Level 1 : Foundation – Generative AI Essentials for Software developers
Course Duration : 5 days
Training Mode : Choose from Virtual Live Instructor Led or Classroom Mode
Course Description: This course offers a practical and foundational understanding of Generative AI, guiding practitioners through Python essentials, data structures, and machine learning foundations, before delving deeply into Generative AI, prompt engineering, natural language processing, and large language models (LLMs). With a hands-on approach, participants will explore real-world applications, ethical considerations, and advanced tools such as Hugging Face. By the end of the course, attendees will have the knowledge and skills to apply Generative AI solutions effectively in various domains.
Module 1: Python Programming Essentials
- Core Python Concepts
- Operators and Expressions
- Data Types in Python
Module 2: Data Structures and File Operations in Python
- Lists and Tuples
- Dictionaries and Variables
- File Handling
- Functions and Modular Programming
Module 3: Foundations of Machine Learning
- Essential Resources for ML
- Introduction to Machine Learning Concepts
- Data Manipulation with Numpy
- Data Analysis with Pandas
- Using Numpy and Pandas Together
- Supervised Learning Basics
- Introduction to Unsupervised Learning
- Linear Regression Fundamentals
Module 4: Introduction to Generative AI
- Overview of Generative AI
- Defining Generative AI
- Generative AI Demonstration
- Lab: Create Videos with a Single Prompt
- Real-World Applications of Generative AI
Module 5: Generative AI Foundations and Ethical Considerations
- Technologies Powering Generative AI
- Ethical and Legal Aspects of AI – Part 1
- Ethical and Legal Aspects of AI – Part 2
- Lab: Rapid PPT Creation in 30 Seconds
- Managing Projects in Generative AI
Module 6: Security and Future Directions in Generative AI & Introduction to Hugging Face
- Security Considerations in Generative AI
- The Future of AI Technology
- Lab: Generate AI Voice with a Single Prompt
- Introduction to Hugging Face
- Lab: Hands-on Tasks with Hugging Face
Module 7: Fundamentals of Prompt Engineering
- Introduction to Prompt Engineering
- Techniques in Prompting
- Behind the Scenes: From Prompt to Output
- Lab: Experiment with Deepseek
- Lab: Experiment with ChatGPT 4.0
Module 8: Advanced Prompt Engineering and Hugging Face Fine-Tuning
- Lab: Prompting with Anthropic Claude
- Lab: Prompting with Google Gemini
- Lab: Fine-Tuning with Hugging Face DITLILBERT
Module 9: Natural Language Processing Essentials
- Introduction to NLP Concepts
- Key Applications of NLP
- Evolutionary Trends in NLP
- Current Challenges in NLP
- Common NLP Tasks
- Building an NLP Pipeline
Module 10: Practical NLP Labs
- Tools and Libraries for NLP
- Lab: Filter Spam from Emails
- Lab: Summarize Text
- Lab: NLP Data Preprocessing Techniques
Module 11: Large Language Models and AI Application Development
- Large Language Models Overview
- Use Cases of LLMs
- Advantages of Leveraging LLMs
- Custom LLMs vs. Fine-Tuned Models
- Exploring Multimodal LLMs
- Lab: Programmatic Access to OpenAI
- Lab: NLP Tasks with OpenAI LLM
- Lab: Programmatic Access to Anthropic Claude
- Lab: NLP Tasks with Ollama – build a rag chatbot
- Lab: Develop a PDF Chatbot
- Lab: Create a Text and AI Voice Integrated App
- Lab: Build a Website Chatbot for Handling PHI Data