Generative AI Course in Pune
Backbenchers Academy’s generative AI course in Pune teaches you to build LLM applications in 3 months: prompt engineering, RAG with vector databases, and AI agents with LangChain and LangGraph. You build real AI projects, practise interviews with mentors and get up to 1 year of placement support.
- LLMs, RAG and AI agents
- 1-to-1 mock interviews
- 620+ learners placed
- 4.9 on Google
Check Your Eligibility
No fee to apply. Only our admissions team sees your details.
What Does a Generative AI Engineer Build?
Most companies do not train their own models. They hire generative AI engineers to connect existing LLMs to their own data and systems. The work includes:
- Designing prompts that return reliable, structured answers
- Building RAG pipelines over company documents
- Creating AI agents that call tools and APIs
- Serving AI features through an API
- Measuring answer quality, cost and response time
How many paid leave days do new joiners get?
Retrieved leave-policy.pdf · section 3
New joiners get 18 days of paid leave in their first year, credited monthly. Source: leave policy, section 3
Generative AI Concepts You Will Learn
The ideas behind every LLM application, explained simply and then put to work in the modules.
- Large language model LLM
- A model trained on large amounts of text that can write, summarise and answer questions.
- Prompt engineering
- Writing clear instructions and examples so a model gives reliable, well-formatted output.
- Embeddings
- Lists of numbers that capture the meaning of text, so similar content can be found quickly.
- Vector database
- A store for embeddings that returns the most relevant chunks of text in milliseconds.
- Retrieval-augmented generation RAG
- Adding retrieved documents to a prompt so answers stay grounded in real, current data.
- AI agent
- A program where the model plans steps and calls tools or APIs to finish a task.
Generative AI Course Syllabus
Eight modules over three months. Every module ends with something you build.
Python for AI
- Syntax, functions and classes
- Reading files and JSON, calling REST APIs
- Packages and virtual environments
- pandas and NumPy basics
Build: A script that calls an API and cleans the response
AI and Machine Learning Fundamentals
- Supervised and unsupervised learning
- Training, testing and overfitting
- Neural networks and how transformers work
- scikit-learn basics
Build: A simple classifier with an evaluation report
LLMs and Prompt Engineering
- Tokens, context windows and temperature
- System prompts, few-shot examples and structured output
- Calling LLM APIs from Python
- Hallucination and safe use
Build: A summariser that returns clean JSON
Embeddings and Vector Databases
- Embeddings and similarity search
- Chunking documents well
- FAISS and Chroma
- Metadata filtering
Build: Semantic search over a document set
Retrieval-Augmented Generation
- RAG pipeline end to end
- Loaders, retrievers and chains in LangChain
- Citing sources in answers
- Measuring answer quality
Build: A document question-answering assistant
AI Agents with LangChain and LangGraph
- Tools and function calling
- LangGraph state, nodes and edges
- Multi-step workflows and memory
- Guardrails for agent behaviour
Build: An agent that plans a task and calls tools
APIs and Deployment
- Building APIs with FastAPI
- Managing API keys and cost
- A simple web front end
- Logging and monitoring
Build: An AI feature served through your own API
Capstone and Interview Preparation
- End-to-end AI project
- GitHub README and demo
- Mock interviews on LLM concepts and system design
Build: A portfolio project you can present
The Generative AI Stack You Will Work With
Each layer builds on the one below it, from Python at the base to the API your users call.
FastAPI
Streamlit
LangChain
LangGraph
- Embeddings
- FAISS
- Chroma
OpenAI API
Claude
Google Gemini
Python
NumPy
pandas
scikit-learn
Git
GitHub
Generative AI Projects You Will Build
Three working applications for your GitHub, each one you can demo in an interview.
Document Q&A Assistant
A RAG assistant that answers questions from a set of PDFs and cites its sources.
- Chunking and embeddings
- Vector search with FAISS or Chroma
- Answers with page references
Python · LangChain · Vector DB · LLM API
Multi-Step AI Agent
An agent that breaks a request into steps, calls tools and APIs, and reports back.
- Tool and function calling
- LangGraph workflow with memory
- Guardrails and fallbacks
Python · LangGraph · APIs
AI Feature as an API
A backend service that exposes summarisation and classification to other apps.
- FastAPI endpoints
- Prompt templates with structured output
- Cost and latency logging
Python · FastAPI · LLM API
Generative AI Jobs You Can Apply For
- Generative AI EngineerBuilds LLM features on company data
- AI EngineerTakes AI prototypes into production
- AI DeveloperAdds AI to web and backend applications
- LLM EngineerDesigns prompts, retrieval and evaluation
- AI / Automation DeveloperAutomates workflows with agents and APIs
Skills employers ask for
- Python
- Prompt engineering
- RAG
- Vector databases
- Embeddings
- LangChain
- LangGraph
- AI agents
- REST APIs
- LLM evaluation
- Git and GitHub
Generative AI Jobs in Pune
AI hiring in Pune spans IT services firms in Hinjewadi, global capability centres in Kharadi and Viman Nagar, and product startups in Baner and Wakad. Backbenchers learners across all three courses have joined employers including TCS, Infosys, Accenture and Capgemini, and placement support also covers openings in other cities and remote teams.
Banks, insurers and manufacturers building internal AI copilots and document assistants.
Teams delivering chatbots, RAG systems and automation for global clients.
Adding AI search, summaries and assistants to existing products.
Small teams building agents and LLM applications from scratch.
What Backbenchers Learners Say
They supported me a lot throughout my placement journey, especially with interview preparation, doubt clearance, and valuable guidance. I’m really happy to share that I got placed with a good package!
The training was practical and easy to understand, and the team supported me with interview preparation and placement guidance. After completing the course and attending interviews, I successfully got a job.
It was one of the life changing experience I had with backbenchers academy. There syllabus and teaching style and interview preparation truly remarkable.
Quoted from the Backbenchers Academy Google Business Profile.
Who Can Join This Generative AI Course?
Any graduate with good communication skills can apply. Freshers, people returning after a break, non-IT workers with a degree and working professionals all fit.
You need
- A graduate degree in any stream
- Good communication skills
- Willingness to write code every day
You don’t need
- Previous AI or machine learning experience
- Advanced maths
- An IT job history
Course Fee and Placement Support
Training takes 3 months. Placement support then continues for up to a year, until you can run your own job search with confidence.
- Resume and job portal profiles
- Help applying for openings
- Technical and HR mock interviews
- AI mock interviews with feedback
- Guidance on real opportunities
- 1-to-1 career mentoring
- Due at enrollment
- ₹0
- Due during training
- ₹0
- Hidden or extra charges
- None
- Placement support
- Up to 1 year
- Program fee
- One fixed amount, due after you are placed
Your exact terms are shared in writing before you enroll.
Generative AI Course in Pune: FAQs
What does the generative AI course in Pune include?
Three months of online training in Python, AI and ML fundamentals, LLMs, prompt engineering, embeddings, vector databases, RAG and AI agents with LangChain and LangGraph, real-world AI projects, mock interviews and up to 1 year of placement support.
How long is the generative AI course in Pune?
Three months of hands-on training, then up to a year of placement support.
Who is eligible?
Any graduate with good communication skills, from any stream. You can apply as a fresher, after a career gap, from a non-IT job or while you are working.
Do I need to know how to code before joining?
No. Python is taught from the basics in Month 1, and the screening call checks that you are ready to write code daily.
Do I need to know machine learning first?
No. Module 2 covers the machine learning and transformer basics you need before working with LLMs.
Does the course cover RAG and AI agents?
Yes. Month 2 covers embeddings, vector databases and RAG, and Month 3 covers AI agents with LangChain and LangGraph.
Which tools and LLMs will I use?
Python, LLM APIs such as OpenAI, Claude and Gemini, LangChain, LangGraph, FAISS or Chroma for vector search, FastAPI, Git and GitHub.
How does the fee work?
There is no fee at enrollment or during training. A single fixed program fee falls due only after you are placed, with no hidden charges, and your terms are given to you in writing first.
Is the course online?
Yes. Classes are online and self-paced, with mentor sessions and mock interviews held online.
What jobs can I apply for?
Generative AI Engineer, AI Engineer, AI Developer, LLM Engineer and AI or Automation Developer roles.
Is there a certificate at the end?
Yes. You receive a Backbenchers Academy course completion certificate, which is not a university degree.
Is generative AI a good career choice in Pune?
Companies across Pune, from capability centres to startups, are adding AI features to their products and internal tools, so engineers who can build reliable LLM applications are in steady demand.
Gen AI guides
Generative AI Articles for Beginners
Plain-language explainers on LLMs, RAG and AI agents, plus interview and resume advice.
What Is RAG? Retrieval-Augmented Generation Explained for Beginners
Retrieval-Augmented Generation (RAG) lets an LLM answer questions using your own documents. Learn how it works step by step, its key components,…
How to Prepare for a Technical Interview as a Fresher: A Step-by-Step Plan
A practical, step-by-step plan for freshers preparing for technical interviews: what to revise for your role, how to talk about projects, the…
How to Write an ATS-Friendly Resume for Tech Jobs (With a Checklist)
Learn what an Applicant Tracking System (ATS) really does, how to format and structure a tech resume so it is read correctly,…
Start the Generative AI Course in Pune
Check your eligibility in a few minutes. Learn to build the LLM, RAG and agent applications Pune companies are hiring for and, if you are eligible, pay nothing until you are placed.
Also see: Data Engineering • Software Testing • Interview Preparation