What you will learn?
Foundations of Generative AI: Understand the core concepts and principles of generative AI, including its purpose and different types of generative models.
Generative Model Types: Learn about various generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models.
Applications and Use Cases: Explore practical applications of generative AI across diverse domains, including text generation, image synthesis, and music composition.
Basic Techniques and Algorithms: Gain insights into the algorithms and techniques used in generative AI, including data training, model evaluation, and fine-tuning.
Ethical Considerations: Discuss the ethical implications and challenges associated with generative AI, including issues of bias, privacy, and misinformation.
Hands-On Experience: Engage in beginner-friendly exercises and projects to apply generative AI concepts in practical scenarios.
About this course
"Generative AI For Beginners" is an introductory course designed to provide a comprehensive overview of generative artificial intelligence technologies. This course covers fundamental concepts, key techniques, and practical applications of generative AI, with a focus on understanding how these systems create content, solve problems, and interact with users. By the end of the course, participants will have a solid grasp of the principles underlying generative models, including text, image, and audio generation, and will be equipped with the knowledge to explore further into this rapidly evolving field.
P.S
This course is by Microsoft Reactor and is offered FREE on YouTube.
Requirements
Prerequisites: No prior experience with AI or machine learning is required. Basic computer literacy and a willingness to learn are sufficient.
Materials Needed: A computer with internet access to participate in online lectures and access course materials.
Software Requirements: Access to a web browser and, if required, installation of specific tools or platforms for practical exercises (details provided during the course).
Course Structure: The course includes lectures, interactive discussions, and hands-on exercises designed for beginners. Active participation and engagement in practical exercises are encouraged.
Assignments: Participants will complete practical assignments to reinforce learning, with guidance and feedback provided to support their understanding and application of generative AI concepts.
