Harvard University - 5 FREE AI Courses!
- CS50’s Introduction to Artificial Intelligence with Python | edX
- graph search algorithms
- adversarial search
- knowledge representation
- logical inference
- probability theory
- Bayesian networks
- Markov models
- constraint satisfaction
- machine learning
- reinforcement learning
- neural networks
- natural language processing
- Fundamentals of TinyML | edX
- Fundamentals of Machine Learning (ML)
- Fundamentals of Deep Learning
- How to gather data for ML
- How to train and deploy ML models
- Understanding embedded ML
- Responsible AI Design
- Applications of TinyML | edX
- The code behind some of the most widely used applications of TinyML
- Real-word industry applications of TinyML
- Principles of Keyword Spotting
- Principles of Visual Wake Words
- Concept of Anomaly Detection
- Principles of Dataset Engineering
- Responsible AI Development
- Deploying TinyML | edX
- An understanding of the hardware of a microcontroller-based device
- A review of the software behind a microcontroller-based device
- How to program your own TinyML device
- How to write your code for a microcontroller-based device
- How to deploy your code to a microcontroller-based device
- How to train a microcontroller-based device
- Responsible AI Deployment
- Data Science: Machine Learning | edX
- The basics of machine learning
- How to perform cross-validation to avoid overtraining
- Several popular machine-learning algorithms
- How to build a recommendation system
- What is regularization and why it is useful?
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