Overview
Coursera
Dive into the fundamentals of generative AI with our comprehensive course on Large Language Models (LLMs). This program is designed to equip learners with essential knowledge to deploy generative AI in practical scenarios.
- Understand the lifecycle of LLM-based generative AI and the key steps involved, including data gathering, model selection, and deployment.
- Gain insights into the transformer architecture, its training processes, and the fine-tuning techniques that adapt LLMs to diverse applications.
- Leverage empirical scaling laws for optimizing model performance in relation to dataset size, compute resources, and inference requirements.
- Master cutting-edge methodologies for training, tuning, inference, and deployment to enhance model performance within project constraints.
- Explore challenges and opportunities in generative AI through insights from industry experts and practitioners.
This intermediate course is ideal for developers with a basic understanding of Python and machine learning, including supervised and unsupervised learning techniques. Prior courses such as Machine Learning Specialization or Deep Learning Specialization by DeepLearning.AI will help in grasping the advanced concepts discussed here.
Enroll now in this Coursera course and develop the practical intuition needed to harness the potential of generative AI for your projects.
Categories covered include Machine Learning, Reinforcement Learning, Neural Networks, Generative AI, Model Training and Deployment, Fine-Tuning, and Transformer Architecture.
