Ian Wilson's Strategy4AI Masterclass in Business AI: https://courses.strategy4.ai/ *** HIGHLY RECOMMENDED***
Getsmarter MIT | SLOAN Artificial Intelligence: Implications for Business Strategy course. 6 weeks, 6-8h/week = 42h. Earn MIT Sloan Certificate. Covers Intro to AI, ML in business, NLP in business, Robotics in Business, AI in business & Society, and the future of AI. REG PAGE
GetSmarter MIT Mgmt / CSAIL Machine Learning in Business. 6 weeks, 6-8h / week = 56h. Focused on ML, sensing, language, pattern recognition and ML challenges.
Northwestern | Kellogg School of Mgmt Artificial Intelligence: Strategies for Leading Business Transformation. 2 months, online, 4-6h/week,
Berkeley Haas Executive Education Artificial Intelligence Business Strategies and Applications. 2 months, 4-6h/week = 40h. Covers
GetSmarter / Berkeley School of Information. Artificial Intelligence Strategy online short course. 6 weeks at 7-10h/week = 50h. Includes informatino on why this time it’s different, challenges and approaches to determining an AI strategy, resource requirements for adopting an AI strategy, KPIs and identifying threats, consolidating your AI strategy canvas, and future AI implications.
EdX / Micro-masters Program in AI from Columbia University. 1 yr at 8-10h/week = 470h.
Coursera IBM AI Engineering Professional Certificate. 2 months. Coursera. 6 courses included covering ML with Python, Apache Spark, DL & NN with Keras, DNN with PyTorch, DL with TensorFlow and Capstone Project.
EdX / IBM Professional Certificate in Deep Learning. 84 h (7 months at 2-4h/week).
edX / Columbia / Artificial Intelligence (AI) program for practitioners. 12 wks, 8-10h/week = 110-120h. Includes content on History, agents, heuristic search, adversarial search, constraint satisfaction, ML Basics, ML Advanced, Neural networks, SVMs, decision trees, unsuperviised learning, Markov decision procsses and reinforcement learning, NLP, Vision/Robotics.
Deep Learning Nanodegree / Udacity/ AWS / Facebook. 4mo, 12h/week = 192h. Includes intro, Neural networks, convolutional neural networks, recurrent neural networks, generative adversarial networks. sentiment analysis models.
Deep Learning Online Course Udacity. AWS. Facebook. 4 mo, 12h/week = 192h. Pre-reqs include Python, NumPy, and pandas, calculus, linear algebra. Includes intro to neural networkks, convolutional neural networks, reecurrent neural networks, generative adversarial networks, and sentiment analysis.
Deep Learning Specialization Deeplearning.ai / Coursera. Andrew Ng. 3 mo. 11h/week = 132h. Includes courses on NN / DL, improving DNN; Structuring ML projects, Convolutional NNs, and Sequence models.
Deep Reinforcement Learning Nanodegree. Udacity with Unity, NVIDIA. 4mo at 10-15h/week = 192h. Includes courses on Reinforcement learning, value based methods, policy based methods, and multi-agent reinforcement Learning.
Intro to Machine Learning with Pytorch Course. Udacity w/ Kaggle, AWS. 3 mo at 10h/week = 120h. Includes courses on supervised, deep, and unsupervised learning.
Introduction to Machine Learning with TensorFlow. Udacity/Kaggle/AWS. 3 mo at 10h/week. Req Intermediate Python skills. Includes courses on supervised Learning, Deep Learning, Unsupervised Learning.
Become a Machine Learning Engineer. Udacity. Kaggle. AWS. 3 mo at 10h/week.= 120h. Pre-reqs: Int Python and ML algorithms. Includes info on software engineering fundamentals, ML in production, ML case studies, ML capstone project.
AI: Artificial Intelligence (AI) Online Courses
Artificial Intelligence (AI) for Business Leaders. Udacity / BMW. 4-8 wks at 5h/week = 40h. Includes courses on paradigm shift, math behind AI, architectures, working with data, accuracy/bias/ethics, soliciting feedback on model prototypes, deploying AI at scale, and delivering a ML/AI strategy for your organization.
AI for Leaders by Babson on edX. 4 weeks x 4-6h/week. $199.
Individual Business Leader Courses
Machine Learning for Leaders (AWS)
Demystifying AI/ML/DL (AWS)
AI for Everyone. Andrew Ng / Deeplearning.ai / Coursera. 4 weeks, 2-3h/week = 9h. Includes information on what is AI, building AI, building AI at your company and AI and society.
Introduction to Artificial Intelligence AI. by IBM/Coursera. 4 weeks at 1-2h/week = 9h.
Become an AI Product Manager. Udacity / Figure Eight. 2 mo at 5-10h/week = 56h. Includes Intro to AI, creating a dataset, building a model, measuring impact and updating models
AI Foundations for Everyone Specialization. IBM/Coursera. 1 month, 13h/week = 52h. Includes Introduction to AI, Getting started with AI using IBM Watson, and Building AI Powered Chatbots without programming.
IBM Applied AI Professional Certificate. IBM/Coursera. 2 months, 13h/week = 104h. Includes 6 sub-courses: Introduction to AI, Getting Started with AI using IBM Watson, Building AI Powered Chatbots without programming, Python for Data Science and AI, Building AI applications with Watson APIs, and Introduction to Computer Vision with Watson and OpenCV.
Artificial Intelligence by Georgia Tech / Udacity
Artificial Intelligence foundational AI Algorithms Udacity
Learn Data Structures and Algorithms Udacity
Machine Learning (Supervised, Unsupervised, and Reinforcement) by Georgia Tech / Udacity
Data Science: Machine Learning by Harvard on edX. 8 weeks, 2-4h/week = 24h. $49.
TensorFlow in Practice Specialization. Deeplearning.ai / Coursera. 1 month, 14h/week = 56h. Includes 4 sub-courses on TF for AI/ML/DL, convolutional neural networks, NLP, and sequences, time series, predictions.
TensorFlow: Data and Deployment Specialization. Deeplearning.ai / Coursera. 1 month, 18h/week = 72h. Includes 4 sub-courses on TensorFlow.js, device-based models, data pipelines and TF data services, and advanced deployment.
AI Programming with Python. Udacity. 3 mox10h/week = 120h. Pre-req algebra and programming knowledge. Includes intro to Python, Jupyter Notebooks, NumPy, Anaconda, Pandas, Matplotlib; Linear algebra, Calculus, Neural Networks.
Deep learning basics (MIT)
Machine Learning by Andrew Ng / Stanford / Coursera. 56h. Heavy Math focus including linear regression, linear algebra, octave/Matlab, log regression, regularization, etc.
Using AI for social good (GOOG)
Introduction to AI and machine learning (GOOG)
What is Machine Learning? (GOOG)
The 7 Steps of Machine Learning (GOOG)
AI Experiments (GOOG)
Machine Learning: Making Sensor of a messy world (GOOG)
Machine Learning: Solving Problems, Big Small, and Prickly (GOOG)
Machine Learning Glossary (GOOG)
Examples of what AI and ML can do: Forecasting floods, monitoring marine life, dettecting plant disease, wildlife conservation, preventing overfishing, predicting wildfires, advancing education (GOOG)
Introduction to Machine Learning Problem Framing (GOOG)
Data Sources including data prep, feature engineering, fairness/bias, datasets from GCloud, kaggle, Google earth engine, google dataset
Using AI Responsibly (GOOG) including Responsible AI, Google AI principles, Fairness in ML, What-if tools
Accessing the right skill set (GOOG)
Getting started with Machine Learning (GOOG)
Crash Course on Machine Learning (GOOG)
Problem Framing (GOOG)
Data Prep (GOOG)
Testing and debugging (GOOG)
Generative Adversarial Networks GANs
DeepMind - From Generative Models to Generative Agents - Koray Kavukcuoglu
Unsupervised Deep Learning - Google DeepMind & Facebook Artificial Intelligence NeurIPS 2018