Why this track works
Learn only what Gen AI interviews actually ask.
13 chapters, 60–90 minutes each. Every concept starts with a real-world problem — the kind production code throws at you. No wall of theory, no textbook topics the industry never touches. Learn → test yourself → take an AI mock → fix your weak spots.
- 📖LearnConcept + real-world problem, 60–90 min
- 🧠RememberModel answers + flashcards
- 🤖PractiseAI mock + weak-topic report
The difference isn’t the content — it’s the filter. Only what’s actually used in production and actually asked in interviews. Textbook topics the industry never touches don’t make the cut.
Certificates
Finish the Gen AI track. Get certified.
Every Gen AI chapter you complete earns a certificate with your name on it, issued instantly. Finish all 13 chapters and you earn the Gen AI Stack Mastery certificate. No exam, no waiting.
Chapter certificate
One for each of the 13 Gen AI chapters you complete.
Stack Mastery certificate
Complete all 13 chapters for the Gen AI Stack Mastery certificate.
Anyone can verify it
Each certificate has a QR code and a public link at hirenix.in/verify.
Verified credential
hirenix.in/verify/…
Python for AI
PyWhy Python for AI? · Python syntax basics · Functions & modules · Data structures · Working with JSON
13 topics · 149 questions
View Python for AI questionsLLM Foundations
LLMLLM basics · Prompt engineering · System prompts · Advanced prompting · OpenAI SDK
12 topics · 156 questions
View LLM Foundations questionsEmbeddings & Vector DB
VecWhat are embeddings? · Embeddings API · Similarity search · ChromaDB · Pinecone
10 topics · 110 questions
View Embeddings & Vector DB questionsRAG (Retrieval Augmented Generation)
RAGWhat is RAG? · RAG vs fine-tuning · Document loaders · Text splitting & chunking · Retrieval strategies
13 topics · 158 questions
View RAG (Retrieval Augmented Generation) questionsFunction Calling & Tools
ToolsWhat is function calling? · Tool definitions (JSON Schema) · The tool-call loop · Parallel tool calls · Real-world tools
13 topics · 155 questions
View Function Calling & Tools questionsLangChain & LangGraph
FrameworkWhat is LangChain? · RAG with LangChain · Tools with @tool · LangGraph basics: StateGraph · LangGraph agents
13 topics · 145 questions
View LangChain & LangGraph questionsMemory Management
MemoryWhat is memory? · Buffer memory · Summary memory · Vector store memory · Checkpointers: short-term memory
13 topics · 159 questions
View Memory Management questionsFine-Tuning
Fine-TuneWhat is fine-tuning? · When to fine-tune (and when not to) · Dataset preparation (JSONL) · Data quality and validation · The hosted fine-tuning API
13 topics · 158 questions
View Fine-Tuning questionsGuardrails & Safety
GuardrailsWhat are guardrails? · Prompt injection · Input validation and blocklists · Detecting injection with a classifier · Hardening the system prompt
17 topics · 206 questions
View Guardrails & Safety questionsFull-Stack AI
StackFrom script to product · FastAPI basics · async def vs def: blocking the server · Streaming responses with SSE · Streaming UI in React
17 topics · 208 questions
View Full-Stack AI questionsAI Deployment & MLOps
DeployFrom laptop to production · Containerizing an AI app · Serverless vs container · The local stack with Compose · Config and secrets
19 topics · 242 questions
View AI Deployment & MLOps questionsImage & Video Generation
MediaHow image models actually work · Prompting for images · Calling an image API · Sizes, formats and web delivery · Seeds and reproducibility
19 topics · 232 questions
View Image & Video Generation questionsMCP — Model Context Protocol
ProtocolWhy MCP exists · MCP vs function calling · Host, client and server · Your first MCP server · Tools in depth
19 topics · 231 questions
View MCP — Model Context Protocol questions