| Course # | Gen AI Course Content | Generative AI Course Content & Hours |
| | Topic Heading | Topic Description | Hrs |
| 1 | Book a FREE Generative AI Introduction and POWER CHAT Demo/Discussion Session. | Email us at manager@PowerGenAI.us, and we will respond within 48 hours to arrange a discussion with our experts at a time that suits your schedule and aligns with your requirements.” | 1 |
| 2 | Gen AI & AI Introduction | Introduction to Course + What is Data Science, Gen AI, AI & ML | 2 |
| 3 | Infrastructure, AI Platform, Tools & Techniques | Gen AI Infrastructure, Cloud Intro (Azure, AWS, Azure, IBM) Architecture & Components, Tools, Techniques & Frameworks | 2 |
| 4 | AI Strategy | Gen AI Strategy, AI CoE, AI Factory | 4 |
| 5 | Responsible AI | Responsible AI & Risk Management Framework | 1 |
| 6 | AI Approach | Gen AI Implementation Approach: Phases, Stages, Milestones & Deliverables | 1 |
| 7 | AI Offerings | Gen AI Offerings & Portfolio: Objective, Use Cases, Tools, Techniques, Frameworks, Deliverables and Q&A | 1 |
| 8 | Python | Python (Simple Data Types , List, Set, Tuples, Dictionary, Loop , Functions, Classes, Array) | 4 |
| 9 | Data Management | Data Processing Using Python (Ingestion, SQL, Panda, Visualization, Quality, Transformation, Analysis, Visualization, Integration, Labeling, Featuring etc.) | 4 |
| 10 | Gen AI Architecture | Gen AI MS Azure End-2-End Architecture & Components Walkthrough | 2 |
| 11 | Azure AI Platform | MS Azure ML Configuration (Azure AI & Open AI Services, ML Studio, Open AI, Flows) | 6 |
| 12 | Azure AI / Local Dev Env. Setup | Generative AI: Development Environment Setup | 2 |
| 13 | Python/PyTorch/Tensorflow | PyTorch & ML & Deep Learning (Data Prep, Libraries, Model, LLM, Algorithm (Classification, Regression, etc.) | 6 |
| 14 | LLM Transformer Architecture | Model/LLM: Creating, Training, Testing, Validation, Finalize, EndPoint,Deployment, Use | 2 |
| 15 | LLM Learning | Understand Learning: Supervised, Un-supervised, Re-Reinforcement, Clustering etc. | 2 |
| 16 | LLM Conceptualization | LLM Conceptualization: Architecture, Text-2-Text, Text-2-Image, Text-2-Speech, Speech-2-Text etc. | 2 |
| 17 | LLM Accuracy | Metrics: Evaluation and Accuracy Metrics etc., How to check LLM Accuracy? | 2 |
| 18 | LLM Evaluation Metrics | LLM Evaluation: How to Select LLM by Use Cases | 2 |
| 19 | Data Preparation using LLM | Data Preparation using LLM (Quality, Labeling etc.) | 2 |
| 20 | Prompt Engineering/Template | Prompt Designing, Engineering & Template | 2 |
| 21 | Prompt Tuning / Soft Tunning / Fine-tuning/TL | Training LLM using Prompt Tuning, Soft Tuning, Fine-tuning, Transfer Learning | 2 |
| 22 | Governance: AI Security / Provacy | Gen AI Security: Guardrails, Encryption, VN, Certificates etc. | 2 |
| 23 | Gen AI App Building | Infrastructure, AI Platform, Tools, Techniques, Framework, Langchain, Agents | 6 |
| 24 | Open AI LLMs | Open AI Platform and Proprietary LLMs | 2 |
| 25 | Huggingface & LLMs | Huggingface Platform and Open Source LLMs | 2 |
| 26 | RAG, Langchain, Agents | RAG Architecture, Langchain, Vectors, Index, Agents, Chains, Retrieval etc. | 8 |
| 27 | Inferenecing / Deployment | Gen AI: Deployment, Monitoring, Maintenance & Optimization using Azure AI | 2 |
| 28 | MMO | Maintenance, Monitoring and Optimization | 2 |
| 29 | Gen AI Solution: Website Chatbot | Solution to implement Chatbot with Website | 4 |
| 30 | Gen AI Solution: Documents Chatbot | Solution to implement Chatbot with Documents | 2 |
| 31 | Gen AI Solution: Database Chatbot | Solution to implement Chatbot with Database / RDBMS | 2 |
| 32 | Gen AI Solution: Knowledge Graph | Understand Chatbot with multiple Databases using Knowledge Graph Neo4J | 2 |
| 33 | Gen AI Solution: Automation | Solution for automating manual repetitive tasks | 1 |
| 34 | Gen AI Solution: Code Generation, Debugging | Solution to write Code / Debugging using LLM | 1 |
| 35 | Gen AI Project | Generative AI: Gen AI Project/Product Building – Chatbot Development and Deployment | 3 |
| 36 | Gen AI Advisory | Gen AI Advisory: Resume Preparation, Mock Interviews, Practical Projects, Guidance for Interviews & Projects, Placement etc. | 6 Weeks |
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| | | Total | 90 |
