Master Generative Ai: Unlock Ai-Powered Innovation
Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.41 GB | Duration: 3h 31m
Mastering Generative AI: Unleash the Power of AI Imagination with State-of-the-Art LLMs
What you'll learn
Practical Implementation of Generative Models: Gain hands-on experience in building and training generative models, including GANs and VAEs.
Proficiency in Generative AI Concepts: Develop a strong understanding of generative AI fundamentals, including generative models, discriminative models
Leveraging Large Language Models (LLMs): Learn to harness the power of Large Language Models (LLMs) for real-world applications. Implement cutting-edge LLMs
Ethical Considerations and Best Practices: Acquire knowledge about ethical considerations in AI and generative models, including bias and fairness issues.
Requirements
1. Basic Programming Knowledge: Familiarity with a programming language, preferably Python, is essential. Understanding of fundamental programming concepts is recommended. 2. Mathematics and Statistics Foundation: A basic grasp of mathematics, including linear algebra and calculus, will be beneficial for comprehending AI concepts. 3. Machine Learning Fundamentals: Prior knowledge of machine learning fundamentals, including neural networks, is helpful but not mandatory. 4. Access to Required Tools: Access to a computer with the ability to install necessary software, such as Python, TensorFlow, and PyTorch. 5. Curiosity and Enthusiasm: A strong desire to explore the exciting world of Generative AI and a passion for learning and problem-solving are essential. These prerequisites ensure that students have the foundational knowledge needed to engage with the course material effectively and make the most of their learning experience.
Description
Introduction:Welcome to "Mastering Generative AI," a comprehensive Udemy course designed to demystify the world of Generative Artificial Intelligence. Whether you're a novice or an experienced professional, this course provides a structured journey through the key concepts and advanced techniques that power the realm of Generative AI.Section 1: Introduction to Generative AIIn the opening section, we set the stage with a warm welcome and a course overview, followed by a deep dive into the fundamentals of Artificial Intelligence. Discover the different types of learning in AI, unravel the mysteries of Neural Networks, and explore the significance of Deep Learning. This section culminates in a captivating exploration of Generative AI and its real-world applications, complete with a hands-on demo of Deep Learning.Section 2: Introduction to Generative ModelsMoving forward, Section 2 introduces Generative Models, providing a solid foundation for understanding their intricacies. Delve into the diversity of Generative Models and put your knowledge to the test with an engaging quiz.Section 3: Generative Adversarial Networks (GANs)The course progresses into the heart of Generative AI with a detailed examination of Generative Adversarial Networks (GANs). Understand their components, explore variants, and witness a live demonstration of generator and discriminator dynamics. Address the challenges, ethical considerations, and future trends in GANs, all while testing your knowledge with an insightful quiz.Section 4: Variational Autoencoders (VAEs)Section 4 takes you on a journey through Variational Autoencoders (VAEs), exploring their architecture, training methods, and practical applications. Watch a captivating demo showcasing VAEs in action and solidify your understanding with a quiz.Section 5: AutoencodersAutoencoders take center stage in Section 5, unraveling their architecture, training processes, and real-world applications. Experience the power of Autoencoders in image compression and denoising through a live demo, and assess your knowledge with a comprehensive quiz.Section 6: Large Language Models in Generative AIIn Section 6, we introduce Large Language Models (LLMs) and delve into their architecture. Explore the future possibilities of LLMs and witness their real-world applications. A quiz awaits to challenge your comprehension.Section 7: Transformer-Based Generative ModelsDiscover the transformative power of Transformer-Based Generative Models in Section 7. From their introduction to practical applications, including text generation, translation, sentiment analysis, and creative content generation, this section is packed with knowledge. Engage in hands-on demos and test your understanding with a quiz.Section 8: Mastering Prompt EngineeringThe final section brings it all together with a deep dive into Prompt Engineering. Learn the fundamentals, design effective prompts, and explore various prompt patterns. Real-world applications and advanced techniques are covered, with a quiz to consolidate your expertise.Embark on this journey of mastering Generative AI, and unlock the potential to create groundbreaking solutions. Enroll now and become a proficient Generative AI practitioner!
Overview
Section 1: Introduction to Generative AI
Lecture 1 Welcome and Course Overview
Lecture 2 Introducing Artificial Intelligence
Lecture 3 Types Of Learning In AI
Lecture 4 Introduction to Neural Networks
Lecture 5 Introduction To Deep Learning
Lecture 6 Generative AI and its Applications and Importance
Lecture 7 Demo-Deep Learning
Section 2: Introduction to Generative Models
Lecture 8 Introducing Model
Lecture 9 What are generative models?
Lecture 10 Exploring the Diversity of Generative Models
Section 3: Generative Adversarial Networks (GANs)
Lecture 11 Introduction to GANs (Generative Adversarial Networks)
Lecture 12 GAN Components and Variants
Lecture 13 Diversity of Generative Models
Lecture 14 Demo-Generator and discriminator
Lecture 15 Challenges, Ethical Considerations, and Future Trends
Section 4: Variational Autoencoders (VAEs)
Lecture 16 Introduction to VAE Variants (CVAE, VQ-VAE)
Lecture 17 Demo:Variational Autoencoder (VAE) for MNIST Digit Reconstruction.
Section 5: Autoencoders
Lecture 18 What are Autoencoders?
Lecture 19 Autoencoder-based Image Compression and Denoising Demo
Section 6: Large Language Models in Generative AI
Lecture 20 Introducing Large Language Models (LLMs)
Lecture 21 Decoding the Architecture of LLMs
Section 7: Transformer-Based Generative Models
Lecture 22 Transformer-based generative models
Lecture 23 Examples of transformer-based generative models
Lecture 24 Demo-Transformer Based Translator
Lecture 25 Demo-Transformer Based Sentiment Analysis
Lecture 26 Demo Creative Content Generation with Generative AI
Lecture 27 Demo-Transformer Based Text Generation
Section 8: Mastering Prompt Engineering
Lecture 28 Introduction To Prompt Engineering
Lecture 29 Prompt Design Fundamentals
Lecture 30 Prompt Engineering for Text Generation
Lecture 31 Evaluating and Improving Prompts
Lecture 32 Real-World Applications of Prompt Engineering
Lecture 33 Prompt Patterns
Lecture 34 Persona Pattern
Lecture 35 Question Refinement Pattern
Lecture 36 Audience Persona Pattern
AI Enthusiasts: If you have a fascination for artificial intelligence and wish to deepen your understanding and skillset in the realm of generative AI, this course is tailored for you. Developers and Programmers: Software developers and programmers seeking to explore generative AI and improve their coding abilities, especially in implementing generative models in practical projects. Data Scientists and Analysts: Data professionals who are interested in integrating generative AI techniques into data analysis, visualization, and report generation. Natural Language Processing (NLP) Specialists: NLP experts aiming to enhance their text generation and language understanding capabilities using the latest Large Language Models (LLMs). Content Creators and Creatives: Writers, artists, musicians, and content creators looking to employ generative AI in creative projects, such as generating art, music, and stories. Entrepreneurs and Innovators: Innovators and entrepreneurs who are exploring opportunities to leverage generative AI for product development, marketing, and business growth. Students and Researchers: Students and researchers in the fields of AI and related disciplines, as well as professionals pursuing academic and industry research, who wish to stay at the forefront of the evolving AI landscape. Tech Enthusiasts: Tech-savvy individuals intrigued by the potential of AI and eager to explore and experiment with generative models. This course is suitable for both beginners looking to build a strong foundation and experienced individuals seeking to expand their expertise. Whether you aspire to create innovative AI-powered projects, advance your career, or simply satiate your curiosity, this course equips you with the knowledge and skills required to excel in the field of Generative AI.
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