Introduction to Generative AI ( LLM )

Course Overview:

Welcome to the cutting-edge world of Generative AI! This course is designed for students who want to explore the rapidly evolving field of Large Language Models (LLMs) and understand how tools like ChatGPT, Claude, and Gemini are built and used. You will learn how machines can generate human-like text, code, and content through deep learning and transformer architectures. Through hands-on projects and real-world examples, you'll gain practical experience using and fine-tuning LLMs for a variety of applications.

What You Will Learn:

• What is Generative AI and what makes LLMs special

• How LLMs like GPT, Claude, and Mistral work

• Understanding tokenization, embeddings, and attention mechanisms

• Transformer architecture: self-attention and encoder-decoder models

• Prompt engineering: how to write effective prompts for LLMs

• Using OpenAI APIs (ChatGPT, GPT-4) and other LLM tools

• Fine-tuning and customizing pre-trained models

• RAG and MCP

• Building chatbots, summarizers, and content generators

• Ethical concerns: AI bias, hallucinations, and responsible use

• How LLMs are changing education, business, and creativity

Course Features:

• Hands-on Exercises: Interact with real LLMs, test prompts, and build mini projects

• Real-World Examples: Learn how LLMs are used in writing, coding, customer support, and more

• Live Support: Q&A sessions and instructor feedback to support your learning

• Flexible Learning: Access to online materials, recorded lectures, and example notebooks

Ideal For:

• Students curious about ChatGPT and other AI tools

• Beginners with basic Python knowledge interested in generative AI

• Future AI developers, researchers, and digital creators

• Anyone exploring how AI can write, answer questions, and solve problems like a human

Duration:

About 10 weeks, with 1 session per week (1 hours per session)

Prerequisites:

A basic understanding of Python and high school-level math is recommended. No deep learning background required.

Materials Included:

• Access to video lectures and prompt design tutorials

• Example notebooks using OpenAI API and Hugging Face tools

• Datasets, model access links, and coding exercises

• Readings on ethics, limitations, and future directions of LLMs

Outcome:

By the end of this course, you will be able to interact with and customize LLMs, write effective prompts, and build simple generative AI applications. You’ll also gain a strong conceptual foundation to explore advanced generative AI and NLP topics.

Join Us Today and Start Building with Generative AI!