Generative-AI
Career Objective
- Gain a solid understanding of the principles and concepts behind Generative AI, including its applications and potential impact across various industries.
- Dive into techniques for generating human-like text, including text generation, summarization, and dialogue systems.
- Gain practical experience in implementing and training generative models using popular frameworks and libraries such as TensorFlow, PyTorch, or OpenAI’s GPT.
Course Instructions
- Follow the course sequence to qualify for the complete course certificate.
- Each module completed individually earns a certificate specific to that module.
- Completing the entire sequence is necessary to obtain the full course certificate.
- Sequential completion ensures thorough learning and mastery.
- Each module certificate acknowledges acquisition of specific skills.
- To earn the full course certificate, completing all modules in sequence is mandatory.
- Following the correct sequence enhances comprehension and application.
- Certificates for individual modules recognize targeted skill advancement.
What you will learn?
- Gain a comprehensive understanding of what generative AI is and its role in creating novel content.
- Explore the difference between generative models and discriminative models in AI.
- Learn about key neural network architectures used in generative AI, including:
- Generative Adversarial Networks (GANs):Understand how GANs generate new data instances by learning from a training dataset.
- Explore methods and architectures for generating realistic images and videos, including:
- Conditional GANs: Generate images based on specific conditions or inputs.
- Apply your knowledge through hands-on projects that involve implementing and experimenting with generative AI models.
- Develop skills in model training, fine-tuning, and evaluation using popular frameworks like TensorFlow or PyTorch.
MODULE SEQUENCE TO BE FOLLOWED:
This course includes:
- 40 hours on-demand videos
- Interesting Quizes for every module
- Individual certificates
- Provide Badges
- App Accessissibility
- Full Time Access
- Feedback Mechanism
- Downloadable Materials
- Resource Library
Frequently Asked Questions
 This course is ideal for data scientists, machine learning engineers, software developers, and anyone interested in exploring advanced AI techniques to generate creative content autonomously. It is suitable for both beginners and those with some background in machine learning.
 Basic knowledge of machine learning concepts, proficiency in Python programming, and familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) are recommended. Some understanding of neural networks and natural language processing (NLP) will be beneficial but not mandatory.
 The course is structured into modules covering foundational concepts of generative AI, neural network architectures (GANs, VAEs, Transformers), practical implementations using frameworks, applications in NLP and image generation, ethical considerations, and hands-on projects. Each module includes lectures, coding exercises, and projects to reinforce learning.
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 Yes, upon completing the course and projects, you will receive a certificate of achievement. This certificate validates your proficiency in generative AI concepts and practical skills.
  This course will equip you with advanced skills in generative AI, making you well-prepared for roles involving AI model development, research in AI-driven creativity, and applications in fields like content generation, design automation, and more.
 Yes, you will have access to instructor support via forums, office hours, or discussion boards to address any questions or challenges you encounter during the course.
