LLM Application Development Course in FaridabadFrom API key
to AI product.
In this course you will ship a structured data extractor
The LLM application development course for people who want to build real AI products in code: LLM APIs, structured outputs, tool calling, RAG, agents, evals and deployment. 8 modules, a capstone and 6 deployed apps, in our Sector 81 classroom or live online.
- Free demo class
- 8 modules
- 6 deployed apps
- Python and APIs
- Sector 81 or online
- Installments
- 4.8 ★from 98 Google reviews
- 25,000+students trained at AdifySkills
- Sector 81Faridabad classroom
- Live onlinesame trainer, same projects
- 6 appsdeployed online
What is LLM application development, in plain words
LLM application development means building software that uses large language models, the models behind ChatGPT, Claude and Gemini, as one part of a real product. Instead of chatting in a browser, your code sends requests to a model API, gets structured results back and uses them inside an app.
A real LLM app is much more than a prompt. It needs clean inputs, structured outputs, tools the model can call, often a knowledge base for RAG, safety checks, tests called evals, logging, cost control and a way to deploy it for users.
This LLM application development course in Faridabad teaches you to build all of that in Python, step by step, and to ship apps that real people can use.
Simple Hinglish mein: ChatGPT use karna ek cheez hai, ChatGPT jaisa apna app banana doosri. Yeh course doosri cheez sikhata hai.
This is a developer course. Basic Python helps a lot. If you are new to code, module 1 gives you a fast Python refresher, and our Generative AI or vibe coding courses are a gentler start.
Why learn LLM application development in 2026
Companies want AI features inside their own products and tools, not just chat subscriptions. Developers who can build them reliably are in demand.
Every product is adding AI
Search, support, writing help and data extraction are now expected features in software.
APIs make it possible
Model APIs from OpenAI, Anthropic and Google let you add strong AI to any app.
Reliability is the hard part
Anyone can call an API. Few can make the output structured, tested and safe. That is the skill.
Works with your code skills
If you know some Python or JavaScript, LLM skills multiply what you can build.
Startup and freelance ready
Small teams now build AI products that used to need large companies.
Foundation for agents
LLM app skills lead straight into agents, MCP and advanced AI systems.
Sound familiar?
If any of this sounds familiar, this course was made for you.
- Your AI prototype works in a notebook but not as a real app
- The model returns text when you needed clean JSON
- Your RAG app gives wrong or uncited answers
- You do not know how to test whether a prompt change made things better or worse
- API costs and response times surprise you
- You worry about prompt injection and leaking API keys
Who joins this LLM application development course
Basic Python or JavaScript is expected. You do not need machine learning or maths background.
Software developers
Developers who want to add LLM features to products and switch into AI roles.
CS and IT students
Students who want a strong, practical AI portfolio before placements.
Data and analytics people
Analysts who code and want to build AI tools for their teams.
Technical founders
Founders who want to build and ship their own AI product.
Who should not join
We would rather tell you now than after you pay.
- You have never written any code and do not want to. Try our Generative AI or AI Automation courses instead.
- You want to train models from scratch. This course is about building apps with existing models.
- You expect a guaranteed job or fixed income. We give placement support, not promises.
- You cannot practise at least 6 to 8 hours a week outside class.
After this course, you will be able to
Each skill is proven by a project in your portfolio, not by a quiz.
- Call LLM APIs from OpenAI, Anthropic and Google in Python
- Get reliable structured outputs with JSON schemas and Pydantic
- Use tool calling so models can run your functions
- Build RAG pipelines with embeddings, vector databases and citations
- Build simple agents and connect them to tools through MCP
- Create a FastAPI backend and a simple frontend for your app
- Write evals to measure quality and catch regressions
- Add logging, tracing and cost tracking
- Protect apps from prompt injection and keep secrets safe
- Deploy apps to the cloud and run open models locally
The course at a glance
| Course | LLM Application Development Course, build and deploy LLM apps in Python |
| Structure | 8 modules plus a capstone project |
| Mode | Classroom at Sector 81, Faridabad, or live online. Weekday and weekend batches |
| Fee | Shared on call or at the free demo class, with an installment option |
| Language | Hinglish, with English notes and project files |
| Level | Intermediate to Advanced |
| You build | 6 deployed apps with code on GitHub |
| You get | AdifySkills certificate, project files, placement and freelancing support |
| Before paying | Free demo class |
Your learning path, step by step
Five stages, from your first API call to a deployed, tested product.
Foundations
Python, APIs and prompts in code.
Modules 1 and 2Reliable output
Structured data and tool calling.
Module 3Knowledge
RAG and agents.
Modules 4 and 5Product
Backends, frontends and evals.
Modules 6 and 7Ship
Security, deployment and capstone.
Module 8 and capstoneFull LLM Application Development course curriculum: 8 modules and a capstone
Open any module to see every topic and what you build in it. Each topic is something you will use on a real project.
01Python and LLM basics for buildersSetting up and thinking like an AI engineer
Basic
Topics
- Python refresher: functions, classes, packages and virtual environments
- How LLMs work: tokens, context windows, temperature
- Model families and choosing a model for a task
- API keys, environment variables and safe setup
- Your first API call to OpenAI, Claude and Gemini
- Git and GitHub for your projects
You build
A command-line tool that summarises any text file with an LLM.02Prompts as codePrompt engineering for applications
Basic
Topics
- System, user and assistant messages
- Prompt templates and variables
- Few-shot examples stored with your code
- Streaming responses to users
- Handling errors, timeouts and retries
- Comparing models on the same prompt
You build
A prompt test harness that compares three models on ten inputs.03Structured outputs and tool callingMaking models reliable
Intermediate
Topics
- JSON mode and structured outputs with schemas
- Validation with Pydantic
- Tool calling: letting the model run your functions
- Parallel and multi-step tool calls
- Data extraction from emails, PDFs and forms
- When to use code instead of the model
You build
An invoice and resume extractor that returns validated JSON.04RAG in codeAnswers grounded in your documents
Intermediate
Topics
- Embeddings and similarity search
- Chunking strategies and metadata
- Vector databases: pgvector, Chroma and Qdrant
- LangChain and LlamaIndex, and when to skip them
- Hybrid search and reranking
- Citations and refusing to answer without sources
You build
A document Q and A app with citations.05Agents and MCPFrom single calls to systems that act
Advanced
Topics
- The agent loop in code
- Agent SDKs and LangGraph basics
- Memory and state
- Model Context Protocol: building and using MCP servers
- Human-in-the-loop approvals
- When agents are overkill
You build
A support triage agent with three tools and an MCP server.06Building the productBackends, frontends and data
Advanced
Topics
- FastAPI backends for LLM features
- Streamlit and simple React or Next.js frontends
- Auth, users and rate limits
- Storing chats and results in Postgres
- Background jobs for long tasks
- Caching to save time and money
You build
A full web app with login, history and an LLM feature.07Evals and observabilityProving your app works
Advanced
Topics
- Why evals matter more than vibes
- Building test sets from real data
- Automatic checks and LLM-as-judge scoring
- Regression testing when prompts or models change
- Tracing, logging and cost dashboards
- Latency and cost optimisation
You build
An eval suite and dashboard for your RAG app.08Security and deploymentShipping safely
Advanced
Topics
- Prompt injection and data leaks
- Guardrails and content filters
- Secrets, keys and least-privilege access
- Docker basics and deploying to Render, Railway or a VPS
- Running open models with Ollama
- Fine-tuning: when it helps and when it does not
You build
A deployed, secured app with a live URL.09Capstone: ship an LLM productPlan, build, test and present
Advanced
Topics
- Pick a real problem and users
- Design the architecture and data flow
- Build, evaluate and deploy
- Write a README and demo video
- Present results, costs and risks to your trainer
You build
A deployed LLM application with evals, docs and code on GitHub.LLM development tools you will use
Grouped by job. Tools change fast, so we update the list before every batch and teach the ideas that work across all of them.
Model APIs
The models behind your app.
- OpenAI API
- Anthropic Claude API
- Google Gemini API
Python stack
Core libraries.
- Python
- Pydantic
- FastAPI
- httpx
RAG and agents
Knowledge and actions.
- LangChain
- LlamaIndex
- LangGraph
- MCP
Data
Store and search.
- Postgres
- pgvector
- Chroma
- Qdrant
Frontends
User interfaces.
- Streamlit
- Next.js
Ship and observe
Deploy and monitor.
- Docker
- GitHub
- Render
- LangSmith
- Ollama
Tool names are trademarks of their owners. AdifySkills is not affiliated with any of these companies.
How an LLM app handles one request
Every app in this course is built around this path, with tests at the end. Press the button to run it again.
6 projects you build in this course
Real briefs for real kinds of clients. Each one is reviewed by your trainer before it goes into your portfolio.
Text summariser CLI
Validated data extractor
Document Q and A with citations
Support triage agent with MCP
Full web app with history
Capstone: deployed LLM product
How every class works
Every session follows the same rhythm, so you always leave with something built, not just notes.
See it
The trainer explains one idea and shows it live, mistakes included.
Build it
You build the same thing yourself, in class, with help on hand.
Get feedback
Your work is reviewed on screen: what works, what to fix and why.
Practise it
A short assignment for the week, plus files and notes to keep.
Careers and earning options after the course
Outcomes depend on your effort and the market. These are the paths this training prepares you for.
AI engineer
Build LLM features and AI products for companies and startups.
Backend developer with AI skills
Add AI features to existing backends and APIs.
RAG and search engineer
Build retrieval systems and knowledge assistants.
AI product prototyper
Turn ideas into working AI prototypes quickly.
Freelance AI developer
Build custom AI tools for businesses and agencies.
Founder
Build and launch your own AI product.
Certificate, plus a portfolio that proves your skill
A certificate says you attended. Working projects say you can do the job. You get both.
- AdifySkills certificate of completion for the LLM Application Development Course
- 6 documented portfolio projects
- Templates, prompts and project files you can reuse
- Letter of recommendation for strong performers
Learn from Charanjeet Singh
Founder and lead trainer at AdifySkills, with 10+ years of training experience and real client campaigns behind every lesson.
Charanjeet builds AI tools, automations and web projects for real clients, and works with LLM APIs daily. He teaches the way he works: explain the idea, show it live, let you build it, then review it honestly.
Students on Google mention his teaching style and real-time examples more than anything else. You will know who is teaching your batch before you pay, not after.
Meet him in a free demo classWhat our students say on Google
Unedited reviews from our Google Business Profile. AdifySkills was earlier known as Digital Charanjeet Academy, the name some reviewers use. This is a new course, so these reviews are from our other courses.
I joined a digital marketing course from Faridabad and at the beginning I wasn’t sure if I would be able to learn it. But the classes were very practical and interactive, which made the concepts easy to understand. Gradually my confidence improved, and after completing the course I also got a placement. Overall, it was a really good learning experience.
I have successfully completed my Digital Marketing course, and the overall journey has been truly amazing. I got the opportunity to learn from Charanjeet Sir, whose teaching style, real-time examples, practical insights, and deep industry experience make every concept extremely easy to understand. Whether you prefer online digital marketing classes or offline digital marketing training, this academy provides a smooth and valuable learning experience for everyone.
I’m currently doing the Digital Marketing course at Digital Charanjeet Academy, and honestly, the experience is really valuable. Yaha ka curriculum well-structured hai, teaching practical hai, aur faculty bahut supportive hai. Classroom environment bhi professional hai, aur management doubts aur guidance mein hamesha help karta hai.
I started my learning journey 4 months ago but I was also sceptical that how will I be able to learn everything online as I live preet vihar and the coaching was in Faridabad...but with the help of their online portal I was easier also... special thanks to Charanjeet sir...great person ❤️
Digital Charanjeet Academy offers the best digital marketing course in Faridabad. Trainers are professional and very supportive. Highly recommended digital marketing course for beginners and professionals.
98 reviews on Google
Read every review, good and bad, before you decide.
Read reviews on GoogleRecognised for practical training
AdifySkills has been recognised by Manav Rachna University and IFA for excellence in digital marketing training. What earned it is the same thing you get in this batch: practical teaching and honest feedback.
Classroom in Sector 81, or live online
Our centre is at Office No. D003, Ground Floor, Puri High Street, Sector 81, Faridabad, with parking and ground floor access. Learners join from Old Faridabad, NIT, Sector 15, Ballabgarh, Greater Faridabad and across Delhi NCR.
Online batches are live, not recorded: same trainer, same assignments, same review sessions. Recordings are there for revision.
Getting here
- Puri High Street, Sector 81, Greater Faridabad
- Easy from Ballabgarh, Neharpar and the Sector 80s
- Parking available, ground floor access
- Call before you visit: +91 8383891716
LLM Application Development Course fee
We share the fee on call or at your free demo class, after we understand your goal. Same fee for classroom and online.
- 8 modules and a capstone, with live classes
- 6 portfolio projects with trainer review
- Templates, notes and project files to keep
- Certificate of completion
- Placement and freelancing support
- Installment option, ask your counsellor for the plan
Fee shared on call or at the demo. Paid tool or API plans, if you choose any, are separate.
- Classroom or live online
- Weekday or weekend batch
- Installments available
Upcoming batches
Small batches fill quickly. Book a demo to hold your seat in the batch you want.
| Batch | Days | Mode | Next start date |
|---|---|---|---|
| Weekday | Monday to Friday | Classroom, Sector 81 | Ask on call or WhatsApp |
| Weekend | Saturday and Sunday | Classroom, Sector 81 | Ask on call or WhatsApp |
| Online live | Weekday or weekend | Live online | Ask on call or WhatsApp |
Call or WhatsApp +91 8383891716 for the next start date and timings.
LLM Application Development course in Faridabad: common questions
What is the fee for the LLM Application Development course in Faridabad?
We share the fee on call or at the free demo class. It is the same for classroom and online batches, and an installment option is available. Paid tool or API plans, if you choose any, are separate.
Do I need to know Python?
Basic Python or JavaScript is expected. Module 1 includes a fast Python refresher for the parts you need.
Do I need machine learning or maths knowledge?
No. This course is about building apps with existing models, not training models from scratch.
How is this different from the AI agents course?
The AI agents course has a no-code main track. This course is fully code-based and covers the whole product: APIs, data, evals, security and deployment.
Which models will we use?
OpenAI, Anthropic Claude and Google Gemini APIs, plus open models through Ollama. You learn to switch between them.
Will I pay for API usage?
Practice costs are usually small, and we show free credits and cheap models. API costs are paid directly to the provider.
Will my projects be on GitHub?
Yes. Every project is pushed to GitHub with a README, so you can show it to employers or clients.
What is an eval?
An eval is a test that checks if your AI app gives good answers on a set of examples. It tells you if a change made the app better or worse.
Can I build my own AI startup after this?
You will have the skills to build and deploy a working AI product. Business success depends on many things beyond code.
Is the online batch live or recorded?
Live, with the same trainer, projects and reviews as the classroom batch. Recordings are available for revision.
Ship your first LLM app in a free class
Book the free demo, watch an LLM app go from API key to working feature, and decide for yourself. If it is not for you, you pay nothing.
- Free demo class
- Classroom at Sector 81 or live online
- Fee shared on call, installment option
- Certificate, portfolio and career support
Reserve your free demo seat
Leave your number. We call within working hours.
Fee shared on call, with an installment option. We never share your number.