GenerativeAI Training – Course Contents

Generative AI Training

Contact:
    +1 (732) 245-1325
    +91 6281 405276
     ramesh@vigilantcorpinc.com

16 Modules 40+ Hours ● Online
Course Content
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Module 1: Python Programming
Topics:
  • Introduction to Python & Setup
  • Variables, Data Types & Operators
  • Conditional Statements & Loops
  • Functions, Modules & Packages
  • Lists, Tuples, Sets & Dictionaries
  • File Handling & Exception Handling
  • Python Library – Pandas
Programs:
  • Writing a "Hello World" script
  • Writing basic scripts using Conditions/Loops
  • Reading/Writing files
  • Manipulating lists and dictionaries
  • Reading and processing (Joins, Aggregates etc) Excel and CSV files
  • Database programming in Python using MySQL
  • UI(Frontend) design - streamlit library
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Module 2: Introduction to Generative AI
Topics:
  • What is Artificial Intelligence vs Machine Learning vs Deep Learning
  • Evolution of Generative AI (Rule-based → Neural Networks → Transformers)
  • Discriminative vs Generative Models
  • Types of Generative Models (Text, Image, Audio, Video, Code)
  • GANs vs VAEs vs Transformers
  • Real-world GenAI Applications (Chatbots, Content Generation, Automation)
  • Ethical AI & Responsible AI principles
  • AI Myths vs Reality
  • Current Industry Trends in GenAI
Explore:
  • Exploring ChatGPT, Gemini, Groq and Anthropic Claude
  • Exploring Flow, Whisk, Leonardo, suno and eleven labs
  • Comparing outputs across different GenAI tools
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Module 3: Overview of Models
Topics:
  • Machine Learning model lifecycle
  • Supervised, Unsupervised & Reinforcement Learning
  • Neural Networks fundamentals
  • Transformers Architecture (Attention Mechanism explained clearly)
  • Encoder vs Decoder models
  • Diffusion models basics
  • Model selection strategies
  • Fine-tuning vs Prompt-based optimization
Presentation:
  • Visualizing Transformer architecture
  • Evolution of Generative AI
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Module 4: Prompt Engineering (Beginner to Advanced)
Topics:
  • What is Prompt Engineering?
  • Zero-shot, One-shot, Few-shot prompting
  • Chain-of-Thought prompting
  • Role prompting techniques
  • Prompt Templates & Structure
  • System vs User vs Assistant prompts
  • Prompt Optimization techniques & evaluation methods
Programs:
  • Writing prompts for Chatbots & Resume Screening
  • Code Generation & Test Case Generation prompts
  • Marketing Content prompt design
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Module 5: Content Generation
Topics:
  • Text to Speech Conversion
  • Audio to Text
  • Text to Music
  • Text to Image
  • Text to Video
  • Image to Video
Demonstration:
  • Groq and Gemini
  • suno, Eleven Labs
  • Flow, Leonardo
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Module 6: Python for Generative AI
Topics:
  • Python fundamentals refresher
  • Virtual environment setup
  • Working with APIs using requests
  • JSON handling
  • Pydantic BaseModel usage (practical examples)
  • Error handling in AI apps
  • Async programming basics
  • File handling for document ingestion
Programs:
  • Creating mini GenAI projects in Python
  • Building a simple AI-powered CLI script
  • Reading and processing CSV/PDF files with Python
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Module 7: Large Language Models (LLMs)
Topics:
  • What are LLMs?
  • How LLMs are trained (Pretraining & Fine-tuning)
  • Tokenization explained
  • Embeddings explained
  • Context windows & limitations
  • Popular LLMs: OpenAI, Claude, Gemini, Llama, LangChain
  • LLM safety & alignment
  • LLM limitations and challenges
  • Enterprise LLM adoption
Programs:
  • Running LLMs locally with Ollama
  • Comparing responses across OpenAI, Claude and Gemini
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Module 8: APIs (Application Programming Interfaces)
Topics:
  • What is an API?
  • REST API fundamentals
  • API Authentication (API Keys, OAuth basics)
  • Calling LLM APIs using Python
  • Working with APIs towards the models: OpenAI, Groq, Gemini, Grok etc.
  • Creating character consistency images using Gemini API
  • Error handling best practices
  • Securing API keys
Programs:
  • Calling OpenAI, Gemini & GROQ APIs from Python
  • Building your own AI API endpoint using FastAPI
  • Streaming responses in real time
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Module 9: RAG (Retrieval-Augmented Generation)
Topics:
  • Why RAG is needed
  • Architecture of RAG systems
  • Embeddings & Vector databases
  • Chunking strategies
  • Similarity search methods
  • Indexing documents
  • Hybrid search techniques
  • RAG vs Fine-tuning comparison
  • Production RAG architecture
Programs:
  • Building a RAG pipeline from scratch
  • Querying organization-specific documents with RAG
  • Optimizing retrieval pipeline performance
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Module 10: LangChain
Topics:
  • Introduction to LangChain
  • LangChain architecture
  • Chains & Sequential Chains
  • Prompt templates
  • RAG using LangChain
Programs:
  • Building a conversational AI app with LangChain
  • Creating a multi-step chain pipeline
  • Integrating custom tools into an Agent
  • Integrating RAG applications with Streamlit
  • Multiple Collections in RAG - Choosing at runtime
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Module 11: LlamaIndex
Topics:
  • Introduction to LlamaIndex
  • Data connectors
  • Index types
  • Query engines
  • Advanced retrieval strategies
  • Metadata filtering
  • LlamaIndex + LLM integration
  • Optimizing indexing performance
Programs:
  • Building an enterprise document search assistant
  • Connecting LlamaIndex to private data sources
  • RAG on Web Pages
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Module 12: Agentic AI
Topics:
  • AI Agents (Autonomous systems)
  • Multi-Agent Architectures
  • crewai
  • NoCode Tools - Flowise / n8n
Programs:
  • Building an autonomous AI agent
  • Setting up a multi-agent pipeline
  • Create Project Planning Agent
  • Email Cleanup Agent
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Module 13: Digital Marketing with GenAI
Topics:
  • AI-powered content creation
  • SEO optimization using AI
  • Blog & social media automation
  • AI Ad copy generation
  • YouTube script & thumbnail generation
Demonstration:
  • Character Consistency videos
  • Producing YouTube scripts and thumbnails using GenAI tools
  • Working with Leonardo, Flow, suno.com and ElevenLabs
  • Creating an AI-written email campaign
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Module 14: GenAI Use Cases / Case Studies
Industry Case Studies:
  • AI Test Case Generator
  • Requirement Validator
  • Customer Support Chatbot (RAG based)
  • AI-powered Knowledge Base
  • Trip Planner
  • Weather API
  • HR Interview Assistant
  • Healthcare Assistant (Conceptual)
Capstone Projects:
  • Build Enterprise RAG Application
  • Resume Validator & Ranking System
  • Build Multi-Agent AI System
  • Build AI SaaS Product (Mini Version)
  • Deploy AI app to cloud
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Module 15: GenAI on Cloud
Topics:
  • Amazon Bedrock
  • Models - Anthropic Claude, Meta Llama, Mistral AI, Cohere, Stability AI and Amazon Titan
  • API calls and boto3
  • anthropic.claude-3-haiku-20240307-v1 / openai.gpt-oss-20b-1
  • bedrock-runtime
Programs:
  • Build GenAI application using Cloud models
  • Writing files to S3
  • Hosting GenAI applications on aws EC2
  • Langchain aws library
  • VectorDB on Cloud
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Module 16: Production Deployments
Topics:
  • Github Integration and Git Clone
  • Configuring Amazon EC2 Instance
  • CI/CD Pipelines
  • Deploy GenAI Application on EC2
  • Virtual Environments on Cloud
  • Task Monitoring/Logs

Trainer Profile

Mr. Ramesh Kandukuri will be leading the Generative AI training program. He brings over 25 years of IT experience in the United States, specializing in data technologies and advanced enterprise solutions.

Throughout his career, he has held roles such as Database Developer, Database Administrator, Data Warehouse Engineer, Solution Architect, and Data Integration Specialist. He has successfully contributed to several large-scale data and application migration projects.

His domain expertise spans:

  • Financial Services (Investment Banking, Retail Banking, Anti-Money Laundering)
  • Pharmaceuticals
  • Sales

In addition to his professional achievements, Mr. Kandukuri has conducted over 200 training batches across technologies such as:

  • Generative AI
  • Snowflake
  • Python
  • Unix Shell Scripting
  • SAP
  • Informatica
  • Business Objects
  • Cognos

With his vast industry expertise and proven training experience, he is well-equipped to mentor learners in mastering the fast-evolving field of Generative AI.

Contact Trainer at:
   +1 (732) 245-1325  |  +91 6281 405276  |  ramesh@vigilantcorpinc.com

Register For Training

Join our Generative AI program and unlock the power of cutting-edge AI technologies.


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