Generative AI & Prompt Engineering Masterclass

Generative AI & Prompt Engineering Masterclass

₹15,990.00

CandidatureDurationProspect

    1. This course is designed for working professionals and tech enthusiasts who are ready to upskill and future-proof their careers in the booming field of Generative AI.

      ✅ Ideal for:

      • Data Scientists aiming to expand into LLMs and generative models

      • Tech Leads & Architects exploring intelligent workflows

      • Product Managers integrating GenAI into user experiences

      • AI/ML enthusiasts & freshers wanting to fast-track their GenAI journey

The Generative AI & Prompt Engineering Masterclass is structured as a 3-month live instructor-led training program, designed to blend guided mentorship with active hands-on practice.

Total Duration (Live Sessions): 3 Months
⏱️ Live Class Frequency: 5 sessions per week
Total Commitment: 10 hours per week

After completing this masterclass, you’ll be fully equipped to take on real-world AI challenges and apply for high-growth roles in the industry.

‍ Career Paths You Can Pursue:

  • Prompt Engineer [Avg. Salary (India): ₹18–30 LPA]

  • Generative AI Developer [Avg. Salary (India): ₹15–28 LPA]

  • LLM Application Engineer [Avg. Salary (India): ₹14–25 LPA]

  • AI/ML Engineer (with GenAI focus) [Avg. Salary (India): ₹12–20 LPA]

  • Chatbot & Virtual Assistant Developer [Avg. Salary (India): ₹8–15 LPA]

  • AI Product Analyst or Consultant [Avg. Salary (India): ₹10–18 LPA]

 

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Description

From mastering Large Language Models (LLMs) like GPT, Claude, and Gemini to building intelligent AI-powered applications with LangChain and Retrieval-Augmented Generation (RAG), this course provides end-to-end training to transform you into a Generative AI practitioner. You’ll explore prompt engineering strategies, learn how to interact with text, image, and video generation models, and even develop your own AI agents and applications.

Step into this Generative AI & Prompt Engineering Masterclass — a comprehensive, hands-on course designed to equip you with the most in-demand skills in the AI revolution.

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Course Outline
Module 1: Python Essentials for AI

  1. Python Data Types, Loops, Functions

  2. Data Structures in Python (Lists, Dicts, Sets)

  3. NumPy & Pandas for Data Handling

  4. Mini Project: Data cleaning & JSON-based prompt generator
Module 2: Foundations of Generative AI

  1. What is Generative AI? How it differs from traditional ML

  2. Applications in images, text, video, and code generation

  3. Types of GenAI Models: VAEs, GANs, Diffusion Models, Transformers

  4. Key Concepts: Embeddings, Sampling, Latent Space

  5. Hands-on: Try DALL·E2, Stable Diffusion, Midjourney, and RunwayML

Module 3: LLMs and Transformer-based Architectures

  1. Understanding Attention & Transformers

  2. LLM Ecosystem: GPT-4, Gemini, Claude, LLaMA, Falcon

  3. Pre-training, Fine-tuning & RLHF

  4. Self-hosted LLMs using Hugging Face, Ollama

  5. Hands-on: Query GPT/OpenAI & HuggingFace models via API

Module 4: Prompt Engineering Essentials

  1. Prompt Design Strategies: Zero-shot, Few-shot, CoT

  2. Chat Prompts vs Completion Prompts

  3. Hands-on with OpenAI Playground

  4. Image Prompting for DALL·E & Midjourney

  5. Common Pitfalls and Prompt Optimization Tips

Module 5: LangChain and RAG

  1. What is LangChain and Why Use It?

  2. LangChain Components: Chains, Agents, Memory

  3. Retrieval-Augmented Generation (RAG)

  4. Hands-on: Build your own Q&A bot over a PDF or website

Module 6: Building LLM-Powered Applications

  1. Architecting LLM Workflows

  2. Vector Databases: FAISS, ChromaDB

  3. Embedding Models & Search

  4. Benchmarking and Evaluating LLMs

  5. Prompt Injection & Guardrails

Module 7: Agentic AI & Autonomous Workflows

  1. Agent Concepts: Actions, Goals, Memory

  2. LangGraph, CrewAI, AutoGen Overview

  3. Hands-on: Create a multi-agent system using LangChain or CrewAI

Module 8: Generative AI on the Cloud

  1. OpenAI on Azure, Gemini on Google Cloud

  2. Deploying LLMs in AWS Sagemaker / GCP Vertex AI

  3. Fine-tuning on the Cloud

  4. Integrate LLM APIs with Web/Mobile apps

Module 9: Generative AI for Images & Videos

  1. Intro to Diffusion Models & VAEs

  2. Autoencoders, Shared Embeddings

  3. Hands-on Tools: Stable Diffusion, RunwayML, Synthesia

  4. Contrastive Learning Techniques

  5. Use Cases: Ad generation, avatar creation, branding assets

Module 10: AI Governance & Ethics

    • Ethical AI Design Principles

    • AI Governance Structures & Lifecycle

    • Risks of Deepfakes, Bias & Hallucinations

    • Industry Guidelines (EU AI Act, NIST, etc.)

    • Future Trends in AI Regulation

Module 11: Capstone Project

  1. Build a GPT-powered FAQ bot with document retrieval

  2. Create a product description generator with OpenAI & LangChain

  3. Design a chatbot agent using CrewAI + embedding store

  4. Image-to-story creative writing generator using DALL·E & LLM

 

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