Dive into the world of deep learning with this comprehensive course! Explore core algorithms and applications in NLP, computer vision, biology, and beyond. Build your own neural networks and gain practical skills. Delve into cutting-edge topics like large language models and generative AI. The course culminates in a project competition with valuable feedback from industry experts. Prerequisites include calculus and linear algebra, with Python experience a plus. Let's unlock the power of deep learning together!

felix
Instructor
Dr. Felix Gonda

Assistant Professor, Computer Science
E-mail: uojdeeplearning@gmail.com
Meeting: Click her to schedule a meeting

Thiong

Thiong Abraham
(Computer Vision)
Head Teaching Fellow

Anthony

Anthony Bush
(TF, Natural Language Processing)

James

James Anyieth
(TF, Generative Adversarial Networks)

Juma

Juma Albert
(TF, Reinforcement Learning)

Benson

Jalle Benson
(TF, Time Series Forecasting)

Lectures and Laboratory

Tuesdays and Thursday: 2pm-4pm
Location: The new UoJ Computer Laboratory

Prerequites

  • Linear Algebra: Background in matrices, vectors, and linear equations will come handy when you design models for classification, regression, etc.
  • Programming: Some programming experience, such as knowledge gain from taking an introductory course to programming is required.
  • Statistics: Statistics will help you extract insights from your raw data and is a valuable skill for a deep learning specialist.

Textbook

A PDF version of the book can be downloaded by clicking on the above image, and a free online version is available at: https://www.deeplearningbook.org