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Generative AI Crash Course

By Aman In Grow Data Skills

Live Classes
English
Completion Certificate

1 Year

Validity (From the date of Enrollment)

30 Hours

Duration

13

Sessions

2

Projects

INR 3500

Admission Open (120 Seats Left)

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This course includes

Content Duration30 Hours
Total Sessions13
Total Industry Projects2
Project will be covered from scratch
Tools – Jupyter Notebook, Google Collab, PyCharm, Spyder, Visual Studio
Technology – OpenAI, Generative AI, Cloud, LLM, Computer Vision
Certificate of completion

Tech stack you'll learn

Course Content

✅ Class 1: Understanding Generative AI

What is Generative AI? Why now?
Evolution from GPT-2 to GPT-4o, Claude, Gemini, Mistral, LLaMA
Generative AI vs Traditional AI
Popular use cases across industries

✅ Class 2: Transformers & Foundation Models

Transformer architecture: Encoder, Decoder, Encoder-Decoder
Pre-training vs Fine-tuning
Anatomy of Foundation Models
Overview of major LLMs: GPT, LLaMA, Claude, Gemini, Mixtral

✅ Class 3: Prompt Engineering & Text Generation

Prompt types: Zero-shot, Few-shot, Chain-of-Thought
Parameters: Temperature, Top-k, Top-p
Completion vs Chat mode
Tools: OpenAI Playground, Hugging Face Transformers

✅ Class 4: Hands-on Project 1 — AI Content Generator

Build a Streamlit or FastAPI app for blog/product/tweet generation
Prompt templates for tone, style, length
Deploy using OpenAI or Hugging Face LLMs

✅ Class 5: Text-to-Image & Image-to-Image Models

Diffusion Models: Stable Diffusion, DALL·E 3, Midjourney
Prompting for image generation
Text-to-image, inpainting, and image variation demos

✅ Class 6: Multimodal AI in Action

GPT-4o, Gemini 1.5, LLaVA, Flamingo overview
Text + image + audio + video models
Applications: Virtual Assistants, Search, Customer Service

✅ Class 7: Deep Dive into RAG

Why LLMs need RAG (context windows, hallucination)
Vector embeddings and similarity search
Vector DBs: FAISS, Chroma, Pinecone
Tools: LangChain, LlamaIndex

✅ Class 8: Hands-on Project 2 — Chat with Your PDFs

Upload PDF → extract text → embed → chat
FAISS + LangChain or LlamaIndex + Streamlit
Use OpenAI or LLaMA as the backend model

✅ Class 9: Fine-tuning LLMs & Parameter-efficient Training

When to fine-tune vs prompt-engineer
LoRA, QLoRA, PEFT explained
Tools: Hugging Face Trainer, OpenAI Fine-tune API
Dataset curation & model hosting

✅ Class 10: Agents & Tool Use

What are LLM agents?
LangChain Agents, OpenAI Function Calling
Autonomous agents: AutoGPT, BabyAGI
Use Cases: Report generation, browsing, scheduling

✅ Class 11: Deploying GenAI Apps

Build FastAPI, Streamlit, Gradio apps
Containerize with Docker
Hosting: RunPod, Replicate, Azure/AWS/GCP
Scalability & cost optimization tips

✅ Class 12: Risks, Ethics & Career in GenAI

Hallucination, bias, and safety concerns
Guardrails & moderation tools
Copyright & responsible AI
Career paths, portfolio building & trends for 2025

Building a Strong Analytics Engineer Portfolio
Resume Optimization for Data Roles
Preparing for Technical Interviews
Networking and Job Search Strategies

Course Schedule

Course Starts On:

31-May-2025

Mode Of The Course:

Live

Course Duration:

30 Hours

Total Sessions:

Total Project:

Course Validity:

1 Year (From the date of enrollment)

Class Timing:

Saturday & Sunday [5:00 PM - 7:00 PM Live Teaching, 7:00 PM to 7:45 PM Live Doubt Session] (IST)

Class Duration:

2 Hours Live Teaching, 45 minutes Doubt Solving

Prerequisite:

Python

⚠️ Important Notice :

The video may not work on Linux due to DRM restrictions. It is only accessible on Chrome when using Windows or macOS.

Workaround: To access the video on Linux, you can create a Windows virtual machine (VM) and watch the video through the VM. Alternatively, you can use our Android or iOS application to view the video on your mobile device.

Instructor

Aman Kumar

Aman, an experienced Data Scientist at EY, excels in turning data into impactful insights and solutions. Beyond his work, he's a certified IBM Instructor for IoT and AI, having mentored over 500 students in Data Science, NLP, ML, and AI. Aman's commitment to education and innovation showcases his passion for using data to drive positive change.