Generative Ai: Techniques, Applications, And Ethics

Published 6/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 389.74 MB | Duration: 0h 58m

Understand the art and science of Generative AI to create intelligent, data-driven models for innovative applications.

What you'll learn
Gain a solid understanding of Generative AI principles and techniques to create intelligent, data-driven generative models.
Learn the principles and techniques of Generative AI to create intelligent, data-driven generative models.
Demonstrate proficiency in evaluating and selecting appropriate Generative AI techniques based on specific project requirements and constraints.
Explore how Generative AI can be applied to diverse fields, such as art, healthcare, gaming, and business.
Develop a critical understanding of the ethical considerations, privacy concerns, and societal impacts of Generative AI technology.
Apply key techniques in Generative AI, such as Bayesian models, autoregressive models, VAEs, GANs, and transformers, to solve real-world problems.
Stay up-to-date on the latest advancements and future trends in Generative AI to enable continuous learning and adaptation in this dynamic field.

Requirements
A willingness to engage in self-directed learning and explore complex topics in Generative AI.
Basic understanding of machine learning principles and concepts.
Comfortable with mathematical concepts like probability and statistics.

Description
Unleash your creativity and explore the world of Generative AI in this comprehensive course. From fundamental principles to cutting-edge techniques, you'll gain hands-on experience with data-driven models that open up new realms of innovation.In the first part of the course, dive into the fundamental principles of Generative AI, including Bayesian models and autoregressive models. Discover the power of Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) to generate realistic and imaginative content. Gain insights into the role of reinforcement learning and transformers in driving advancements in Generative AI.Next, explore a range of real-world applications where Generative AI is making its mark. From art and healthcare to gaming and the business world, witness how Generative AI is transforming industries with its potential for creative content generation, drug discovery, procedural content generation, advertising, and marketing.Finally, delve into the ethical and societal considerations surrounding Generative AI. Understand the implications of AI-generated content, privacy concerns, and the rise of deepfakes. Get a glimpse into the future trends and emerging techniques that will shape the landscape of Generative AI.Join us on this captivating journey to become a leader in the world of Generative AI, and unlock your creative potential through intelligent algorithms.

Overview
Section 1: Introduction

Lecture 1 The Concept of Generative AI

Lecture 2 Importance and Potential of Generative AI

Lecture 3 A Brief History of Generative AI

Lecture 4 Fundamental Concepts in Generative AI

Section 2: Techniques in Generative AI

Lecture 5 Bayesian Models

Lecture 6 Autoregressive Models

Lecture 7 Variational Autoencoders (VAEs)

Lecture 8 Generative Adversarial Networks (GANs)

Lecture 9 Transformers in Generative AI

Lecture 10 Role of Reinforcement Learning in Generative AI

Section 3: Advances in Generative AI Techniques

Lecture 11 Evolution and Progress of GANs, VAEs, and Transformers

Lecture 12 New Techniques and Approaches in Generative AI

Section 4: Applications of Generative AI

Lecture 13 Applications of Generative AI in Art, healthcare, gaming, and Business World

Lecture 14 Emerging Applications of Generative AI

Section 5: Ethical and Societal Considerations

Lecture 15 Ethical Implications of AI-Generated Content

Lecture 16 The Deepfake Phenomenon

Section 6: Future Trends in Generative AI

Lecture 17 Latest Developments and Emerging Trends in Generative AI

Lecture 18 The Intersection of Generative AI and Other AI Disciplines

Lecture 19 Conclusion

Data Scientists and Machine Learning Engineers who want to expand their skill set and delve into the realm of generative models.,AI Researchers and Practitioners seeking to understand the latest advancements and applications of Generative AI.,Computer Science and Engineering students who want to specialize in the field of AI and gain hands-on experience with generative models.,Professionals in the fields of art, healthcare, gaming, advertising, and marketing, who wish to leverage Generative AI for innovative and creative solutions.,Decision-makers, managers, and entrepreneurs who want to gain a comprehensive understanding of Generative AI to make informed strategic decisions.,AI enthusiasts and lifelong learners who are passionate about staying updated on cutting-edge AI technologies and exploring new frontiers.

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