GenAI Seekhne Ke 30 Din Ka Plan (Hinglish)

GenAI engineer roles 2026 mein 60% growth dekh rahi hai. Salaries ₹15 LPA se ₹80 LPA tak (3 saal exp ke baad).

Aur tum YouTube pe "GenAI tutorial India" search kar rahe ho aur confused ho. Sab Sundar Pichai bann'na chahta hai 1 din mein.

30 din ka realistic plan. Free resources. Indian context. No bullshit.

Pehle yeh samjho#

GenAI engineer ban'na hai? Yeh roles hai:

1. AI Application Developer (entry): GPT-4 APIs use karke apps banata hai. Salary: ₹8-20 LPA
2. ML Engineer (GenAI focus): RAG systems, fine-tuning. Salary: ₹15-40 LPA
3. GenAI Researcher: Novel models, papers. Salary: ₹40-1.5 Cr (PhD level)
4. Prompt Engineer: Pure prompting expert. Salary: ₹10-25 LPA (declining role)

30 din mein tum #1 (AI Application Developer) ban sakte ho. Yeh practical hai. Real jobs aati hai.

Pre-requisites#

Yeh hone chahiye pehle:

• Python basics (variables, functions, classes, list/dict)
• Git/GitHub basics
• REST API concept
• HTML/JS basic (frontend ke liye)
• Curiosity aur 30 din ka commitment

Agar Python nahi aati, pehle 1 week Python karo (freeCodeCamp Python tutorial YouTube).

Hafta 1: GenAI fundamentals + APIs#

Day 1-2: GenAI intro

Watch:

• 3Blue1Brown "Neural Networks" playlist (YouTube, free)
• "Transformers explained" Andrej Karpathy (1 hour video)

Read:

• OpenAI docs intro (platform.openai.com/docs)
• Anthropic API docs intro (docs.anthropic.com)

Yeh sirf samjhne ke liye hai. Math mein deep dive mat karo.

Day 3-4: First API call

Setup:

• OpenAI account banao ($5 free credit usually)
• ya OpenRouter (cheaper, multiple models)
• ya Groq (free tier with Llama models)

Pehla project: Python script jo ChatGPT API call kare aur jokes generate kare.

from openai import OpenAI

client = OpenAI(api_key="sk-...")

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": "Tell me an Indian engineering joke"}
    ]
)
print(response.choices[0].message.content)

Yeh kaam karta to GenAI ka 30% samajh aa gaya.

Day 5-7: Streaming, system prompts, parameters

Concepts:

• System prompt vs user prompt
• Temperature (0 vs 1)
• Max tokens
• Streaming responses
• Function calling (tools)

Project: Apna chatbot banao. Streamlit use karke.

pip install streamlit openai

Streamlit ka chatbot template GitHub pe free milta hai. Customize karo.

Hafta 2: RAG (Retrieval Augmented Generation)#

Yeh sabse important concept hai for jobs. 80% AI applications RAG-based hai.

Day 8-10: RAG basics

Concept: Tumhare apne documents pe ChatGPT chala'na. Pehle relevant chunks dhundo, fir LLM ko context do.

Components:

• Document loader (PDF, text, etc.)
• Chunker (split text in pieces)
• Embedder (text to vectors)
• Vector DB (Pinecone, ChromaDB, Weaviate)
• Retriever (query → relevant chunks)
• LLM (final answer generate)

Watch:

• LangChain YouTube series (free)
• "Building RAG applications" by Pinecone (YouTube)

Day 11-14: Build RAG app

Project: PDF chatbot. User PDF upload kare. Questions pucho. Answer mile from PDF only.

Stack:

• LangChain (orchestration)
• ChromaDB (vector store, local, free)
• OpenAI embeddings
• GPT-4o-mini (LLM)
• Streamlit (UI)

Tutorial: "LangChain PDF chatbot" YouTube pe search karo. 50+ tutorials available.

Yeh project har AI job interview mein puchte hai. Achi quality wala project banao.

Hafta 3: Production patterns#

Day 15-17: Prompt engineering

Beyond basics:

• Chain of thought prompting
• Few-shot examples
• Output formatting (JSON mode)
• Prompt chaining
• Self-critique loops

Practice: 10 different problems prompt karke solve karo. Resume parsing, code review, content generation, etc.

Day 18-21: Agents aur tools

Concept: LLM ko tools de do (web search, calculator, custom APIs). LLM khud decide karta hai kab kaunsa tool use karna hai.

Frameworks:

• LangChain Agents
• LangGraph (newer, recommended)
• OpenAI Assistants API
• AutoGen (Microsoft)

Project: Personal assistant agent. Email parse kare, calendar check kare, summary do.

Hafta 4: Deployment + portfolio#

Day 22-25: Real deployment

Apne projects deploy karo:

• Streamlit Cloud (free, easy)
• Hugging Face Spaces (free)
• Vercel (Next.js apps)
• Render (free tier)

Each project ka live URL hona chahiye. Recruiters click karte hai.

Day 26-28: GitHub portfolio

Apna GitHub clean karo:

• 3-5 quality projects
• Each project mein detailed README
• Architecture diagram
• Tech stack listed
• Demo video (1-2 min)
• Live link

Top GenAI portfolios mein dekh:

• github.com/topics/genai-portfolio (browse karo)
• github.com/topics/rag-application

Day 29-30: Job applications

Resume update:

• Headline: "GenAI Engineer | LangChain, RAG, LLMs"
• 5 projects listed
• Skills section: Python, LangChain, LangGraph, ChromaDB, OpenAI API, Anthropic API, Streamlit

Apply:

• AI startups (Sarvam AI, Krutrim, Yellow.ai, ChatPay)
• Mid-size product (Postman, Hasura, Razorpay)
• GenAI consultancies
• Big tech AI teams (Microsoft, Google, Amazon GCC)

Free resources (best 10)#

1. Andrew Ng's "Generative AI for Everyone" - Coursera free audit
2. DeepLearning.ai short courses - Free, 1 hour each, hands-on
3. LangChain documentation - Best official docs
4. Hugging Face course - Free, deep dive
5. Fast.ai Practical Deep Learning - Free
6. OpenAI Cookbook - GitHub examples
7. Anthropic Cookbook - Claude examples
8. 3Blue1Brown YouTube - Neural networks visualized
9. Karpathy's "Build GPT from scratch" - YouTube, 4 hours
10. Indly Code (YouTube) - Hindi GenAI tutorials

Paid resources (worth ₹2000)#

• DeepLearning.ai specialization (₹500/month subscription)
• LangChain Academy (some free, some paid)
• ₹500 OpenAI API credits (real practice)

Yeh max kharcha hai. Free se start karo.

Common galtiyan#

1. Tutorial hell:

• Sirf videos dekhte rehna, code nahi likhna
• Solution: Har video ke baad code likho 30 min

2. Math mein atak jana:

• Linear algebra, calculus deep mein chala jana
• Solution: Math basics enough, focus on building

3. Outdated tutorials:

• 2023 ke tutorials abhi outdated hai
• Solution: 2025-2026 ke tutorials use karo

4. Sirf OpenAI use karna:

• Industry mein Claude, Llama, Gemini bhi use hote hai
• Solution: Multiple models try karo

5. Project complexity wrong:

• Bohot complex (3 mahine wala) ya bohot simple (1 din wala)
• Solution: 3-5 din mein complete ho jaye projects

Salary expectations 2026#

Entry-level GenAI roles (0-2 years GenAI experience):

• IT services: ₹6-10 LPA
• Product startups: ₹12-20 LPA
• Big tech: ₹18-30 LPA
• Foreign clients (remote): ₹15-40 LPA

3+ years GenAI:

• IT services: ₹18-25 LPA
• Product: ₹35-60 LPA
• Big tech: ₹50-1 Cr
• Foreign remote: ₹40 LPA-2 Cr

Demand >> Supply abhi. Achi opportunity hai.

Yaad rakh#

30 din mein expert nahi banoge. Lekin job-ready zaroor ho jaoge entry-level GenAI roles ke liye.

Daily 4-5 ghante consistent put karo. Code likho, theory ya videos pe sirf 30% time.

3 quality projects banao. Live deploy karo. GitHub clean rakho. Resume update karo. Apply karo aggressively.

3-6 mahine mein tumhe pehla GenAI role mil sakta hai agar consistent ho.

JobRise pe GenAI-ready resume banao aur AI engineer ke roop mein nikalo.