AWS Data Engineering + AgenticAI MasterClass on 📅 1st July @ 8:30 PM IST
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🔥 FREE Live Masterclass

Master Agentic AI

How to become an AI Engineer in 60 Days

Practical roadmap to build AI Agents, RAG Applications, MCP Integrations, and Multi-Agent Systems for high-paying AI roles.

Structured learning roadmap Week-by-week roadmap
Build production-ready portfolio Portfolio-first execution
Industry-demanded skills Practical add-ons
Career transition blueprint Recruiter-ready profile

Mentor - Velmurugan M.S

Data Architect | Ex-IBM, Cognizant & HP | 17+ years experience

Starts On 1st July 2026
(08:30 PM)

Language - English

Fill Out The Form Now!
Bonus: You’ll also get a checklist for “Job-ready Agentic AI portfolio” + interview prep tracker.

Success Stories

Badal

Ayushi

( Hexaware Technology )

Old Package:

20 L

New Package:

26 L

Ritu

Pritesh

( Mckinsey,lti mindtree,SteerLean )

Old Package:

15 L

New Package:

30 L

WHAT YOU LEARN

AI AGENTS BOOTCAMP

Phase 1: Agentic AI & Enterprise Patterns

  • Understand Agent vs Workflow vs RAG
  • Learn why LangChain + LangGraph matter together
  • Study enterprise reference architecture patterns

Phase 2: AWS Bedrock for Reasoning

  • Work with the Bedrock runtime
  • Use Claude and Titan models for agent reasoning
  • Implement tool calling support and guardrails

Phase 3: FastAPI for Agent APIs

  • Build async APIs for agent workflows
  • Stream responses for real-time interactions
  • Handle request validation cleanly

Phase 4: LangChain Fundamentals

  • Use PromptTemplate, Chains, and Tools
  • Understand memory concepts and agent flow basics
  • Build a simple LangChain agent

Phase 5: LangGraph Fundamentals

  • Work with nodes, edges, and state schema
  • Implement conditional routing in graph flows
  • Build a single-agent LangGraph workflow

Phase 6: LangChain Inside LangGraph

  • Embed LangChain agents inside LangGraph nodes
  • Apply separation of concerns and failure isolation
  • Follow the LangGraph → LangChain → Bedrock pattern

Offer Letters

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Reviews

Vishal Yennam avatar

Soumya Parida

LinkedIn
★★★★★

Velmurugan is a very nice tutor and very well equipped with bigdata technologies like Hadoop, python, pyspark, sql, AWS and azure services. Previously I was into support environment,but with his help I transitioned my career into data engineering domain with a decent salary hike. He not only cleared the concepts but also used to give me realtime scenarios which helped me a lot in cracking the interviews. So would highly recommend everyone to attend his training who want to transition their career in data engineering domain.

Abhishek Sharma avatar

Paramjit Singh

LinkedIn
★★★★★

Velmurugan sir ability to break down complex concepts into simpler, easy-to-understand explanations is remarkable. He guided me step by step, ensuring I had a solid grasp of both foundational and advanced topics. His mentorship was instrumental in helping me clear the Databricks certification, which had been a major goal for me.

Tejaswi S avatar

Kirti Sharma

Google
★★★★★

Learning from Velmurugan was an incredible experience. His deep knowledge of AWS Glue, Spark, and Databricks is matched by his ability to teach in a way that makes even the most complex topics approachable. I’m extremely grateful for his mentorship and would highly recommend him to anyone aspiring to grow in the fields of data engineering or cloud technologies. Velmurugan’s commitment to his students' success truly sets him apart.

About the Mentor

🎓 AWS Certified

Data Architect | Ex-IBM, Cognizant & HP | 17+ years experience

Velmurugan has 17+ years of industry experience and has worked at global giants like IBM, HP, and Cognizant,

Velmurugan M.S. is a veteran Data Architect now channeling his deep technical mastery into the field of specialized education. He brings 9+ years of dedicated expertise in Big Data technologies—specifically Apache Spark, Databricks, and Snowflake—to the classroom, offering students a bridge between academic theory and production-grade engineering.
As an educator, Velmurugan’s "practitioner-first" approach is his greatest asset. He doesn't just teach ETL; he teaches the art of designing scalable Lakehouse architectures and high-performance ELT processes that survive real world stress tests. His recent work integrating agentic AI using AWS Bedrock and LangGraph ensures his curriculum remains at the cutting edge of the AI-driven data revolution.

60 LPAHighest CTC Recorded
2000+ LearnerFrom 30+ Countries
1000+ HoursTraining
200+ CareerTransformation
100+ BatchesDelivered

Who Is This Workshop For?

This course is ideal for professionals who want a specialized learning path in AI Agents with hands-on, real-world implementation.

Individuals seeking a specialized course in AI Agents
Professionals looking for a path suited to 4+ years of experience
Learners who want to build 2 real-time projects

Certification

Certificate Preview

How certification works :

  • Attend the live masterclass session.
  • Complete the required roadmap steps/project checklist.
  • Submit final details and get your completion certificate.

Some of the tools you will learn in this masterclass

Amazon BedrockAmazon Bedrock
FastAPIFastAPI
LangChainLangChain
LangGraphLangGraph
AWS LambdaAWS Lambda

Frequently Asked Questions (FAQs)

  • If you’re working in Support, Testing, Development, .NET, SQL, Power BI, Informatica, SSIS, or Mainframe — this masterclass is your bridge to AWS Data Engineering.
  • No prior AWS experience? No problem. We cover everything from basics to advanced, to make you industry-ready.
  • Even non-tech learners can join the program.
  • Data Integration: Design real‑world ETL pipelines using AWS Glue, Step Functions, and Amazon Managed Airflow to move data across RDS, DynamoDB, S3, and Iceberg/Snowflake/Redshift.​
  • Big Data & Compute: Build scalable PySpark workloads on AWS Glue and EMR, applying Medallion architecture and Spark optimization best practices.
  • Storage & Analytics: Implement S3‑based data lakes, Apache Iceberg tables, Amazon Redshift Serverless, Snowflake on AWS, and Athena for end‑to‑end analytics.
  • SQL Fundamentals: Strengthen SQL on Athena, Redshift, Snowflake, and RDS with real scenarios like CTEs, SCD Type 2, and incremental data loads.
  • Our program is designed to bridge the gap between learning and earning.
  • The Blueprint: Master the tools and FAQs across the full stack—AWS, Pyspark, and Snowflake.
  • The Portfolio: Build a high-impact project portfolio to prove your technical expertise.
  • The Personal Brand: Optimise LinkedIn and Resume to ensure you stand out to top-tier recruiters.
  • The Rehearsal: Gain confidence through mock interviews to crack high-paying AWS Data Engineering roles
  • 60 Days.
  • By balancing technical depth with practical mentorship, we ensure you gain maximum proficiency in minimum time. Your transition to AWS Data Engineering isn't a years-long process—it's a 60-day strategic shift.

Ready to join?

Click below to register. After successful registration you’ll be redirected to WhatsApp group.