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Certified Generative AI expert course
Rating: 4.4 out of 5(25 ratings)
53 students

Certified Generative AI expert course

Generative AI, Chatgpt, diffusion model, Gen- AI for text and Image,Gen-AI application, prompt engineering,Data privacy
Last updated 12/2024
English

What you'll learn

  • Basics of Generative AI
  • The difference between Generative AI and NO generative AI
  • Generative AI use in different industry sectors
  • Generative AI text generation
  • Generative AI stable diffusion
  • Challanges for Image generation using generative AI
  • Compelete GEN AI sturucture
  • Gen AI application for public service,Healthcare, Tourism, Education
  • How to do data privacy in Gen-AI
  • Gen-AI for text , information , code generation
  • Gen AI for question Answering
  • Upcoming trends for generative AI
  • Machine learning basics, Supervised, Unsupervised learning
  • advantages & disadvantages of ML
  • ML life cycle, Exploratory data analysis , ML Challenges and libraries
  • Generative Adversarial Network (GAN) and its application
  • Variational Autoencoders, Transformers and its application
  • Convolutional Neural Network , Expert systems, Recurrent neural networks
  • Generative AI tools (Alphacode, DALL E2, DUET AI, GIThub Copiolet, ChatGPT4 etc.)
  • Prompt Engineering for Text Analysis

Course content

14 sections58 lectures7h 45m total length
  • Introudction to generative AI course5:17

    This video tells about topics to covered in Generative AI course.

Requirements

  • Engieer should be aware of basics of machine learning.

Description

This course covers below mentioed topics to be complete generative AI skills:

• Machine learning basics

. Supervised and Unsupervised learning

. Generative Adversarial Network (GAN) and its application

. Variational Autoencoders, Transformers and its application

. Convolutional Neural Network , Expert systems, Recurrent neural networks

. Generative AI tools (Alphacode, DALL E2, DUET AI, GIThub Copiolet, ChatGPT4 etc.)

•Gen-AI basics

•Gen- AI and Non Gen- AI

•Gen-AI applications

•Text Data

•Gen-AT text Intro

•Chatgpt Overview

•Chatgpt - Text generation

•Google bard - Text generation

•Diffusion AI models

•Dream studio platform

•Generating Images with Stable Diffusion

•Editing Images with Stable Diffusion

•Prompt Engineering for Image Generation

•Mitigating Data Leakage using Data Masking

•Using Private Generative AI Models

•Role of Privacy by Design in AI

Aside

Gen AI use in Healthcare, Education, Tourism covered

•Potential Risks to Data Privacy in AI

•Mitigating Data Leakage using Data Masking

•Using Private Generative AI Models

•Role of Privacy by Design in AI

•Implementing a Data Privacy Culture


Genertive  experts have good skills  to  create, innovate, and generate content. They have a deep understanding of generative models, neural networks, machine learning algorithms, and other advanced techniques that enable the creation of novel and creative outputs.

Generative AI creates new content, like text or images, based on patterns in data. Large Language Models (LLMs) are a powerful form of this AI, generating human-like text, while Small Language Models (SLMs) focus on specialized tasks with less data. Retrieval-Augmented Generation (RAG) enhances these models by pulling in external information for more accurate results.

AI Agents use generative AI to autonomously perform tasks such as writing or research. Together, they represent cutting-edge advancements in automation and creativity.


Who this course is for:

  • Graduates who want to make carieer in generative AI
  • Engineering graduates