Abstract Futuristic Background

Create neural networks and big data

Artificial Intelligence

Class Description:

Machine learning (ML) tools are increasingly being used by companies and governments to shape our world, and basic ML proficiency is rapidly becoming a required skill in most technical fields. It is also a deeply interesting subject that most people enjoy and find useful. This course will provide you with a solid foundation and introduce you to some state-of-the-art tools in an approachable environment.

 

Prerequisites:


Required:
- Precalculus
- Basic programming course

Ideal:
- Statistics
- Calculus
- Intermediate coding ability (2 courses and/or comfortable with data structures)
- Python (NumPy)

Syllabus:


1. Introduction to ML; Python, data structures
2. Vectors, Matrices, Tensors
3. Regression, optimization
4. Simple neural networks (MLP)
5. Optimization & Regularization
6. Convolutional neural networks (CNN)
7. Transfer learning
8. State-of-the-art, diversity of models + project
9. Ethics + project
10. Project
11. Project
12. Project

About the instructor:


Rich Hakim is a PhD candidate in Neuroscience at Harvard and former student at PVNET. He studies how the brain learns to move and develops tools for brain-machine-interfacing.

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Interested? Check out our
 Course Catalog