Deep Learning: Getting Started (2026)
Released 7/2026
With Kumaran Ponnambalam
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 6m | Size: 219.1 MB
Learn the fundamentals of deep learning through hands-on Python examples and understand how neural networks power modern AI and generative AI systems.
Course details
As generative AI adoption accelerates, many technical professionals are expected to work with neural networks and AI models without a clear understanding of how they're built or trained. In this course, instructor Kumaran Ponnambalam provides a practical, hands-on introduction to deep learning, guiding you step by step through designing, training, and evaluating neural network models using Python and modern frameworks. Through real‑world examples in both structured and text data, learn how to build working models while learning the foundational workflows that power today's AI systems. Along the way, find out how to connect core deep learning concepts to modern generative AI architectures like transformers, embeddings, and foundation models. By the end of this course, you'll be prepared to confidently evaluate, adapt, and reuse deep learning models in enterprise AI applications.This course is integrated with GitHub Codespaces, an instant cloud development environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you'll likely encounter in the workplace.
Skills covered
Generative AI, Deep Learning, Artificial Intelligence (AI), Python (Programming Language)
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