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AI Engineer Program Next batch 21 Nov 2026 · Live online · Enrolment closes Fri 20 Nov
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Flagship Program Career Focused Program

AI Engineer Course: Build Production AI Agents with RAG & MCP

Master Agentic AI, LLMs & Multi-Agent Systems

Go from Python fundamentals to shipping autonomous, multi-agent AI systems, with dual certification prep for Anthropic's Claude Certified Architect (CCAR-F) and Microsoft's Azure AI Apps & Agents Developer Associate (AI-103).

  • Build production AI agents with LangChain, LangGraph, CrewAI & MCP
  • Ship real RAG pipelines, vector search and tool calling systems
  • Prep for two industry certifications: Claude CCAR-F & Microsoft AI-103
80 Hrs Training + 20 Hrs Prep
  • Lifetime accessto every session recording
  • Pre-recorded contentlearn at your own pace
  • 80 hrs training+ 20 hrs dedicated project & interview prep
  • Dual certificateClaude + Microsoft AI-103, plus 360DT participant certificate
Next Cohort21 Nov 2026
Duration14–16 Weeks
FormatLive Online · Sat–Sun
Projects11 Projects · 8 Capstones
Next Batch 21 Nov 2026
Program Fee ₹27,999₹37,239
Payment EMI Available
Enrolment closes Fri 20 Nov

Built For

Who This AI Engineer Course Is For

You don't need an ML background; you need to be ready to build. Tap any card below to see why it fits you.

Software developers who want to ship products powered by LLMs, not just prototype with them

Tap to learn more

You already know how to code. Here you will learn to design agent architectures, manage context windows and ship LLM features that hold up in production, not just in a demo.

Data, ML & cloud professionals transitioning into generative and agentic AI roles

Tap to learn more

You bring the data and infrastructure background. This program adds the missing piece: reasoning loops, tool calling and orchestration, so you can move confidently into agentic AI roles.

Builders who want hands-on reps with real agent frameworks before touching production

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You learn fastest by building. Every week you wire up real frameworks, break things, fix them and walk away with working code you actually understand end to end.

Students and career switchers who want a structured, project based path into AI engineering

Tap to learn more

You do not need a computer science degree to start. A structured, project first path takes you from your very first prompt to a portfolio ready for interviews.

Certification & Partnerships

Dual certification prep, built into the curriculum

Module 7 (Claude CCAR-F) and Module 8 (Microsoft AI-103) map directly to the current public exam blueprints for both credentials below.

Anthropic

Claude Certified Architect – Foundations (CCAR-F)

Anthropic's official, proctored credential at the architecture level. It validates your ability to design and ship production ready Claude applications, covering agentic architecture, MCP integration, Claude Code workflows and context reliability.

Agentic Architecture MCP Integration Claude Code Structured Output
Microsoft

AI-103 — Azure AI Apps & Agents Developer Associate

Validates your ability to plan, build and deploy generative AI and agentic solutions on Azure using Microsoft Foundry, including grounding, tool integration and responsible AI practices.

Azure AI Foundry Agentic Solutions Grounding & RAG Responsible AI

Platforms & exams covered

Claude Anthropic Microsoft OpenAI Google Cloud AWS NVIDIA CompTIA Atlassian

Certification exams are administered independently by Anthropic and Microsoft and are not included in program tuition.

11
Projects & 8 Capstones
2
Certifications Prepped For
1:1
Dedicated Mentor Support
∞
Lifetime Access to Sessions

Curriculum

AI Engineer Course Syllabus, Module by Module

Ten modules taught live over 16 weeks, each one building toward the two certification tracks and your final capstone. Every module ends in something you build.

1 Python & AI Engineering Foundations Module 1

Weeks 1 to 3

Every AI system is still just a program underneath. We make sure that foundation is solid before touching a single model.

  • Python fundamentals, data structures & OOP for AI systems
  • NumPy & Pandas for data handling
  • APIs, JSON & system integration
  • File handling, automation scripts & modular code
  • Debugging, logging & configuration workflows
Project: Reusable data processing pipeline PythonNumPyPandas
2 LLM Foundations & Prompt Engineering Module 2

Weeks 2 to 3

Before you can build an agent, you need to understand what you're actually talking to, and how to talk to it well.

  • Transformers, attention & tokenization
  • How LLMs generate text: context windows & next token prediction
  • Prompt engineering: zero shot, few shot, chain of thought
  • System prompts, role based prompting & structured output
  • Function calling and structured JSON responses
  • Comparing model choices: GPT, Claude, Gemini, Llama & Granite
OpenAI APIClaude APIGemini APIHugging Face
3 RAG & Vector Systems Module 3

Weeks 3 to 4, 6, 8

An LLM only knows what it was trained on. This module is about connecting it to your own, current data, accurately.

  • Generating and comparing embeddings
  • Chunking strategies & data ingestion
  • Vector databases: FAISS, ChromaDB & Pinecone
  • Retrieval pipelines & semantic search
  • Reranking, hybrid retrieval & reducing hallucinations
  • Agentic RAG: retrieval inside a reasoning loop
Project: Production grade RAG assistant FAISSChromaDBLangChain
4 Building AI Agents with LangChain Module 4

Weeks 3 to 4, 7

This is where the program turns a corner, from calling a model to building something that reasons and acts on its own.

  • What makes a system "agentic" versus a simple chatbot
  • Tool calling & chaining with LangChain Expression Language (LCEL)
  • Extracting tool inputs from LLM outputs, then validating and executing the call
  • ReAct style reasoning: think → act → observe
  • Using built in LangChain agents to analyze data, generate visualizations & run database queries
  • Short term & long term memory for agents
  • Designing and binding custom tools safely: accuracy, safety & cost tradeoffs
Project: an agent that executes tasks with real tool access LangChainLCEL
5 LangGraph: Stateful Multi Agent Workflows Module 5

Weeks 4, 7 to 8, 10, 14

Single agents hit a ceiling fast. LangGraph is how you give a system memory, structure, and the ability to correct itself as it works.

  • Workflows built as graphs: state, nodes & edges
  • Conditional logic & iteration in agent workflows
  • Agents that improve themselves: Reflection, Reflexion & ReAct architectures
  • Structuring agent feedback and integrating external data while reasoning
  • Human in the loop checkpoints for higher stakes decisions
  • Agentic RAG systems that route queries and support reasoning enhanced by retrieval
  • Agent orchestration, query routing & governance for reliability at scale
Project: multi step research agent with self correction LangGraph
6 Multi Agent Orchestration: CrewAI, AutoGen & BeeAI Module 6

Weeks 9 to 10

One agent can only do so much. This module is about splitting work across a team of agents the way you'd delegate across a real team.

  • Structuring agents, tasks & tools into crews
  • Designing agent roles and delegating tasks
  • Selecting and combining agentic frameworks & architectural patterns for a given problem
  • Memory management across multiple collaborating agents
  • Agents driven by conversation, built with AG2 (AutoGen) and BeeAI
  • Agent to agent communication patterns
  • Comparing frameworks (LangGraph vs. CrewAI vs. AG2 vs. BeeAI) for real world fit
Project: Collaborative multi agent system CrewAIAutoGen (AG2)BeeAI
Milestone 1CLAUDE

Redeem your Claude Agentic AI badge

7 MCP & Claude Agentic Architecture CCAR-F Prep Module 7

Weeks 5 to 6

MCP is quickly becoming the standard way agents connect to tools and data. This module doubles as direct prep for Anthropic's own architecture exam.

  • Model Context Protocol: servers, clients, tools, resources & prompts
  • Connecting models, tools and data through MCP
  • Claude Agent SDK & Claude Code workflows
  • Structured output design and context window management
  • Reliability patterns: multi instance review and coherence across long conversations
  • Mapped to Anthropic's Claude Certified Architect, Foundations exam domains
Project: MCP based workflow automation system MCPClaude APIClaude Agent SDK
Milestone 2MICROSOFT

Redeem your Microsoft Agentic AI badge

8 Agentic AI on Azure AI-103 Prep Module 8

Weeks 4, 9, 11

Most companies hiring for agentic AI roles already run on Azure. This module makes sure you can ship there too.

  • Azure AI Foundry: projects, model deployment & managed identity
  • Implementing generative AI & agentic solutions on Azure
  • Grounding agents with Azure AI Search & RAG patterns
  • Responsible AI, content filtering & security on Azure
  • Practice aligned to the exam: planning & managing Azure AI solutions
Azure AI FoundryAzure AI SearchAzure OpenAI Service
9 LLMOps, Deployment & Evaluation Module 9

Weeks 2, 5, 11 to 13

A working notebook isn't a product. This is the module where your agent becomes something other people can actually rely on.

  • Serving agents with FastAPI & containerizing with Docker
  • Deploying to the cloud & designing for scale
  • Prompt versioning, tracing & observability
  • Evaluation pipelines, guardrails & hallucination checks
  • Caching, batching & cost/latency optimization
  • CI/CD for AI applications
Project: Deployed, monitored production agent FastAPIDockerLangSmith
10 Capstone, Certification & Interview Prep Module 10

Weeks 12 to 16

  • End to end capstone: build & ship a multi agent product
  • Mock interviews with AI engineering hiring panels
  • Sample exam papers for CCAR-F and AI-103
  • Resume & LinkedIn profile built around your project portfolio

Portfolio

8 flagship capstone projects

Each project, drawn as the system you build: the real tools, and the data moving through them. Scroll; they animate.

01

Enterprise RAG Assistant

Built in weeks 3 to 6

Internal policies and SOPs go in; a chat assistant that answers with sources, and says so when it has none, comes out.

Swipe →
You shipIngestion pipelineVector indexChat UI with citationsRetrieval config
02

Multi-Agent Research Assistant

Built in weeks 7 to 10

A planner, three searcher agents on three different models, a validator that cross-checks sources, and a report at the end.

Swipe →
You shipLangGraph agent graphSource validatorResearch report templateRun traces
03

AI Customer Support Copilot

Built in weeks 7 to 9

Messages from WhatsApp, email and Slack, routed through knowledge, order data and tickets, with a human on standby.

Swipe →
You shipIntent routerHelp-centre RAGTool integrationsEscalation policy
04

MCP Workflow Automation System

Built in weeks 5 to 8

A trigger fires, an agent plans, MCP servers do the work across Drive, Gmail, the database and the task board, and a summary lands in Slack.

Swipe →
You shipMCP serversTyped tool contractsWorkflow runbookAudit log
05

AI Resume & Interview Copilot

Built in weeks 3 to 15

A resume and a job description converge into a gap analysis, then a mock interviewer runs rounds until the score clears the bar.

Swipe →
You shipResume-to-JD matcherMock interview agentScoring rubricFeedback report
06

Deployed Production LLM App

Built in weeks 11 to 13

A Streamlit front end and a FastAPI backend, through CI and a container, onto AWS, traced and watched on a dashboard.

Swipe →
You shipLive app URLCI pipelineTraces & evalsMonitoring dashboard
07

CrewAI Collaborative Ops Team

Built in weeks 9 to 12

A manager agent hands a real weekly workflow down a relay of role agents sharing one memory, and QA sends it back when it is not right.

Swipe →
You shipCrew definitionRole prompts & toolsShared memory storeWeekly ops report
08

Azure Hosted Agentic Solution

Built in weeks 9 to 11

An agent on Azure AI Foundry, grounded by AI Search, guarded by content safety, calling Functions, monitored, and mapped to AI-103.

Swipe →
You shipFoundry agentAI Search groundingContent-safety configAI-103 evidence pack

Skills Covered

Python for AI Systems Prompt Engineering RAG Systems Vector Databases AI Agents & Agentic Workflows Multi-Agent Orchestration Model Context Protocol (MCP) LLMOps & Deployment Azure AI Solutions Claude Agentic Architecture

Tools & Frameworks Covered

Python LangChain LangGraph CrewAI AutoGen (AG2) BeeAI FAISS ChromaDB FastAPI Docker Azure AI Foundry Claude API & Agent SDK MCP LangSmith

Program Creators

Your AI Engineer Course Instructors

Six working trainers run this program live. Hover any card for their full background.

Naga Nandhini

Naga Nandhini

Certified Trainer

Java Full Stack Corporate Trainer and Enterprise Solutions Expert

More about Naga

Powerhouse corporate trainer with 10+ years of upskilling engineers at HCL, Accenture, Cybage, Mobileum and Renault. An award-winning engineer who helped build the RAPTOR and KIKO platforms for an American Airlines client, she brings real enterprise delivery into every session.

Praveen Kumar

Praveen Kumar

Certified Trainer

Full Stack and GenAI Corporate Trainer, Ex-TCS Team Lead

More about Praveen

Full stack lead and GenAI builder with 10+ years of training behind 50+ corporate batches for TCS, HCL, Perficient, Renault Nissan and Saint-Gobain. He ships real RAG and local-LLM systems with Ollama, FastAPI and Spring Boot, then teaches exactly how they work.

Johan

Johan

Certified Trainer

D365 Customer Service Lead, Power Platform School Founder

More about Johan

D365 Customer Service Lead – Europe at Avanade, and founder of the Power Platform School. A Microsoft Business Applications MVP and Microsoft Certified Trainer based in London, specializing in Dynamics 365 Customer Service and Power Platform.

Akim Nyamande

Akim Nyamande

Certified Trainer

Microsoft, CompTIA, Juniper and Cisco Certified Trainer.

More about Akim

IT training facilitator with over five years of experience and certifications across Microsoft, CompTIA, Juniper, and Cisco. Previously a Network Administrator before moving into technical training, now delivering hands-on courses in networking, systems administration, and cybersecurity fundamentals.

Ali El Khatib

Ali El Khatib

Certified Trainer

Cisco Certified Systems Instructor (CCSI), Microsoft Certified Trainer

More about Ali

Infrastructure Engineer at RHUH with 13 years in the training field, holding CCSI, MCSE, CCNP Routing and Switching, CCNP Security, CompTIA and Microsoft Azure certifications.

Arshad Ahmad

Arshad Ahmad

Certified Trainer

Microsoft Certified Trainer (MCT), Cybersecurity & Power Platform Expert

More about Arshad

Technology Trainer with 15 years in strategic client delivery, holding MCT, Azure Solutions Architect Expert, Cybersecurity Architect Expert and Power BI Data Analyst credentials, with 200+ trainings delivered.

Florian Garcia Compte

Florian Garcia Compte

Certified Trainer

Cisco Certified Systems Instructor (CCSI)

More about Florian

Partner Director at AVAANZA FORMACION, a Cisco Learning Partner based in Madrid. Certified Cisco Systems Instructor (CCSI No. 21053) specializing in Cisco Data Center (ACI/SDN), Nexus, and Wireless, delivering official Cisco certification courses including CCNA, CCNP Enterprise, and CCNP Data Center.

Shantanu Pandey

Shantanu Pandey

Certified Trainer

Microsoft, Google, NVIDIA and HPE Certified Trainer

More about Shantanu

Director of Engineering at Meteoros Automation, ranked in Microsoft's Top 100 Trainers of 2025, holding MCT, Google Cloud, NVIDIA and PeopleCert credentials, with 500+ trainings delivered since 2011.

Sid

Sid

Certified Trainer

Microsoft Certified Trainer since 2016 and Azure Data Engineer

More about Sid

Dynamic corporate trainer and consultant with more than 10 years of experience across Microsoft Fabric, Azure Data Engineering, and modern cloud platforms. Focused on clear, practical learning that sticks.

Sravia

Sravia

Certified Trainer

NVIDIA Authorized Instructor and AI Data Specialist

More about Sravia

Passionate AI and data evangelist with over 10 years of experience across machine learning, MLOps, and cloud native technologies. Dedicated to delivering impactful, engaging enterprise training programs.

Vikas Mittal

Vikas Mittal

Certified Trainer

AI instructor with 25+ years in technology training

More about Vikas

Veteran technology trainer with more than 25 years of rich industry experience spanning Google, Microsoft, and emerging AI platforms. An exceptional mentor recognized for proven teaching excellence.

Bipeen

Bipeen

Certified Trainer

AWS, Microsoft, and Anthropic Certified Trainer

More about Bipeen

AI, machine learning, and cloud transformation expert with more than 25 years of experience. A renowned global corporate trainer and conference speaker known for practical, outcome driven sessions.

Learner & client voices

What people trained by our instructors say

I had the opportunity to be trained by Vikas on a 4-day Google Professional Data Engineer course — a genuinely useful experience. His expertise in Data Science and Machine Learning shows in how he delivers the training, and it played a huge role in my clearing the certification exam on the first attempt.

Archana Bhalla

Archana Bhalla

Data Science & Big Data Engineer, Atos

One of the best trainings I have ever attended in my life. The instructor gave an in-depth knowledge of Machine Learning and its use cases in the financial industry.

Ashish Kulshrestha

Ashish Kulshrestha

Managing Director, American Express

Vikas was invited to be a GCP data engineering instructor at a 4-day Google Developer Machine Learning Bootcamp in Bangkok, sponsored by Google. He simplified tough topics with concrete examples, making difficult material easy and fast to understand. Good instructor — thanks for the dedication.

Ekawut Suwanicho

Ekawut Suwanicho

Data & ML Solution Engineer, Tangerine Co. Ltd.

From corporate and bootcamp training led by our instructors. More on Success Stories.

Dual Certification + 360DT Certificate

Dual certification, plus your 360DT participant certificate

A verifiable, portfolio-ready certificate that signals real, project-tested skill, not just seat time.

  • Your name, program and completion date, ready to add to LinkedIn
  • Backed by 80 hrs of training + 20 hrs of project & interview prep, and 8 shipped capstone projects
  • Dual certification: Claude CCAR-F (Anthropic) and AI-103 (Microsoft), both built into the curriculum
  • Your 360DT participant certificate comes in addition to both credentials
Enroll & Earn Yours
Sample Certificate Sample 360DT program completion certificate

Fees & Batch

AI Engineer Course Fees and Next Batch Dates

Live Online · Weekend Batch

AI Engineer Program

Start Date21 Nov 2026
Duration14–16 Weeks
TimingSat–Sun, 8:00–11:00 PM IST
Enrolment closesFri 20 Nov
₹37,239₹27,999

EMI options available · Corporate/team batches, contact us

Optional add-ons

The course is complete on its own. Add one only if it fills a gap. Nothing is pre-selected.

Cloud & Deployment

Docker & Kubernetes Basics+₹5,000

AI-Specific Add-Ons

Prompt Engineering Masterclass+₹5,000

Career & Soft Skills

Resume & LinkedIn Optimization for AI Roles+₹5,000
Mock Interview / Technical Interview Prep+₹5,000
Portfolio Building Workshop+₹5,000
0 add-ons selected

Add-ons are added to your enrollment automatically when you click Enroll Now below.

Where This Takes You

Jobs and Career Paths After This AI Engineer Course

Agentic AI is the fastest moving hiring category in tech right now; this is your on-ramp into it, mapped out step by step.

1

AI Agent Engineer 🔥 Highest Demand

Build the autonomous systems every company is racing to ship.

Design and ship autonomous agents and multi-agent systems for real business workflows.

2

Generative AI Specialist ⚡ Fastest Growing

Own the copilots and chat experiences users interact with every day.

Build AI copilots, chatbots and content systems on top of modern LLMs.

3

LLMOps Engineer 🛠️ Mission Critical

Be the person production AI systems can't run without.

Deploy, monitor and optimize production ready AI systems at scale.

4

AI Solutions Architect 🏆 Senior Track

Design the AI backbone enterprise leadership is betting on.

Architect end-to-end AI systems that integrate cleanly into enterprise stacks.

5

Applied AI Engineer 🚀 Startup Favorite

Turn cutting-edge models into products people actually pay for.

Turn LLMs, RAG and agents into working, revenue-generating products.

6

Agentic AI Consultant 💼 High Trust Role

Become the expert organizations call to adopt AI the right way.

Help organizations design and responsibly adopt automation built on agents.

Placement Support · Included

Finish this course, then get introduced to the companies hiring for it.

A named mentor, recorded mock interviews, a résumé rebuilt around your projects, and warm introductions to our placement partners Arusto AI, Meteoros, Confluent and Accenture. Included with your seat, for 6 months after the course.

Each partner interviews and hires directly; an introduction is not a job offer. What career support covers.

Next cohort starts 21 Nov 2026

Live, online, Saturday–Sunday · Enrolment closes Fri 20 Nov.

Join the 21 Nov batch

FAQ

AI Engineer Course FAQs

Do I need prior AI/ML experience to join?

No. We start from Python fundamentals in Module 1. A background in basic programming helps, but it isn't required.

Are the Claude CCAR-F and AI-103 exam fees included?

No, exam fees are paid directly to Anthropic and Microsoft and are separate from program tuition. We prepare you fully for both; scheduling and payment for the exams themselves happens on their respective platforms.

What happens if I miss a live session?

Every session is recorded and added to your dashboard the same day, and you can re-attend any future live batch of the same module at no extra cost.

Is job or placement assistance included?

Yes, mock interviews, resume and LinkedIn support, and introductions to our hiring partners are part of Module 10. Final hiring decisions always depend on your interview performance and the employer's needs.

What do I need to get started?

A laptop with a stable internet connection. All frameworks, model APIs and cloud sandboxes used in class are provided or free-tier for the duration of the course.

When does the next batch start, and when does enrolment close?

The next live batch starts Sat 21 Nov, and enrolment closes Fri 20 Nov. Classes run live on Saturday and Sunday, 8–11 PM IST.

Can I pay in instalments?

Yes. Cards, UPI, net banking and EMI options are available at checkout; tenure and cost depend on your card.

Can my company pay, and will I get a GST invoice?

Yes. Add your company's GSTIN in the cart before checkout so it appears on your invoice. For a team batch, talk to our corporate team.

Can I move to a later batch?

One free batch transfer is allowed, up to 5 days before your batch starts and subject to seats in the new batch.

Can I get a refund?

Every enrolment includes lifetime access to the recordings and materials from day one, so all enrolments are final. If you are unsure, book a free demo first, or use the one free batch transfer.

What happens right after I enrol?

You get a confirmation email with your LMS login and batch schedule. Class links, recordings and materials are all in your learner dashboard.

Do I get a certificate from 360DT?

Yes. Learners who meet the attendance and project criteria get a 360DT completion certificate they can share on LinkedIn. It is separate from the official exam certification.

Can I talk to someone before I enrol?

Yes. Book a free demo or call +91 70914 64529, and an advisor will walk you through the syllabus and help you pick the right course.

Ready to enrol in AI Engineer Course: Generative AI, RAG & AI Agents (Microsoft + Claude Certified)? Dates, seats and fees are on the enrolment page — enrolment is open now.
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