial intelligence.

• edX
• 7 weeks, 10-30 hours/week
• Self-Paced
• Free Online Course (Audit)

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

115 ratings

Explore AI foundations through hands-on Python projects. Cover graph search, classification, optimization, reinforcement learning, and more. Gain practical skills in implementing AI algorithms and understanding their applications.

• freeCodeCamp
• 12 hours
• Self-Paced
• Free Video

Introduction to Generative AI

262 ratings

Explore the fundamentals of Generative AI, its applications, and how it differs from traditional machine learning, with an introduction to Google's development tools.

• Google Skills
• 45 minutes
• Self-Paced
• Free Certificate

University of Tübingen

Probabilistic Machine Learning

Comprehensive lecture series on probabilistic machine learning, covering Bayesian paradigms, statistical concepts, and deep learning connections for master's-level computer science students.

• YouTube
• 1 day 16 hours
• Self-Paced
• Free Online Course

Venelin Valkov

3D Photo Inpainting Python Tutorial - Turn Any Picture Into 3D Photo with Machine Learning

Learn to create stunning 3D photos from regular images using machine learning and Python. Explore the process of 3D photo inpainting, from setup to final results, in this hands-on tutorial.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Transformer Memory as a Differentiable Search Index - Machine Learning Research Paper Explained

Explore a novel approach to information retrieval using a single Transformer model that encodes corpus information in its parameters, enabling direct query-to-document mapping without external indices.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Gradients Are Not All You Need - Machine Learning Research Paper Explained

Explores limitations of differentiable programming in machine learning, focusing on chaos-based failures in various systems. Discusses alternatives to backpropagation for gradient estimation in complex, stochastic environments.

• YouTube
• 49 minutes
• Self-Paced
• Free Video