Language: English
Created by: Yogesh Raheja, Thinknyx Technologies, Dheeraj Sain
Rate: 4.4 / 19 ratings
Enroll: 3,339 students
What you’ll learn
- AI Branches
- Getting Started with Generative AI
- Prompt Engineering, Anatomy and Framework
- Generative Adversarial Networks (GANs)
- Variational Autoencoder (VAE’s)
- Foundational Models (FMs)
- Large Language Models (LLMs)
- Retrieval Augmented Generation (RAG)
- Trending Handson Use cases for Emails, PDF’s, Text to Image & Video, Music Composition, Power Point Presentations, Designing Brand Logos, Data Analysis and more
- AI – Best Practices
- AWS Bedrock Project
- Capstone Project – Your own GenAI application.
Requirements
- No prior experience is required
- Laptop/Desktop with Internet Connectivity anfd that’s it
Description
What’s Covered in this Course?
The “Generative AI Essentials – Practical Use Cases” course is tailored for learners of all levels, from beginners to seasoned professionals eager to explore the world of Generative AI through effective Prompt Engineering. This course serves as your gateway to mastering generative AI, offering essential concepts and practical, hands-on experience.
We’ll begin with an overview of Generative AI, tracing its evolution within the broader AI ecosystem, and then cover essential GenAI terminologies. Following this, we’ll examine the fundamental concepts of prompt engineering and its best practices. The core of this course is practical use cases—domain-specific scenarios designed to streamline and enhance your daily workflows. We will also address the potential risks and challenges of using Generative AI. Finally, we’ll conclude with an exciting capstone project utilizing AWS Bedrock.
Whether you’re new to AI or have some experience, this course will guide you through foundational concepts and each stage of learning.
What is Generative AI?
Generative AI is a subset of artificial intelligence capable of creating new content, including images, videos, music, text, code, and more. It achieves this by learning from extensive datasets of existing information and leveraging that knowledge to produce fresh, clean, and precise outputs.
Legal Notice:
ChatGPT is an open-source, community-driven software managed by the OpenAI. ChatGPT/OpenAI and the ChatGPT/OpenAI logo are trademarks or registered trademarks of The OpenAI in one or many countries. The OpenAI and other parties may also have trademark rights in other terms used herein. This course is not certified, accredited, affiliated with, nor endorsed by The OpenAI.
Course Structure:
- Lectures
- Demos
- Quizzes
- Assignments
Course Contents:
- Getting Started with GenAI
- GenAI Terminologies:- Generative adversarial networks (GANs)- Variational Autoencoder (VAEs)- Foundational Models (FMs)- Large Language Models (LLMs)- Retrieval Augmented Generation (RAG)
- Prompt Engineering
- Hands-On Use Cases on GenAI Tools & Platforms:- Email Composition- Summarization- Pdf Reader | Chat with PDF- Content Creation: blogs, YouTube video etc- Text to Image- Text to Video- Creating Presentations- Product & Fashion Photo Shoots- Design Your Brand logo- Capture and Share Insights from Virtual Meetings- Coding and Development- Data Analysis- Building Website with Generative AI- Deploying Website with Generative AI
- Responsible Generative AI
- Potential Risks
- Ethical Considerations
- Best Practices
- Capstone Project using AWS Bedrock
All sections of this course are demonstrated live, providing step-by-step guidance to help you set up your local environment, perform all exercises, and learn through hands-on practice.
Who this course is for:
- AI & ML Engineers
- Anyone who wants to get started with AI Ecosystem (AI, ML, DL and Generative AI) Journey
- Aspiring AI/Generative AI Enthusiasts
- Business Professionals and Leaders, Entrepreneurs, CXOs, Business Managers, CHRO’s
- Data Scientists/Data Engineers.
