Advanced Generative AI and Agentic AI Training in Mumbai equips professionals with LLM, multi-agent, and production AI skills for real-world enterprise deployment.
Level
Advanced
Duration
8 Weeks
Placement Client
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About Advanced Generative AI And Agentic AI Training In Mumbai
Advanced Generative AI and Agentic AI Training in Mumbai prepares professionals to design, build, and deploy enterprise-grade AI systems using large language models and multi-agent architectures. Mumbai, as India’s financial and technology powerhouse, hosts BFSI firms, startups, and global IT companies actively adopting AI-driven automation. This training covers LLM fundamentals, prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, multi-agent orchestration, model optimization, and production deployment strategies. Learners gain hands-on experience with real-world use cases, scalability planning, and AI security best practices, enabling them to deliver high-impact AI solutions in Mumbai’s competitive enterprise market.
Training Plan
About trainer
Working professional who is carrying more then 10 years of industry experience.
Decks & Updated Content
Access to updated presentation decks shared during live training sessions.
e-Book
E-book provided by TechPratham. All rights reserved.
Assignments & MCQs
Module-wise assignments and MCQs provided for practice.
Video Recording
Daily Session would be recorded and shared to the candidate.
Projects
Live projects will be provided for hands-on practice.
Resume Building
Expert-guided resume building with industry-focused content support.
Interview Preparation
Comprehensive interview preparation with real-time scenario practice.
Advanced Generative AI And Agentic AI Training In Mumbai Course Curriculum
Testing Dockerized LangGraph Solutions
An overview of validating and testing LangGraph applications running in Docker to ensure reliability, scalability, and smooth deployments.
Introduction to Kubernetes (K8s)
A beginner-level overview of Kubernetes for orchestrating, scaling, and managing containerized applications in production environments.
Deploying LangGraph in K8s
An overview of deploying and managing LangGraph-based AI workflows on Kubernetes for scalable and resilient production setups.
AutoGen on Kubernetes
A concise overview of deploying and scaling AutoGen-based multi-agent systems on Kubernetes for production-ready AI workloads.
Azure Cloud Deployment
An introduction to deploying, managing, and scaling applications on Microsoft Azure using secure, reliable cloud services.
AWS Cloud Deployment
An introduction to deploying, managing, and scaling applications on Amazon Web Services using secure, scalable, and cost-effective cloud infrastructure.
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Who Should Take Advanced Generative AI And Agentic AI Training In Mumbai
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Working Professionals
Ops/Administrators/HR
Developers
BA/QA Engineers
Cloud / Infra
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Job Roles For Advanced Generative AI And Agentic AI Training In Mumbai
NLP Engineer
ML Ops Engineer
AI Systems Architect
AI Platform Engineer
AI Research Engineer
AI Solutions Architect
LLM Application Engineer
Senior Machine Learning Engineer
NLP Engineer
ML Ops Engineer
AI Systems Architect
Key Projects
Advanced Generative AI And Agentic AI Training In Mumbai
AI-Powered Code Generation & Review Assistant - (Navi Mumbai)
In this project, learners build an intelligent AI system that generates, reviews, and optimizes code using large language models. The system supports automated debugging, documentation generation, and code quality improvement, reflecting real-world developer productivity tools used in modern tech companies. • Design prompt pipelines for structured code generation and refactoring. • Implement automated bug detection and logic validation workflows. • Integrate version control APIs for code review automation. • Measure accuracy, security risks, and performance optimization metrics.Key Highlights:
Conversational AI with Long-Term Memory & Context Awareness- (Andheri)
Develop an advanced conversational AI system capable of maintaining long-term memory and contextual understanding across sessions. This project focuses on building scalable, enterprise-ready AI assistants for customer support, knowledge management, and business automation. • Implement vector-based memory storage and retrieval mechanisms. • Design contextual reasoning pipelines for multi-turn conversations. • Reduce hallucinations using grounding and validation techniques. • Deploy a scalable chatbot architecture with monitoring tools.Key Highlights:
Agentic AI for Data Analysis & Automated Decision Systems (Powai)
In this project, learners create an autonomous AI agent that performs data analysis, generates insights, and makes structured decisions. The system can fetch data, run analytics scripts, and generate reports without human intervention, simulating enterprise AI automation workflows. • Build AI agents capable of tool usage and task orchestration. • Integrate Python-based analytics and visualization pipelines. • Automate report generation with structured reasoning outputs. • Optimize reliability, latency, and decision accuracy benchmarks.Key Highlights:
Placement Process
Live Class with Industry Use Cases
- Interactive learning
- Real-world examples
- Expert guidance
- Doubt resolution
Daily Assignment & Weekly Assessments
- Hands-on practice
- Concept reinforcement
- Weekly evaluation
- Timely feedback
Project Testing & Deployment
- Project development
- Testing practice
- Deployment exposure
- Portfolio creation
Interview Preparation (Mock, PD, Alumni Session)
- Mock interviews
- Personal development
- Alumni guidance
- Confidence building
Resume Building
- Resume crafting
- Industry-focused format
- Skills highlighting
- Professional presentation
Placement
- Job assistance
- Interview support
- Career guidance
- Opportunity access
Knowledge Center
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Course FAQs
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