Generative AI Professional

Comprehensive training designed for professionals

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Course Overview

Explore the course outline and contact our advisors about prerequisites, practical work, and current availability.

For the current syllabus, prerequisites, fees, and batch availability, contact our training advisors.

Meet Your Instructor: Dr. Muhammad Bilal

Machine learning researcher and practitioner specializing in applied AI, generative models and intelligent systems.

Course Lectures

Course Content

1 Generative AI Landscape & Foundations
2 Prompt Engineering Mastery
3 LLM Architecture Deep Dive
4 RAG Systems: Design & Implementation
5 AI Agents & Tool Use
6 Fine-Tuning LLMs
7 Evaluating & Securing AI Systems
8 Generative AI Capstone Project

Generative AI Landscape & Foundations

2 hours

Lecture 1 of 8

From GANs to transformers: how generative models work and where they create business value.

Prompt Engineering Mastery

2 hours

Lecture 2 of 8

System prompts, few-shot learning, chain-of-thought, and structured output techniques.

LLM Architecture Deep Dive

2 hours

Lecture 3 of 8

Tokenization, attention, and transformer blocks explained intuitively with visualizations.

RAG Systems: Design & Implementation

3 hours

Lecture 4 of 8

Build retrieval-augmented generation pipelines with vector databases and LangChain.

AI Agents & Tool Use

3 hours

Lecture 5 of 8

Function calling, ReAct agents, and multi-agent workflows for autonomous task completion.

Fine-Tuning LLMs

2 hours

Lecture 6 of 8

LoRA/QLoRA fine-tuning, dataset preparation, and evaluation of custom models.

Evaluating & Securing AI Systems

2 hours

Lecture 7 of 8

Hallucination control, guardrails, red-teaming prompts, and OWASP LLM Top 10 defenses.

Generative AI Capstone Project

3 hours

Lecture 8 of 8

Design and deploy a production-grade AI application with your chosen use case.

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Eligibility Criteria

Python basics and general AI/ML awareness. No deep learning expertise required.

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Generative AI Professional