Programming Generative AI: Unit 1

Overview

Unlock the transformative power of generative AI with our comprehensive online course, designed for learners eager to master the fundamentals and practical applications of deep generative modeling. Begin your journey by demystifying what generative AI truly is, exploring the diverse landscape of multimodal models, and understanding how algorithms can create rich media content from scratch. Delve into the theoretical underpinnings and formalizations that drive deep generative models, gaining insight into the trade-offs between different architectures. Transition seamlessly from theory to practice as you are introduced to the PyTorch framework—one of the most powerful tools in modern deep learning. Through hands-on programming exercises, you’ll learn to manipulate tensors, leverage automatic differentiation, and harness GPU acceleration to build and train your own neural networks. By the end of this course, you’ll not only grasp the core concepts behind generative AI but also acquire the practical skills needed to implement and experiment with deep learning models using industry-standard tools. Whether you’re aspiring to innovate in AI research or apply these skills in real-world projects, this course is your gateway to the future of artificial intelligence.

Syllabus

Programming Generative AI: Unit 1

This module introduces the fundamentals of generative AI and deep generative modeling, exploring how algorithms can create rich media across various modalities. It covers the theoretical foundations and trade-offs of different generative model architectures. The module then provides hands-on experience with the PyTorch framework, guiding learners through programming with tensors, leveraging automatic differentiation, and building neural networks. By the end, students will understand both the principles behind generative models and the practical skills needed to implement them using modern deep learning tools.