Containerised API Service
A FastAPI service backed by Postgres, typed and tested, shipped in Docker with CI running on every push.
- Python
- FastAPI
- Docker
- GitHub Actions
Best After 12th 3-Month Agentic AI Program in Phagwara
Rated on Google4.9556+ reviews
Three months that take you from your first line of Python to an autonomous agent running in public, with citations, guardrails and a cost-per-conversation figure behind it. No programming experience needed.
Agentic AI Course in Phagwara
A language model answers a question. An agent decides what to do next — it plans, calls real tools, reads what came back, and repeats until the goal is met. This 3-month course teaches you to build, test and deploy these AI agents from scratch.
Key Highlights
- Duration:
- 3 Months
- Eligibility:
- 12th Pass (Any Stream)
- Mode:
- Classroom, Weekend & 1-on-1
- Includes:
- Certificate + Placement Support
Overview
Course overview
A language model answers a question. An agent decides what to do next — it plans, calls real tools, reads what came back, and repeats until the goal is met. This 3-month course teaches you to build, test and deploy these AI agents from scratch. The course starts from the very basics — Python, the command line, Git, HTTP and databases — so no prior coding experience is needed. Once the foundations are clear, you move straight into agent engineering: prompting, tool calling, retrieval, memory and deployment. Every topic ends with a project you actually build.
What You’ll Learn
Every module ends in something you have built and a trainer has reviewed, so the list below is work you will have done rather than topics you will have heard about.
- 01
Strong foundations first
Python, Git, HTTP and SQL before a single prompt
- 02
Write the reason-act-observe loop by hand, so a framework is readable rather than magic
- 03
Build cited RAG graded on RAGAS faithfulness and context precision against a gold set
- 04
Manage memory, multi-user isolation and checkpointed state across sessions
- 05
Add guardrails against prompt injection, with PII filtering and escalation policies
- 06
Deploy a publicly reachable agent gated by an eval suite in CI, with a cost-per-conversation figure
SyllabusHands-on
Course Curriculum
The syllabus is arranged so every module produces an asset rather than a set of notes. You will cover month 1 — foundations: python, llm prompting & tool calling, month 2 — rag, memory & agent frameworks, month 3 — evaluation, guardrails, deployment & capstone, and finish with a live project built on Python, Git & GitHub, FastAPI. Modules run in the order a real project runs: foundations first, then the core skills, then applied work under supervision, then the portfolio and interview preparation that turn all of it into an offer letter.
Agentic AI02/03
Core Skills
The working knowledge the job description actually lists.
Month 2 — RAG, Memory & Agent Frameworks
Grounding answers in real documents, carrying state across sessions, and reading what a framework does for you.
4 weeks · 24 sessions
Topics covered
Retrieval-Augmented Generation: embeddings, vector search, chunking strategiesDocument parsing for PDFs and tablesVector stores (Qdrant, Chroma, FAISS); hybrid search combining keyword and dense vectorsReranking and citation; RAG quality measurement — faithfulness and context precisionWhen to use RAG vs fine-tuningMemory and state: short-term, long-term and episodic memoryConversation buffers, summarisation and context engineeringMulti-user isolation, PII handling and privacy; state persistence and checkpointingLangGraph: nodes, edges, conditional routing, cycles and subgraphs; typed state and streamingHuman-in-the-loop: approval gates, time-travel debugging, durable execution and resumabilityMulti-agent patterns: supervisor and worker roles, the handoff pattern, termination conditions
The toolchain
Tools you will actually work in
Everything below is installed on the lab machines and used on live client work, not shown once in a slide and forgotten.
- Python
- Git & GitHub
- FastAPI
- PostgreSQL
- Docker
- Claude API & OpenAI API
- Pydantic & Instructor
- MCP SDK
- LangChain & LlamaIndex
- LangGraph
- Qdrant, Chroma & FAISS
- RAGAS & promptfoo
- LangSmith & Langfuse
- Guardrails AI & Presidio
- Streamlit
- GitHub Actions
Eligibility
Who can do this course
- 01
Students straight after 12th
Join from any stream. There is no assumed technical knowledge and no programming prerequisite. Most students run the programme alongside a degree at a Phagwara college using the weekday or weekend batch.
- 02
Graduates and final-year students
If you are finishing a BCA, B.Sc, BBA or B.Tech, this is the shortest route from degree to an AI automation role. You enter placement season with a deployed agent and an evaluation report instead of a blank CV.
- 03
Career changers
The weekend batch exists for people already earning. Three months is enough to become interview-ready for AI Automation Engineer and Agentic AI Developer roles without leaving your current job.
- 04
Developers and analysts
If you already write code or work with data, the foundations part is revision and the pace picks up quickly. What changes your title is the part most self-taught developers skip — evaluation, guardrails and cost.
The case for itWhy this programme
Why this programme
is worth your year
Someone has to decide which problems need an agent, wire the tools so they cannot be misused, ground the answers in real documents, and prove the whole thing works with numbers before it touches a customer — and almost nobody in this market can do all four. That gap is the whole argument for this course: there is local demand, there are budgets, and there are very few trained people to hand the work to.
Build skills that hold up beyond the classroom.
What separates this from a playlist of tutorials is supervision on real work. From the second half of the course you build on live client projects with a trainer beside you, make decisions that have consequences, and correct them the following week. That loop is the skill. No employer in Phagwara will take your word for it without work they can inspect.
Be realistic about the money. A fresher who finishes with a working portfolio starts near the bottom of the band and moves quickly; someone who finishes with a certificate and nothing to show does not. The difference is entirely what you built.
The alternative is what most people try first: free videos, a cheap online course, six months of drifting, and knowledge you cannot demonstrate. A structured programme with live projects, a mentor who corrects you, an internship letter and a placement cell that actually calls employers is the difference between knowing the subject and being hired to do it.
Students reach the Phagwara centre from Banga, Nakodar, Kartarpur and the university belt, and the weekend batch exists so a job or a degree does not have to be paused to attend.
- 01
Foundations before frameworks
The course starts with Python, Git, HTTP and SQL. Every agent pattern after that is something you can reason about rather than copy, because you already understand the request, the schema and the commit graph underneath it.
- 02
The loop, written by hand
You build the ReAct loop from scratch before using any framework. When frameworks like LangGraph arrive later, you can read what they are doing — which is the difference between using a tool and being trapped by it.
- 03
Evidence is the deliverable
Anyone can demo an agent that works once. A labelled evaluation set, a measured before-and-after and a cost-per-task number are what actually get people hired.
- 04
A ladder, not a dead end
This 3-month course is the foundation of the 6-month and 9-month tracks. Nothing is removed when you extend later; the next track begins exactly where this one ends, so you never restart.
Why now
An Agent Decides. A Chatbot Only Answers.
- An agent is goal-directed — you give it an outcome rather than a script; it uses tools, reaching outside the model to APIs, databases, browsers and code.
- It has memory, carrying state across steps and sessions, and autonomy, running its own loop within the budgets and approval gates you set.
- That is why the job exists: someone has to decide which problems need an agent, wire the tools so they cannot be misused, ground the answers in real documents, and prove it works with numbers before it touches a customer.
- A fresher with a deployed agent and an evaluation report typically starts around ₹20,000 – ₹40,000 per month in the Phagwara, Jalandhar and Ludhiana market.
Certification
Get Certified in Agentic AI
Complete the course with a portfolio of live projects and receive an industry-recognised certificate, plus a documented internship letter accepted by Punjab universities.
- Industry Certificate
Recognised by employers across Punjab and beyond
- Internship Letter
Based on real client work, not a simulation
- Portfolio of Projects
Live work you can show in any interview
- Placement Support
CV review, mock interviews and hiring drives
Two certificates on completion — the course certificate and a separate capstone project certificate.
Future scope
Where this course takes you
The roles this opens, what they pay in Punjab and beyond, and who is hiring for them — drawn from published job-market listings, not a brochure number.
Entry level, and the most common first destination after this course. Interviews test whether you can wire tools reliably, handle failures gracefully and show a working deployed demo. Show the MCP server, the cited RAG assistant and the deployed capstone.
Early career. Interviews test framework fluency, RAG quality debugging and human-in-the-loop design. Show the approval-gated graph agent, the extraction engine and the eval CI gate.
The role that sits between the customer and the build. You demonstrate agents, scope what is feasible and prototype it — which is exactly the shape of the six projects you build here.
Day-two work on a live agent: reading traces, triaging failed tool calls, curating evaluation sets from real traffic and escalating what the guardrails caught. Every one of those skills is covered in this course.
- 05RAG / Retrieval Engineer
- 06Freelance AI Consultant
Salary outlook — AI Automation Engineer
Builds, evaluates and deploys agents that take real actions. Agent work carries more remote and freelance opportunity than most fields, since the systems are not in the room.
- Starting
- ₹20,000–₹40,000/month
- After 2 years
- ₹45,000–₹90,000/month
Indicative ranges compiled from public job-market listings. Actual offers vary by employer, skillset and interview performance.
Who is hiring for this
- Product startups putting agents and assistants into their software
- IT services companies adding AI automation to client delivery
- Agencies and consultancies building internal copilots for business clients
- Remote roles, which are unusually available because the systems are not in the room
Portfolio
Hands-on projects you will ship
Document Extraction Engine
Unstructured invoices and contracts converted into schema-valid JSON with under 2% validation failure across 100 documents.
- Pydantic
- Instructor
- promptfoo
Published MCP Server
Five or more scoped tools with full schema documentation, integration tests and a hand-written ReAct loop that uses them without a framework.
- MCP SDK
- FastAPI
- Tenacity
Cited Compliance Copilot
A hybrid-search RAG assistant with clause-level citations, scoring 0.85+ faithfulness on a 50-question gold set.
- LlamaIndex
- Qdrant
- RAGAS
Human-in-the-Loop Approval Agent
A stateful graph agent that pauses for sign-off, streams every step, and resumes cleanly after a crash.
- LangGraph
- Checkpointers
- SSE
Deployed Support Agent (Capstone)
A publicly reachable capstone with CRM write-back, human escalation, a CI regression gate and a cost-per-conversation figure.
- LangGraph
- Streamlit
- Railway
- Sentry
The working loop
Learn it. Build it. Make it yours.
Every project moves through the same loop: understand the brief, build with guidance, then explain the decisions behind your work.
- 01
Understand
Take a real requirement apart before touching a tool — what is being asked, what it needs, and which part to build first.
Containerised API Service
- 02
Build
Work hands-on with your trainer watching the screen, so a wrong turn is caught in the same session rather than three weeks later.
Document Extraction Engine
- 03
Present
Walk through what you built and why you built it that way. This is the interview rehearsal, run against every project rather than once at the end.
Published MCP Server
Why techcadd
Why students choose techcadd
There are many places to learn this in Phagwara and the brochure syllabus looks similar at all of them. What differs is who teaches, whether you ever touch real work, and whether anyone picks up the phone after you have paid. techcadd has trained students across Punjab since 2007 on the same model: small batches, working practitioners as trainers, client projects as coursework.
Progress by skill, not by date
You advance when a deliverable passes review. A student who needs extra time on retrieval gets it; nobody is moved on just because the timetable says so.
Real model APIs, with budgets
Labs run against live Claude, OpenAI and Gemini endpoints with per-student token budgets and cost dashboards — so the cost awareness is something you have felt, not just read about.
Trainers who still ship
The people teaching MCP servers and LangGraph checkpointing are the people writing them for client work, which is why the failure sections cover failures that actually happen.
A ladder you can extend
Finish here with a certificate and a deployed capstone, or continue into the six- and nine-month tracks later. The next track starts where this one ended — you never repeat what you have already passed.
FAQs
Frequently asked questions
Find answers to the questions students ask before enrolling.
Three months, divided into three clear blocks — foundations, frameworks and deployment. Weekday, evening and weekend batches cover the same syllabus, and 1-on-1 training is available if you would rather set your own pace. Every class runs for 2 hours, whichever format you choose.
Course information
Ask about Agentic AI
Send your question and a counsellor will call you back about batch timings, fees, EMI options, placement record, or whether this course fits your degree.
- Free counselling and demo class
- Weekday, evening, weekend or 1-on-1, all 2-hour classes
- Internship letter and placement support
Get started today
Not sure if Agentic AI is the right fit?
One call with a counsellor is usually enough to find out. Book a free demo class and see the lab before you decide.