
Generative AI Fundamentals
Employ the abilities of Generative AI with a deep dive into fundamentals. This course examines how various models are developed, how they work, and how to use them to their full potential.
LLM fine-tuning and optimization is genuinely one of the harder AI engineering specializations to develop. Practitioners need to customize general-purpose models for specific domains, reduce inference costs, and deploy efficient systems at scale. Udacity's LLM fine-tuning courses build the technical depth for this work, covering transformer neural network programming with PyTorch, model optimization principles, advanced compression techniques including quantization and pruning, and efficient architectural design with hardware acceleration. You'll learn how to adapt pre-trained models to new tasks, optimize for constrained deployment environments, and apply efficiency techniques that reduce compute costs without sacrificing performance.

Employ the abilities of Generative AI with a deep dive into fundamentals. This course examines how various models are developed, how they work, and how to use them to their full potential.

This course equips learners with essential techniques to enhance machine learning models. Starting with an introductory overview, the course covers key optimization strategies, including quantization techniques that reduce model size and improve efficiency. Students will explore pruning and sparsity methods to eliminate redundancy in models. The use of profiling tools and performance analysis is emphasized, allowing students to assess and refine their models effectively. Finally, the course culminates in practical applications, featuring hands-on experience with optimizing and deploying the GPT-2 model. Students will gain a solid foundation in optimizing state-of-the-art models for real-world applications.

This course equips learners with essential methodologies to reduce the size of machine learning models without significantly impacting performance. Starting with an introduction to various techniques, tools, and real-world applications, the course delves into post-training and training-time compression methods. Participants will explore how to build collaborative compression pipelines that enhance model efficiency. In the project "UdaciSense - Optimized Mobile Object Recognition," learners apply their knowledge to develop a practical, optimized solution for mobile devices. This course is perfect for AI practitioners seeking to advance their skills in model optimization.

This course will guide you through the essential concepts of Transformer Neural Networks and their implementation using PyTorch. Starting with an introduction to Transformers, you will learn to build and train Transformer models from scratch. Additionally, you will explore the advantages of using pre-trained Transformer models and how to leverage them effectively in your projects. By the end of this course, you will have a solid foundation in programming Transformer Neural Networks with PyTorch.
Fine-tuning builds on core model knowledge. Pair this collection with Generative AI & Large Language Models, Deep Learning, and RAG & Vector Database courses to understand the models, train them well, and extend them with your own data.

Gain a solid background in AI basics to better understand Generative AI, or compliment your AI knowledge with product management skills to create AI-powered products. Explore the exciting field of Game Development and Monetization.

Deep learning opens into several applied specialisms. Pair this collection with Machine Learning & Deployment, Computer Vision, and LLM Fine-Tuning & Training to ship models, work with image data, and adapt large language models to your own tasks.

Retrieval-augmented systems connect to the wider LLM toolkit. Explore AI Agent Development, Generative AI & Large Language Models, and LLM Fine-Tuning & Training to ground models in your data and improve how they respond.

Explore all of Udacity’s Schools, consisting of hundreds of career-driven programs and courses that are designed to teach practical skills and help you learn to your full potential.