01
Students After 12th
Students from any stream can begin the program. The curriculum starts with programming fundamentals before introducing advanced AI concepts.
Start right after school
Best After 12th 3-Month Agentic AI Program in Mohali
Turn your interest in artificial intelligence into practical skills with a 3-month Agentic AI Program in Mohali. Start with Python and AI fundamentals, then progress into prompt engineering, tool integration, RAG, memory, agent workflows, evaluation, security, and deployment. Build functional AI agents that can work with data, APIs, documents, and real-world tasks — even if you are starting without a programming background.
0113
01Where this starts
Course Overview
This 3-month program follows a progressive learning path so that beginners can build confidence before working with advanced AI architectures.
Month 1 — Coding & AI Foundations: Learn Python programming, Git/GitHub, APIs, JSON, databases, LLM fundamentals, prompt engineering, structured responses, and tool calling. You will also understand how an AI agent differs from a conventional chatbot.
Month 2 — RAG, Memory & Agent Workflows: Build systems that can search documents and external knowledge before generating responses. Explore embeddings, vector databases, document processing, memory, state management, agent orchestration, and human approval workflows.
Month 3 — Evaluation, Security & Deployment: Learn how to test AI agents, measure response quality, manage costs, add safety controls, monitor applications, and deploy an agent as a usable application. The final stage focuses on a complete portfolio project.
02Skills you collect
What You'll Learn
The ten outcomes below run in order, from the Python underneath an AI application through to a hosted agent you can demonstrate in an interview.
Build a strong technical base
Start with Python, APIs, databases, Git, and command-line fundamentals so you understand what happens underneath an AI application.
Design effective AI instructions
Learn practical prompt engineering techniques for structured, reliable, and task-specific model responses.
Connect AI with external tools
Create tool-enabled workflows where an AI model can interact with APIs, databases, services, and custom functions.
Create knowledge-based AI
Build RAG applications that retrieve relevant information from documents and databases before producing an answer.
Add memory and context
Understand how AI applications maintain conversation state, user context, and persistent information across interactions.
Develop agent workflows
Learn how agents can plan tasks, make decisions, call tools, evaluate results, and continue through multiple steps.
Work with agent frameworks
Get practical exposure to modern frameworks used to create structured and stateful AI workflows.
Evaluate AI applications
Learn to test responses, retrieval quality, tool selection, and complete agent trajectories instead of relying only on visual demos.
Add security and guardrails
Understand common AI application risks and implement validation, filtering, approval steps, and safe-response mechanisms.
Deploy your AI project
Move from a local development environment to a hosted application that can be demonstrated during interviews or portfolio reviews.
03The route
Course Curriculum
Three months, three stages — the code and the model, then retrieval, memory and agents, then evaluation, safety, deployment and a capstone.
- Python syntax, variables, operators, conditions, loops, functions, and data structures
- Object-oriented programming and reusable Python code
- Type hints, packages, virtual environments, and asynchronous programming
- Command-line fundamentals and developer workflows
- Git and GitHub for source-code management
- HTTP, REST APIs, JSON, authentication, and API integration
- SQL and database fundamentals
- Introduction to large language models and generative AI
- Tokens, context, model parameters, and prompt structure
- System, user, and assistant instructions
- Prompt engineering and few-shot prompting
- Structured outputs and schema validation
- Function and tool calling
- Building a basic agent workflow without relying completely on a framework
- Introduction to Model Context Protocol and tool-based AI integrations
- Practical Projects:
- Python API application
- AI prompt experimentation project
- API-connected AI assistant
- Basic tool-calling agent
Hands-on Lab Practice
Every stage ends in build work rather than revision — API and prompt exercises in month one, RAG and stateful workflows in month two, and an evaluated, deployed agent in month three.
Outcome
By completing the curriculum, students will have taken an AI workflow from the initial idea through tools, retrieval, memory, evaluation, guardrails and deployment, with a capstone agent to demonstrate.
04Your toolkit
Tools You Will Practically Work With
The program focuses on tools that help you move from experimentation to complete AI applications.
PythonGit & GitHubFastAPIPostgreSQLDockerOpenAI APIClaude APIGemini APIPydanticLangChainLlamaIndexPythonGit & GitHubFastAPIPostgreSQLDockerOpenAI APIClaude APIGemini APIPydanticLangChainLlamaIndexPythonGit & GitHubFastAPIPostgreSQLDockerOpenAI APIClaude APIGemini APIPydanticLangChainLlamaIndex
LangGraphQdrantChromaFAISSRedisRAGASLangSmithLangfuseStreamlitGitHub ActionsLangGraphQdrantChromaFAISSRedisRAGASLangSmithLangfuseStreamlitGitHub ActionsLangGraphQdrantChromaFAISSRedisRAGASLangSmithLangfuseStreamlitGitHub Actions
- Python
- The language everything in the programme is built in.
- Git & GitHub
- Source-code management and the development workflow.
- FastAPI
- Serve an agent behind an HTTP API.
- PostgreSQL
- Relational storage for application and agent data.
- Docker
- Package the finished agent for deployment.
- OpenAI API
- One of the model providers behind the agents.
- Claude API
- A second provider, for comparison and structured work.
- Gemini API
- A third provider in the same tool-calling patterns.
- Pydantic
- Schema validation for structured model outputs.
- LangChain
- Chains, tools and the glue around model calls.
- LlamaIndex
- Document indexing and retrieval pipelines.
- LangGraph
- Agent graphs, state and conditional routing.
- Qdrant
- A vector database for semantic search.
- Chroma
- A lightweight vector store for local RAG work.
- FAISS
- Similarity search over embeddings at speed.
- Redis
- Short-term memory and fast shared state.
- RAGAS
- Measure retrieval and answer quality.
- LangSmith
- Trace runs and debug agent trajectories.
- Langfuse
- Logging, monitoring and cost tracking.
- Streamlit
- A chat interface for the deployed capstone.
- GitHub Actions
- Automate tests and the deployment pipeline.
05Is this you?
Who Can Join the Agentic AI Program?
02
College Students
Students pursuing BCA, B.Sc, B.Tech, BBA, or other technology-related programs can use the course to add practical AI development skills to their academic knowledge.
03
Graduates & Freshers
Graduates looking to enter the growing AI and automation space can develop a project portfolio instead of relying only on theoretical knowledge.
04
Working Professionals & Career Changers
Professionals interested in AI automation can use the practical curriculum to understand how AI agents are designed, integrated, evaluated, and deployed.
05
Developers & Tech Learners
Anyone who already understands programming can use the program to move from conventional application development toward AI-powered systems and agent workflows.
06Why this one
Why Choose This Programme?
01
Learn AI by Building
Instead of spending three months only watching demonstrations, you work on practical exercises and progressively larger AI projects.
02
Start From the Basics
You do not need to be an AI expert on day one. Python, APIs, databases, and developer tools are introduced before advanced agent concepts.
03
Understand the Technology Behind Agents
The focus is not simply on prompting ChatGPT. You learn how agents interact with tools, retrieve information, maintain state, and execute workflows.
04
Build Portfolio-Ready Work
Your projects can demonstrate practical skills in Python, APIs, RAG, agent workflows, evaluation, and deployment.
05
Learn Responsible AI Development
Security, validation, evaluation, privacy, monitoring, and human approval are included so you understand the challenges involved in real AI applications.
07Why now
From AI Users to AI Builders
Artificial intelligence is moving from simple content generation toward systems capable of handling multi-step tasks. Learning Agentic AI early can give students exposure to a fast-evolving area that combines programming, automation, APIs, data, and generative AI.
Rather than learning AI only as a user, this program helps you understand how AI-powered applications are constructed and connected to real services.
Generative AI has made powerful models accessible, but building dependable AI applications requires more than writing prompts. Organizations also need people who can connect models to business data, tools, workflows, and applications.
Agentic AI brings these capabilities together by combining language models with tools, retrieval, memory, automation, and controlled decision-making.
What an agent adds to a model
- ToolsCall APIs, databases, services and custom functions to act, not just answer.
- RetrievalSearch documents and knowledge bases before generating a response.
- MemoryHold conversation state and user context across interactions.
- AutomationPlan and run multi-step tasks through to completion.
- Controlled decision-makingValidation, guardrails and human approval on the steps that matter.
Not sure Agentic AI is your starting point?
Ten minutes with a course counsellor settles eligibility, session timings, fees and where this leads — before you commit three months to it.
08Certification
Get Certified in Agentic AI Program
After completing the program and practical assignments, students receive a course completion certificate. Students who successfully complete the final project can also use their project as a portfolio piece during interviews and further career applications.
Course CertificateRecognition of successful completion of the Agentic AI training program.
Project ExperienceA completed AI application demonstrating practical development skills.
Internship & Placement AssistanceCareer guidance, resume support, interview preparation, and placement assistance are provided as part of the training support.
Portfolio DevelopmentBuild project documentation and demonstrations that can strengthen your technical portfolio.
Capstone Defense
Fullscreen
Project Completion Certificate
ISO 9001:2015 Accredited
Fullscreen
Course Completion Certificate
Two documents on completion — the course certificate, and a separate certificate for the capstone you build and defend. Click any card to inspect in full screen.
09Where it leads
Where This Course Can Take You
Agentic AI combines software development with artificial intelligence and automation. Depending on your existing skills and further learning, possible career directions include:
Possible career directions
Work on AI-powered workflows that connect models with business tools, APIs, and data.
10What you build
Hands-on Projects You Will Build
01
AI-Powered API Assistant
Create a Python-based service that communicates with external APIs and uses an AI model to process user requests. Skills: Python · FastAPI · REST APIs · Git
02
Intelligent Document Assistant
Build an application capable of processing documents and answering questions using retrieved information. Skills: Python · RAG · Embeddings · Vector Search
03
Tool-Calling AI Agent
Develop an agent that can select and execute predefined tools based on a user's objective. Skills: LLM APIs · Tool Calling · Structured Outputs
04
Knowledge Base Copilot
Create a citation-aware assistant that searches a knowledge base before generating responses. Skills: RAG · Qdrant/Chroma · Retrieval · Evaluation
05
Human Approval Workflow
Build a stateful AI workflow where selected actions require human approval before execution. Skills: LangGraph · State Management · Checkpoints
06
Deployed AI Agent
Complete a publicly demonstrable capstone application with a user interface, evaluation process, monitoring, and deployment. Skills: Agent Framework · Streamlit · Docker · Deployment
11How it works
Learn. Build. Deploy.
The programme runs the same five stages on every project you build:
Understand
Start by understanding the problem, data, tools, and expected output before writing the solution.
AI-Powered API AssistantDevelop
Build the workflow step by step with trainer guidance and practical testing.
Intelligent Document AssistantEvaluate
Test your AI application using real examples and identify weaknesses in retrieval, responses, or tool execution.
Tool-Calling AI AgentImprove
Refine prompts, workflows, retrieval strategies, validation, and safety controls.
Knowledge Base CopilotDeploy
Turn the completed project into a working application that can be demonstrated online.
Human Approval Workflow12Why techcadd
Why Students Choose techcadd
Practical training, a beginner-friendly progression and project work at every stage, closed with career support.
01
Practical Learning Approach
The program combines concepts with hands-on implementation so students can immediately apply what they learn.
02
Beginner-Friendly Progression
The curriculum is structured to help students move from Python basics toward advanced AI development without assuming extensive prior knowledge.
03
Project-Based Training
Each stage introduces practical work, allowing students to gradually build a portfolio of AI applications.
04
Career-Focused Guidance
Students receive support with resume preparation, interview practice, project presentation, and career direction.
05
Expandable Learning Path
After completing the 3-month program, students can continue developing their skills through advanced AI, full-stack, cloud, data, or automation pathways.
13Who has walked it
Students who started where you are
Alumni of this route, on what changed once they were sitting in interviews.
4.8
293 reviews
586%
49%
33%
21%
11%
The Agentic AI course at Techcadd Mohali got me interview-ready faster than I expected. My interviewer asked to see my MCP server project, and that was basically the whole conversation.
I travelled in from Zirakpur for the weekend session and it was worth every trip. 1:1 session, real client work, no time wasted on theory nobody actually uses on the job.
Techcadd's placement cell kept calling me for drives across Mohali and Chandigarh until I was actually placed. That persistence mattered more to me than the certificate itself.
I was switching careers at 27 and worried I'd be behind everyone else. Half the session at the Mohali centre was doing the same thing — nobody made me feel slow.
I joined with almost zero coding background and finished with a deployed agent I could actually demo. The trainer corrected my work daily instead of just moving to the next slide.
What made Agentic AI click for me was the lab time. You could sit back after class in the Mohali centre and someone would still explain it until it actually made sense.
Working full-time in IT Park Mohali, the evening session was the only reason I could do this without quitting my job. Interview-ready for an AI Engineer role in about five months.
I run a small digital agency in Chandigarh and took this course to stop outsourcing AI work I couldn't evaluate myself. Now I scope and review agent projects with confidence.
Compared two other training centers in Mohali before joining Techcadd. The difference was real client work versus recorded demos — that's what actually got me placed.
The internship letter from live client work was accepted for my university's industrial training requirement without any issue — one less thing to worry about in final year.
I'm a self-taught learner who had watched dozens of YouTube tutorials and built nothing real. A deadline attached to every module here is what finally got me shipping projects.
1:1 session format at the Mohali centre meant the trainer actually knew what each of us was stuck on. That's rare compared to the crowded classes I sat through elsewhere.
14Before you go
Frequently Asked Questions
Still unsure? A ten-minute call with a counsellor usually settles it faster than any brochure.
The program is designed as a 3-month practical training pathway covering programming foundations, AI development, agent workflows, evaluation, and deployment.
15Final stage
Ask About Agentic AI Program in Mohali
Have questions about the syllabus, practical training, session timings, fees, projects, eligibility, or career opportunities? Connect with a course counsellor to understand whether the Agentic AI Program is suitable for your learning goals.
+91 98881 22442Call the admissions desk+91 98881 22442WhatsApp for a quick replyinfo@techcadd.comEmail us your questions
Your details are used only to contact you about this enquiry — never sold, never added to a marketing list.
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Still deciding
Where You Can Go After This
The 3-month program can serve as a foundation rather than an endpoint. After building your fundamentals, you can continue along a longer learning path.
You can continue toward
- Advanced Agentic AI
- Generative AI
- Machine learning
- Cloud
- Automation
- Software development
- Full-stack development
- Data