Advanced Certificate in Applied Artificial Intelligence (AI) Programming Module 5: Introduction to AI Programming using Large Language Models (Synchronous E-Learning)
About This Course
Unlock the power of Large Language Models (LLMs) and Generative Pre-trained Transformers (GPT) in this immersive 2-day module. Participants will embark on a journey to understand the capabilities of LLMs, delve into the intricacies of GPT, and harness the potential of leading providers such as OpenAI and HuggingFace.
Through a combination of interactive lectures and hands-on exercises, participants will gain practical experience in integrating Python applications with OpenAI and HuggingFace application programming interfaces (APIs). They will learn to create simple artificial intelligence (AI) applications using LangChain, explore techniques to query local private data using LlamaIndex and LLM, and master the art of building intuitive AI user interfaces (UIs) with Gradio.
By the end of the module, participants will emerge with a comprehensive understanding of LLMs, GPT, and their applications in AI development. Armed with practical skills and knowledge, they will be equipped to leverage cutting-edge language models to build innovative AI solutions that push the boundaries of what is possible in natural language processing and artificial intelligence.
What You'll Learn
• Understand what is a Large Language Model (LLM)
• Understand what is a Generative Pre-trained Transformer (GPT)
• Use some of the GPT providers – OpenAI, HuggingFace, etc
• Integrate Python applications with OpenAI and HuggingFace
• Create simple artificial intelligence (AI) applications using LangChain
• Query local private data using LlamaIndex and LLM
• Build AI user interfaces using Gradio
Entry Requirements
• Basic programming experience using Python
• Recommended to have knowledge of NumPy and Pandas (covered in Module 2)
• Recommended to have knowledge of Machine Learning (covered in Module 3)
• Recommended to have knowledge of Deep Learning (covered in Module 4)