Generative AI Learning Series
We are doing weekend sessions on Generative AI. If you are looking for free session fill this form and i will be sending you invite.
please follow me you will automatically getting notification for my upcoming session details.
Form link: Contact Information — Google Forms
Gen AI Registration Form
docs.google.com
Facebook link: Facebook
YouTube : SynapseEdge Technology — YouTube
SynapseEdge Technology - YouTube
This channel is dedicated to helping you understand and master Generative AI (GenAI) in a simple, practical, and real-world way. Whether you're a beginner, developer, or working professional, you’ll find valuable content to grow your AI skills. 🔹 What you’ll learn: • GenAI Basics & Fundamentals • LLMs (Large Language Models) explained • Prompt Engineering (Zero-shot, Few-shot, Role-based) • Real-world Use Cases & Projects • AI Tools & Frameworks (OpenAI, LangChain, Semantic Kernel, etc.) • RAG (Retrieval-Augmented Generation) • AI Agents & Automation • .NET + GenAI Integration 💡 Our goal is to make AI easy, practical, and useful for everyone. 📌 New videos every week with hands-on demos, architecture, and real-time examples. 👉 Follow and stay updated with the latest in AI Medium Blog: https://medium.com/@devesh.akgec 🔥 Start your GenAI journey today and build the future with AI!
youtube.com
Topic to cover
Generative AI Basics — Understand what Generative AI is and where it is used.
Large Language Models (LLMs) — Learn how models like GPT work.
Prompt Engineering — Write effective prompts to get better AI responses.
Tokens and Context Window — Understand how AI processes input and output.
OpenAI API Basics — Connect and interact with AI models from applications.
Building AI Chatbots — Create conversational applications using AI.
Chat History & Memory — Make chatbots remember previous conversations.
Structured Outputs — Generate JSON and strongly typed responses from AI.
Embeddings Explained — Convert text into vectors for semantic understanding.
Vector Databases — Store and search embeddings efficiently.
Semantic Search — Find information based on meaning instead of keywords.
RAG (Retrieval Augmented Generation) — Combine AI with your own knowledge base.
OpenAI Vision — Analyze and understand images using AI.
Tool Calling / Function Calling — Allow AI to execute external functions and APIs.
AI Agents — Build systems that can reason and perform tasks autonomously.
Agent Loops — Learn how agents think, act, observe, and repeat.
Multi-Agent Systems — Coordinate multiple AI agents to solve complex problems.
MCP (Model Context Protocol) — Connect AI models with external tools and data sources.
AI Security & Guardrails — Protect applications from misuse and prompt injection.
Enterprise AI Applications — Build production-ready AI solutions using .NET and OpenAI.
Thanks and happy learning.
