learn Gen AI
6 months
(3 hours/day)
44 students/ class
₹ 45,000
(Books are included)
course syallabus
Introduction
Generative Artificial Intelligence (Gen AI) refers to a class of AI models designed
to generate new content, such as images, text, music, or even video, based on
learned patterns from existing data. Unlike traditional AI, which focuses on
recognizing patterns or classifying data, generative AI creates novel outputs
that mimic human creativity. Some of the most prominent examples of generative
AI include language models like GPT, image generation tools like DALL-E, and music
composition algorithms.
This course provides an in-depth understanding of generative models, including the
principles behind Generative Adversarial Networks (GANs), Variational Autoencoders
(VAEs), and transformer-based models like GPT. Participants will gain practical
experience in building and training generative models for various applications,
including natural language processing (NLP), computer vision, and creative arts.
By the end of the course, you will be equipped with the skills to create AI-driven
content generators, which are increasingly in demand in fields like marketing,
entertainment, and technology.
Objectives
After this course student will be able to:
- Understand the fundamentals of Generative AI and its applications.
- Learn the architecture and workings of Generative Adversarial Networks (GANs).
- Explore Variational Autoencoders (VAEs) and their use in data generation.
- Gain proficiency in training and fine-tuning large language models like GPT.
- Learn how to use transformers for natural language generation tasks.
- Understand deep learning techniques for generating images and videos.
- Implement creative AI models for music, art, and other creative domains.
- Explore reinforcement learning in the context of generative AI.
- Study the ethical and societal implications of generative models.
- Learn how to deploy and integrate generative models into real-world applications.
Certification
After this course Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmodc illum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
Who can apply for this course?
- AI researchers or practitioners looking to explore the generative capabilities of AI.
- Data scientists and machine learning engineers seeking to specialize in generative models.
- Software developers and engineers who want to integrate generative AI into applications.
- Professionals in creative industries (art, music, and marketing) who want to harness AI for content creation.
- Students or graduates in computer science, engineering, or related fields interested in AI.
- Entrepreneurs looking to develop AI-driven products or services.
Training Methodology
- Instructor-Led Sessions: Live, interactive lessons covering the theory and practical applications of generative models.
- Hands-On Practice: Work with real-world datasets to train and evaluate generative models.
- Tool Training: Learn how to use popular frameworks such as TensorFlow, PyTorch, and OpenAI's GPT models.
- Case Studies: Study successful generative AI applications in fields like gaming, art, and business.
- Assessments: Periodic quizzes and coding assignments to ensure comprehension of key concepts.
- Capstone Project: Build and deploy a generative model for a specific task, such as generating text, images, or music.
- Peer Collaboration: Collaborate with fellow learners to share ideas, feedback, and improve your projects.
