Duration: 1 day – 8 hrs
Overview
This training course provides a comprehensive introduction to generative AI and prompt engineering. Participants will learn the principles, techniques, and tools required to effectively utilize generative models like GPT-3 and GPT-4. The course covers crafting effective prompts, fine-tuning models, and applying generative AI to solve real-world problems across various domains.
Objectives
• Understand the fundamentals of generative AI and prompt engineering.
• Learn how to create effective prompts to elicit desired responses from generative models.
• Explore the architecture and functioning of models like GPT-3 and GPT-4.
• Gain hands-on experience in fine-tuning generative models.
• Apply generative AI to solve practical problems in various domains.
Audience
• AI Researchers and Practitioners
• Data Scientists
• Machine Learning Engineers
• Software Developers
• Business Analysts
• Product Managers
• Technology Enthusiasts
Prerequisites
• Basic understanding of machine learning and artificial intelligence concepts.
• Familiarity with programming languages such as Python.
• Basic knowledge of natural language processing (NLP) is helpful but not required.
Course Content
Module 1: Generative AI Foundation
▪ GenAI course Overview
▪ Define GenAI
▪ GenAI Demo
▪ Lab: Generate-Videos-in-single-prompt
▪ Applications of GenAI
▪ Technologies behind GenAI
▪ Part1-Ethics and Legal in AI
▪ Part2-Ethics and Legal in AI
▪ Lab: Generate ppt in 30 secs
▪ Managing GenAI Projects
▪ Security in GenAI
▪ Future of AI
▪ Lab: Generate AI voice in single prompt
▪ GenAI in Finance
▪ GenAI in Sales and Marketing
▪ GenAI in HR Management
▪ Lab: Generate AI avatar videos
▪ GenAI in Healthcare
Module 2: Prompt Engineering
▪ Define Prompt Engineering
▪ Prompting Technique
▪ Behind the scenes Prompt to output
▪ Lab: Prompt with Chatgpt 3.5
▪ Lab: Prompt with Chatgpt 4.0
▪ Lab1-Prompt with Anthropic Claude
▪ Lab: Prompt with Google Gemini
Module 3: Natural Language Processing
▪ Introduction to NLP
▪ Applications of NLP
▪ Evolution of NLP
▪ Challenges in NLP
▪ NLP tasks
▪ NLP Pipeline
▪ NLP tools and Libraries
▪ Lab 1: Email spam filtering
▪ Lab 2: Text summarization
▪ Lab 3: NLP-data-pre-processing
