Work on Enterprise projects specific to core industries.
Go beyond theory with MERN Stack, Python for AI, LangChain, LlamaIndex, CrewAI, Google Agent Stack, BaaS, Kubernetes, GCP, NVIDIA AI, RAG-as-a-service, Agentic AI
This intensive, industry-first approach is your shortcut to becoming a world-class AI/GenAI Engineer.
3 Weeks
20+ hours/week (additional effort required for non-technical students)
Minimum Graduate; Engineering (Any Specialization), MCA/BCA, MBA/BBA graduates
• Aspiring tech professionals who want the most practical and direct path into a high-growth AI career
Building next-gen solutions
Enterprise technology solutions
Technology Consulting
Why spend months and lakhs on outdated, "real-world like" projects? With us, you skip the simulation. You'll be immediately immersed in Enterprise projects from booming sectors. Your code won't just be for a grade; it will solve real business problems. This is the ultimate career launchpad.
This intensive program delivers tangible results for your career through hands-on experience
3 Weeks
Live Online
20+ Hrs/Week
Production Grade Projects
30+ Tools
Career Prep
Build and deploy Enterprise Grade applications specific to booming sectors. Learn to present projects compellingly for technical interviews.
Working with industry experts, orchestrate complete enterprise applications with real-world development cycles.
Receive lifetime access to Git repository with all projects and codebases. A living portfolio to showcase skills to recruiters for years.
Your journey continues:
Getting started with Python and MERN stack and essential developer tooling
Fundamentals of AI, GenAI, ML, and Large Language Models (LLMs)
Embedding models & Vector basics
Full Enterprise stack:
Master Python, including backend API development with Flask/FastAPI, and MERN for versatile full stack development. Utilize Github/GitLab for deployment pipelines. This ensures a holistic understanding of end-to-end application development.
Hands-on AI coding and testing with cutting-edge tools:
Gain proficiency in AI-assisted coding and testing environments. Learn how to leverage these assistants to develop cleaner, more efficient, and robust AI-powered enterprise ready applications, significantly boosting productivity.
Advanced Prompting & Reasoning:
Master advanced prompting for complex business problems. Develop skills in multi-step reasoning, self-correction, and embedding logic in prompt workflows to maximize LLM performance.
Robust RAG Systems & Context Engineering for Enterprises:
Build production-grade RAG systems using frameworks like LlamaIndex and LangChain. Master context and memory engineering to enhance LLM accuracy and minimize hallucinations.
Mastering Frameworks for AI Applications:
Learn to select best framework (Google ADK, OpenAI SDK, CrewAI, LangGraph) for creating production-ready AI applications. Build strong understanding of RAG, Agentic RAG, and multi agent systems for different use cases.
Scalable Microservices Architecture:
Understand and implement microservices principles essential for building distributed, resilient, and highly scalable AI applications that can handle enterprise-level loads.
Hands-on deployment across diverse environments:
Acquire practical skills deploying containerized AI solutions on enterprise-grade platforms. Gain hands-on experience with Docker and Kubernetes, focusing on GCP and Microsoft Azure ecosystems.
Openshift, NVIDIA AI solutions & security:
Focus on industry-standard platforms and technologies such as Openshift, and NVIDIA solutions for optimized AI computation, all while embedding security best practices throughout the application lifecycle.
Build collaborative, and advanced multi-agent systems:
Design and construct enterprise-ready AI systems where multiple specialized agents collaborate to achieve complex objectives. Master agent orchestration, communication protocols, and intelligent model routing to select the best LLM for any given task.
12-Factor Agent for Production Readiness:
Apply our proprietary "12-Factor Agent" methodology. Learn to evaluate agent response with observability and evaluation metrics. Implement robust monitoring, logging, and feedback loops to track agent performance, latency, and accuracy, ensuring your AI applications are reliable and maintainable.
Participants working closely with our experts will design, develop, and deploy a complete production ready AI/GenAI solution.
A significant portion of the program and case studies are tailored to address the unique needs and challenges of the industries.
Programming & Development, AI Development Tools, Backend-as-a-Service (BaaS), AI Models, AI CLIs, Agentic AI & RAG, Infrastructure, Network & Security, Cloud Providers, and Advanced Enterprise AI platforms.
