Understanding Generative Ai Fundamentals And Possibilities

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Understanding Generative Ai: Fundamentals And Possibilities

Last updated 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.23 GB | Duration: 2h 7m

Learn essential concepts, architectures, and the exciting potential and applications of Generative AI

What you'll learn
Understand the fundamental concepts of Generative AI and how it compares to other approaches
Learn what are the most important Generative AI architectures and how they work
Identify applications of Generative AI across diverse fields
Learn to craft prompt engineering patterns to program LLMs to perform sophisticated behaviours
Explore the future of Generative AI and find inspiration for your own projects
Demystify the learning processes of the neural networks that power Generative AI applications
Understand key ethical considerations about Generative AI
Build a solid knowledge base to confidently pursue more advanced Generative AI concepts and techniques
Requirements
No experience needed. You will learn everything you need to know in this introductory course
Description
Unlock the Transformative Power of Generative AI: Where Creativity and Technology CollideAre you fascinated by the idea of machines generating stunning images, realistic text, or even composing music? Generative AI is revolutionizing the way we create, and this course is your key to begin mastering this groundbreaking field.What You'll Discover:The Building Blocks of Generative AI: Delve into the fundamental concepts, architectures, and techniques that make machines generate breathtaking content.Limitless Applications: Explore the real-world impact of Generative AI across industries - from art and design to marketing and even scientific research.Learn to craft prompt engineering patterns to program LLMs to perform sophisticated behavioursThe Future is Now: Gain insights into the transformative potential of Generative AI and how it's poised to change the world.Demystifying the Learning Process: We'll break down the inner workings of the neural networks that power generative AI technology in an engaging way, combining colourful physical elements with advanced digital representations to visualize how these networks learn.Why This Course is DifferentThis isn't just another theoretical overview. We provide a compact introduction to Generative AI while simultaneously going very deep into the very base of this technology, the processes by which they learn their powerful mappings.Join us and explore the age of Generative AI
Overview
Section 1: Foundations of Generative AI
Lecture 1 Welcome
Lecture 2 Generative modelling, Evolution of Generative AI and Overview of applications
Lecture 3 Building Blocks of Machine Creativity: Machine Learning Foundations for Gen AI
Section 2: Generative AI Models and Applications
Lecture 4 Architectures of Machine Imagination, from GANs to Diffusion and beyond
Lecture 5 Machine Creativity Meets Real-World Impact - Applications of Generative AI
Lecture 6 The Ethics of Machine Creativity: Challenges and Considerations in Generative AI
Lecture 7 Worlds Reimagined: Visions of the Future with Generative AI
Lecture 8 Prompt Programming: Programming Generative AI models with natural language
Section 3: Journey to the latent space of a Neural Network
Lecture 9 In Search of the Magical Mappings of Creativity
Lecture 10 The Search for the Perfect Mapping: datasets and dimensionality
Lecture 11 From Linearity to Complexity: Neural Networks and the Nonlinearities of Life
Lecture 12 Bending the Rules: Non-Linear transformations and the key to complexity
Lecture 13 Not Too Tight, Not Too Loose - Finding the perfect fit
Lecture 14 How increasing the dimensionality impacts the latent complexity of the network
Lecture 15 The Power of Depth: Creating Sophisticated Mappings with AI networks
Lecture 16 From high dimensional manifolds to dynamic and ever changing latent spaces
Lecture 17 Advanced digital representations of the latent complexity of neural networks
Lecture 18 Visualizing the Journey: Loss Landscapes and the Search for Optimal Weights
Lecture 19 Example of the dynamic Loss Landscape of a generative adversarial network
Lecture 20 Lucy - Real Time Visualization of the changing weights of a neural network
Lecture 21 Charting the hidden depths: a recap of our transformative latent space journey
Section 4: Final Review Quiz and Closing thoughts
Lecture 22 Summary and closing thoughts
Curious minds fascinated by the future of creativity,Industry professionals seeking an edge,Anyone intrigued by the intersection of creativity and machines,Creators of all kinds,Tech enthusiasts and lifelong learners,Those that want to explore possible applications of Generative AI technology,Those that want to learn in great depth how the neural networks that power Generative AI applications learn their objectives

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