Generative & Agentic AI
Learning Format
Online Mode
Total Training Duration
200 Hrs
Duration
4 Month
Certification
Yes
Generative & Agentic AI Course in PCMC Pune
Generative AI Course in PCMC Pune
Take your AI knowledge to the next level with the Generative AI Course in PCMC Pune offered by IntelliBI Innovations Technologies. This advanced program helps students and professionals master the latest techniques in Generative Artificial Intelligence, including GANs, VAEs, and prompt engineering. You’ll learn how to build, fine-tune, and deploy AI applications using OpenAI, Hugging Face, and other modern tools. The course also covers data science foundations, deep learning, NLP with transformers, and deployment using Flask and Docker. Through hands-on projects and mini-capstones, you’ll gain practical experience in building real-world AI solutions that go beyond theory.
Agentic AI Course in PCMC Pune
The Agentic AI Course in PCMC Pune focuses on the next generation of AI systems—intelligent agents capable of reasoning, automation, and decision-making. You’ll explore tools like LangChain, CrewAI, and AutoGen to design agent-based workflows and retrieval-augmented generation (RAG) systems. The curriculum also includes modules on embeddings, vector databases, and hybrid RAG pipelines, along with fine-tuning large language models (LLMs) using LoRA and RLHF. With project-based learning and expert mentorship, this course helps you develop skills to build and deploy autonomous AI agents used in industries like finance, healthcare, and customer support.
At IntelliBI Innovations Technologies, we provide flexible Online IT Courses in PCMC Pune with practical learning, expert guidance, and real-time projects. Whether you want to become an AI engineer, data scientist, or automation specialist, these courses prepare you for the fast-evolving AI job market.
Course Summary
Eligibility
Tech & Non-Tech Working professional, Freshers, Graduate from any domain.
Real time projects
Gain hands-on experience through projects that simulate real-world challenges, preparing you for a career in analytics.
Dedicated Profile Building
Along with learning, we help you with ATS resume building and LinkedIn profile optimization
Hands-on Industry Relevant Casestudies
Complete guidance for 25+ Assignments and case studies to help you gain the hands-on experience.
Live Doubt Solving
Get your queries solved with daily dedicated doubts solving sessions.
800+ Companies
Connect with top employers
Certification
10+ ISO Globally recognized certified
LMS Access for 2 Years
Get course recording access for 2 years after course completion.
Aspirational peer group
10K+ students & alumni across diverse domains. Dedicated Telegram virtual classroom for peer-to-peer support.
Instructor
Experts and trainer for top-tech companies.
Direct CRM Calls
Get shortlisted instantly
GitHub Enhancement
Showcase coding skills
Al Mock
Interviews Practice and improve with Al feedback
Placement Assistance Until Placed
Along with up skilling and preparing you for the job, we also help you for your search & your interview.
Mode of Learning
100% Live Learning Learn directly from experienced instructors in Live sessions, with an emphasis on practical, hands-on learning.
Program Name
LinkedIn Optimization
Program Duration
Eligibility
Real time projects
Dedicated Profile Building
Live Doubt Solving
800+ Companies
Certification
LMS Access for 2 Years
Aspirational peer group
Hands-on Industry Relevant Casestudies
Instructor
Direct CRM Calls
GitHub Enhancement
Al Mock Interviews
Mode of Learning
Placement Assistance Until Placed
Syllabus Summary
A Comprehensive Curriculum Designed for Real-World Success
- Week 1: Intro to Data Science – lifecycle, tools (Jupyter, Git).
- Week 2: Python for DS – NumPy, Pandas, file handling. Ο
- Week 3: Data Exploration & Viz EDA, dashboards.
- Week 4: Probability & Stats distributions, hypothesis testing.
- Week 5: ML Basics regression, classification, clustering.
- Week 6: Advanced ML + Deployment – ensembles, neural nets, Flask/Docker.
Mini-Capstone 1: House Price Predictor (EDA + regression, Flask API, Dockerized).
- Week 7: Neural Nets perceptrons, activation, backprop.
- Week 8: NLP Basics tokenization, embeddings, preprocessing.
- Week 9: Sequence Models → RNNs, LSTMs, sentiment analysis.
- Week 10: Transformers – attention, encoder-decoder, Hugging Face.
- Week 11: Fine-tuning Transformers – LoRA/PEFT, task-specific NLP.
- (Weeks 7-11)
Mini-Capstone 2: Sentiment Classifier (Fine-tune Transformer + deploy with
FastAPI/Spaces).
- Week 12: Intro to GenAI – GANs, VAEs, transformers, applications.
- Week 13a: API Integration → OpenAl, Hugging Face.
- Week 13b: Local Deployment – Ollama, vLLM, open-source models.
- Week 14: Prompt Engineering→ zero/few-shot, CoT,evaluation.
- Week 15: Responsible Al → bias, fairness, hallucination reduction.
Mini-Capstone 3: Customer Support Chatbot (API or local LLM + prompt library).
- Week 16: Embeddings & Vector DBs → FAISS, Pinecone, semantic search.
- Week 17: RAG Pipelines -→ LangChain, hybrid RAG, knowledge graphs.
- Week 18: Agentic Al LangChain Agents, CrewAI, AutoGen, memory systems.
- Week 19: LLM Fine-Tuning → LoRA, RLHF, evaluation methods.
Mini-Capstone 4: Enterprise RAG Assistant (LangChain + Vector DB + CrewAl agents).
- Week 20: Cloud Deployment – Docker, Kubernetes, AWS/GCP.
(Weeks 20-24) - Week 21: GenAI MLOps + Security – CI/CD, MLflow, monitoring, agent security.
- Weeks 22-23: Multimodal GenAI → CLIP, Stable Diffusion, text-image pipelines.
- Week 24: Final Capstone Prep choose project, deploy end-to-end.
Mini-Capstone 5: Cloud-Deployed GenAl Service (CI/CD + monitoring).
- RAG Assistant – Knowledge search + retrieval
- Multi-Agent Al Assistant – Workflow automation with agents
- Multimodal Search Engine – Text + image retrieval
- Workflow Automation Agent – Jira/Slack/CRM integration
- Healthcare Al Assistant – Summarize & assist with records
- Cloud deployment (Docker/K8s + CI/CD)
- Demo presentation + GitHub repo
- Documentation with real-world use case
- Portfolio-grade project aligned with
GenAl Engineer → Al Solutions Architect roles.
Syllabus Summary
A Comprehensive Curriculum Designed for Real-World Success
- Week 1: Intro to Data Science – lifecycle, tools (Jupyter, Git).
- Week 2: Python for DS – NumPy, Pandas, file handling. Ο
- Week 3: Data Exploration & Viz EDA, dashboards.
- Week 4: Probability & Stats distributions, hypothesis testing.
- Week 5: ML Basics regression, classification, clustering.
- Week 6: Advanced ML + Deployment – ensembles, neural nets, Flask/Docker.
Mini-Capstone 1: House Price Predictor (EDA + regression, Flask API, Dockerized).
- Week 7: Neural Nets perceptrons, activation, backprop.
- Week 8: NLP Basics tokenization, embeddings, preprocessing.
- Week 9: Sequence Models → RNNs, LSTMs, sentiment analysis.
- Week 10: Transformers – attention, encoder-decoder, Hugging Face.
- Week 11: Fine-tuning Transformers – LoRA/PEFT, task-specific NLP.
- (Weeks 7-11)
Mini-Capstone 2: Sentiment Classifier (Fine-tune Transformer + deploy with
FastAPI/Spaces).
- Week 12: Intro to GenAI – GANs, VAEs, transformers, applications.
- Week 13a: API Integration → OpenAl, Hugging Face.
- Week 13b: Local Deployment – Ollama, vLLM, open-source models.
- Week 14: Prompt Engineering→ zero/few-shot, CoT,evaluation.
- Week 15: Responsible Al → bias, fairness, hallucination reduction.
Mini-Capstone 3: Customer Support Chatbot (API or local LLM + prompt library).
- Week 16: Embeddings & Vector DBs → FAISS, Pinecone, semantic search.
- Week 17: RAG Pipelines -→ LangChain, hybrid RAG, knowledge graphs.
- Week 18: Agentic Al LangChain Agents, CrewAI, AutoGen, memory systems.
- Week 19: LLM Fine-Tuning → LoRA, RLHF, evaluation methods.
Mini-Capstone 4: Enterprise RAG Assistant (LangChain + Vector DB + CrewAl agents).
- Week 20: Cloud Deployment – Docker, Kubernetes, AWS/GCP.
(Weeks 20-24) - Week 21: GenAI MLOps + Security – CI/CD, MLflow, monitoring, agent security.
- Weeks 22-23: Multimodal GenAI → CLIP, Stable Diffusion, text-image pipelines.
- Week 24: Final Capstone Prep choose project, deploy end-to-end.
Mini-Capstone 5: Cloud-Deployed GenAl Service (CI/CD + monitoring).
- RAG Assistant – Knowledge search + retrieval
- Multi-Agent Al Assistant – Workflow automation with agents
- Multimodal Search Engine – Text + image retrieval
- Workflow Automation Agent – Jira/Slack/CRM integration
- Healthcare Al Assistant – Summarize & assist with records
- Cloud deployment (Docker/K8s + CI/CD)
- Demo presentation + GitHub repo
- Documentation with real-world use case
- Portfolio-grade project aligned with
GenAl Engineer → Al Solutions Architect roles.
Top Hiring Industries in India
Career Support Services
Resume Building
Linkedin Optimaztion
Access To Job Board
Interview Calls
GitHub Portfolio
IntelliBI Azure Data Engineering Certification
Course Highlights
- Course Duration
- 250+ Hours /
- 4 Months
-Pre-Class-
-Pre Career Counseling,
-Technical Evaluation
-Sessions- Technical,
-Softskill, Mentor,
-E-Consultation.
-Technical
-Assignments
-300+ Case Studies
-Industry Real
-World Project 4
-Mock Interviews 5
-Student Internship
-Dashboard
-Resume Preparation,
-Interview Guidance
-Job Readiness,
-Placement support
Our Learners Got Assured Placement. So Can You!
Students reviews
Real stories. Real success.
Real students.
