Deep Learning: Getting Started
With Kumaran Ponnambalam
Liked by 3 users
Duration: 2h 6m
Skill level: Intermediate
Released: 7/23/2026
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 you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
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Showcase on your LinkedIn profile under “Licenses and Certificate” section
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Download or print out as PDF to share with others
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Share as image online to demonstrate your skill
Meet the instructor
Learner reviews
Contents
What’s included
- Practice while you learn 1 exercise file
- Learn on the go Access on tablet and phone
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