Class / Class Details

Generative AI Learning

  • Sateesh image

    By - Sateesh

  • 0 students
  • 1 Hour
  • (0)
Start Date & Time

2nd Nov, 2024 At 11:26 AM

End Date & Time

1st Feb, 2025 At 12:26 PM

Duration

N/A

Course Description

Course Description:

This course provides an in-depth exploration of Generative AI, covering the foundational theories, practical applications, and latest advancements in the field. You’ll learn how generative models create realistic data, images, text, and other outputs through AI-powered techniques. By the end, you will have a solid foundation in Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer models, and you’ll gain hands-on experience building and deploying models for a wide range of applications.

Prerequisites:

  1. Mathematics Fundamentals: Basic knowledge of linear algebra, calculus, and probability.
  2. Programming Experience: Proficiency in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch).
  3. Introduction to Machine Learning: Prior understanding of core machine learning concepts, such as supervised and unsupervised learning, is helpful but not required.

Course Outcomes:

  1. Understand Generative AI Fundamentals: Identify the differences between various generative models, including GANs, VAEs, and transformer-based models.
  2. Build and Implement Generative Models: Gain hands-on experience in constructing and training GANs, VAEs, and text generation models.
  3. Customize and Deploy Models: Learn how to fine-tune models for specific tasks, enabling practical deployment in applications like image generation, natural language processing, and creative AI.
  4. Develop a Portfolio of Projects: Complete assignments that demonstrate your proficiency in generative modeling.
  5. Practice Ethical and Responsible AI Use: Understand the ethical implications of generative AI and apply best practices for safe and responsible use.

Course Schedule

Instructor

Sateesh

Sateesh A, bringing extensive expertise in AI-driven healthcare solutions. With a background in Engineering (B.E., M.Tech., and Ph.D. in AI for Healthcare), Sateesh has over two decades of experience in technology innovation, spanning roles in top organizations like Samsung, Intel, and Sandisk.


His work focuses on developing advanced AI models for healthcare, including federated learning frameworks, synthetic data generation, and explainable AI models for predictive healthcare applications.


Sateesh has led multiple groundbreaking research projects, authored numerous publications, and presented at international conferences, advancing the field of adaptive, teacher-less education platforms. His vision is to make high-quality education accessible to remote regions through AI, helping learners achieve employability and lifelong learning.


Sateesh’s achievements include recognition as a top tech innovator, participation in elite accelerator programs, and collaboration with esteemed institutions like Stanford, IIIT-B, and IIM-A.

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