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Generative AI Accelerated Course

person icon Vivian Aranha

4.7

Generative AI Accelerated Course

Start with an introduction to Generative AI Fundamentals and learn tools and practical skills

updated on icon Updated on Jun, 2025

language icon Language - English

person icon Vivian Aranha

category icon Development ,Data Science,Generative AI

Lectures -8

Duration -26 mins

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4.7

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Course Description

Welcome to the world of Generative AI! In this comprehensive crash course, we will embark on an exciting journey into the realm of artificial intelligence that enables machines to generate new and original content across various domains. Generative AI has revolutionized creative expression, content generation, and data augmentation, opening up endless possibilities for innovation and exploration.

Generative AI refers to a class of algorithms designed to create new data that resembles the patterns and characteristics of the input data it was trained on. Whether it's generating realistic images, composing music, or writing text, generative AI allows machines to exhibit creativity and produce content that is indistinguishable from human-generated content. Through the use of deep learning techniques and neural networks, generative models learn to understand the underlying structure of the data and generate new samples that exhibit similar properties.

Whether you're a seasoned AI practitioner or a curious beginner, this crash course will provide you with the knowledge, tools, and resources you need to dive into the fascinating world of generative AI. So let's embark on this journey together and unlock the boundless potential of AI-driven creativity and innovation. Welcome to the world of Generative AI!

Goals

Introduction to Generative AI Fundamentals

  • Begin with the basics of generative AI.
  • Explore different generative models: GANs, VAEs, RNNs, and Transformers.
  • Understand foundational principles for further exploration.

Applications of Generative AI

  • Generative AI's impact across various domains.
  • Applications include generating realistic images, synthesizing music, creating lifelike characters, and building virtual environments.
  • Real-world examples and case studies demonstrating AI's role in solving complex problems and driving innovation.

Ethical Considerations and Challenges

  • Discuss challenges such as mode collapse, training instability, and the misuse of AI-generated content.
  • Emphasize the importance of ethical decision-making in AI development.
  • Explore strategies for promoting responsible AI practices.

Tools and Practical Skills

  • Equip yourself with tools like TensorFlow, PyTorch, GANLib, and pre-trained models like the GPT series.
  • Engage in hands-on experimentation to gain practical experience in building and training generative AI models.

Prerequisites

  • None
Generative AI Accelerated Course

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction to Generative AI

2 Lectures
  • play icon Welcome 03:52 03:52
  • play icon Introduction To Generative AI 01:59 01:59

Types of Generative AI

1 Lectures
Tutorialspoint

Applications of Generative AI

1 Lectures
Tutorialspoint

Challenges in Generative AI

1 Lectures
Tutorialspoint

Tools and Frameworks

1 Lectures
Tutorialspoint

Getting Started

1 Lectures
Tutorialspoint

Thank you

1 Lectures
Tutorialspoint

Instructor Details

Vivian Aranha

Vivian Aranha

After completing my Master's in Computer Science at George Washington University, started working on Web and Mobile Applications. Have been training people in Mobile Technologies since 2009 in both iOS and Android Technology.

Been building Mobile Apps and Websites since 2002 for brands like Delta Air Lines, The Washington Post, Cars, Kaplan, and many more. Have more than 150 mobile applications of my own.

Hands-on experience architecting, developing, and publishing apps since 2009.

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