Best After 12th 3-Month Agentic AI Program in Jalandhar
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 Program Course in Jalandhar
Enrol in the 3-Month Agentic AI program after 12th at techcadd Jalandhar (4.9★, 556+ reviews). Learn Python, Git, LLM prompting, tool calling, MCP servers, RAG with citations, memory, agent orchestration and deploy a real AI agent. No programming background required.
Key Highlights :
- Duration: 3 Months
- Mode: Practical + Theory
- Eligibility: 12th Pass, Any Stream
- Includes: Certificate + Placement Support
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. Once the basics are solid, every session is agent engineering — which is only possible because the foundation is real.
- 02
ReAct written by hand before any framework
You build the reason-act-observe loop from scratch first. When LangGraph arrives later you can already read what it is doing for you.
- 03
Citations that a reviewer can check
The RAG section is graded on RAGAS faithfulness and context precision against a 50-question gold set, not on whether the answer sounded right.
- 04
A capstone that is publicly reachable
The final month deploys the agent, gates it behind an eval suite in CI, and puts a cost-per-conversation number next to it — the three things an interviewer actually asks about.
Course Curriculum
The course is divided into three months. Each month builds on the previous one, moving from basics to deploying a real AI agent.
Month 1 — Foundations: Python, LLM Prompting & Tool Calling
- 1
Python from scratch — syntax, variables, data structures, loops, functions, classes, type hints, async/await; virtual environments with uv and pip.
- 2
Command line, Git and GitHub — navigation, commits, branches, pull requests and .gitignore.
- 3
HTTP, REST APIs, JSON, API keys and bearer tokens; SQL basics with PostgreSQL; Docker and containerisation.
- 4
LLM fundamentals — how transformers work (intuition, no heavy maths), tokens, context windows, temperature; system, user and assistant roles.
- 5
The four properties of an agent — goal-directedness, tool use, memory and autonomy; when NOT to use an agent.
- 6
Prompting techniques — few-shot, chain-of-thought, structured output with JSON schema and Pydantic validation.
- 7
Tool calling — writing tool descriptions, parameter schemas, the ReAct loop built from scratch without any framework.
- 8
Model Context Protocol (MCP) — servers, clients, resources and transports; wrapping a REST API as tools.
- 9
Tools covered: Python · Git · GitHub · FastAPI · PostgreSQL · Docker · Claude API · OpenAI API · Pydantic · MCP SDK
- 10
Projects: Containerised API service + model comparison notebook + published MCP server with 5+ tools and a hand-written ReAct loop.
Tools you will actually work in
Everything here is installed on the lab machines and used on live client work, not shown once in a slide and forgotten.
- GPTLLChFA
Who can do this course
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 Jalandhar college using the weekday or weekend batch.
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.
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.
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.
Why this programme is worth your year
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.
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.
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.
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.
Automate. Assist. Achieve.
- An agent is defined by four properties: it is goal-directed, so 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 it has 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 the whole thing works with numbers before it touches a customer.
Get certified in Agentic AI Program
Complete the course with a portfolio of live projects and receive an industry-recognised certificate, plus a documented internship letter accepted by Punjab universities.
Computer Education · JalandharCertificateof Project ExcellenceThis is to certify thatStudent Namehas designed, built and deployed a live capstone project in Agentic AI Program, reviewed and graded under industry mentorship.
Computer Education · JalandharCertificateof Course CompletionThis is to certify thatStudent Namehas successfully completed the professional training programme in Agentic AI Program with a grade of A+.
Two certificates on completion — the course certificate and a separate capstone project certificate.
Where this course takes you
The roles this opens, what they pay in Punjab and beyond, and who is hiring for them — the same figures our free Salary Estimator publishes, 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 in this course.
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.
Hands-on projects you will ship
Containerised API Service
A FastAPI service backed by Postgres, typed and tested, shipped in Docker with CI running on every push.
Document Extraction Engine
Unstructured invoices and contracts converted into schema-valid JSON with under 2% validation failure across 100 documents.
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.
Cited Compliance Copilot
Hybrid-search RAG assistant with clause-level citations, scoring 0.85+ faithfulness on a 50-question gold set.
Human-in-the-Loop Approval Agent
A stateful graph agent that pauses for underwriter sign-off, streams every step, and resumes cleanly after a crash.
Deployed Support Agent
Publicly reachable capstone with CRM write-back, human escalation, a CI regression gate and a cost-per-conversation figure.
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.
Understand
Break a real requirement into a clear plan and the right tools.
Containerised API ServiceBuild
Work hands-on with trainer feedback while the decisions are still easy to change.
Document Extraction EnginePresent
Turn the finished work into a portfolio story you can defend in an interview.
Published MCP ServerWhy students choose techcadd
Nine campuses across Punjab, 4.9★ from 556+ reviews, and a syllabus that is republished each year rather than reprinted.
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.
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.
No. The course begins with Python taught from the first line, alongside the command line, Git, HTTP and SQL, and the programme is explicitly built for career changers and for students joining straight after 12th from any stream. The only prerequisite is turning up consistently and finishing each month's project.
A language model answers; an agent decides. A prompting course teaches you to ask better questions. This teaches you to build software that sets its own next step, calls real tools, reads what came back and repeats until the goal is met — then to evaluate, secure, deploy and cost it.
You deploy. The capstone in the final month is a publicly reachable agent with a GitHub repository, an evaluation report with a CI regression gate, an architecture diagram, a five-minute demo video and a cost-per-conversation analysis.
Six portfolio projects: a containerised API service, a document extraction engine, a published MCP server, a cited compliance copilot, a human-in-the-loop approval agent and the deployed support agent capstone. Every one can be opened, run and defended in an interview.
AI Automation Engineer, Agentic AI Developer and Solutions Engineer are the roles this course prepares you for. Those interviews test whether you can wire tools reliably, debug retrieval quality and show a working deployed demo — which is what the six projects are for.
A fresher with a deployed agent and an evaluation report typically starts around ₹20,000 – ₹40,000 per month in the Jalandhar and Ludhiana market, rising quickly with a second year of production experience. Agent work also carries more remote and freelance opportunity than most, since the systems are not in the room.
Yes, and nothing is repeated. The three tracks are nested rather than parallel — this 3-month course remains the permanent foundation, and the 6-month and 9-month tracks continue from where it ends. You never restart, and a topic you have already passed is never re-taught.
No training provider can honestly guarantee a job, and you should be cautious of anyone in Jalandhar who claims one. techcadd guarantees placement support: CV reviews, mock interviews, portfolio preparation and repeated drives with hiring partners across Jalandhar and Ludhiana.
Yes. The course ends in a documented final evaluation — capstone demonstration, technical viva and certification — and every student receives an industry-recognised certificate on completion alongside a documented internship letter based on live project work.
Ask about Agentic AI Program
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.
- info@techcadd.com
- Phone
- +91 98881 22254
- Address
- 2nd Floor, Crystal Plaza, SCS 78, Opposite PIMS Hospital, Jalandhar, Punjab 144001
- Counselling hours
- Monday – Saturday, 9:00 AM – 7:00 PM
Not sure if Agentic AI Program 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.