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Mastering Generative AI; A Comprehensive Guide 2024

Mastering Generative AI; A Comprehensive Guide 2024

$198.00
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What does the Generative AI course cover?

Generative AI is covered here in 8 modules: Introduction to Generative AI: Real-world examples : Case studies and success stories, Fundamentals of Deep Learning, Generative Adversarial Networks (GANs): Types of GANs : DCGAN, CGAN, WGAN, and more and 5 more.

How do you approach Generative AI step by step?

The work is sequenced in 8 stages. It starts with Introduction to Generative AI: Real-world examples : Case studies and success stories, moves through Fundamentals of Deep Learning and Generative Adversarial Networks (GANs): Types of GANs : DCGAN, CGAN, WGAN, and more, and ends at Hands-on Projects and Capstone.

What is in Module 1 of the Generative AI course?

Module 1 is Introduction to Generative AI: Real-world examples : Case studies and success stories. It works through Overview of Generative AI : Definition, history, and evolution, Types of Generative AI : GANs, VAEs, autoregressive models, and more, applications of Generative AI : Art, music, text, images, and videos and 1 more. It sets the vocabulary the remaining 7 modules build on.

How is the Generative AI course delivered?

The Generative AI course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Generative AI course cost?

The Generative AI course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

More answers: what you get with every course, refund policy, all help answers.

Mastering Generative AI: A Comprehensive Guide 2024



Course Overview

Welcome to Mastering Generative AI: A Comprehensive Guide 2024, a cutting-edge course designed to equip you with the knowledge and skills necessary to excel in the rapidly evolving field of Generative AI. This extensive and detailed course curriculum is organized into chapters, ensuring a comprehensive learning experience.



Course Objectives

  • Understand the fundamentals of Generative AI and its applications
  • Learn to design and develop Generative AI models using various techniques and tools
  • Gain hands-on experience with real-world projects and case studies
  • Develop a comprehensive understanding of the latest advancements and trends in Generative AI
  • Acquire the skills to implement Generative AI solutions in various industries and domains


Course Outline

Module 1. Introduction to Generative AI: Real-world examples : Case studies and success stories

  • Overview of Generative AI: Definition, history, and evolution
  • Types of Generative AI: GANs, VAEs, autoregressive models, and more
  • Applications of Generative AI: Art, music, text, images, and videos
  • Real-world examples: Case studies and success stories

Module 2: Fundamentals of Deep Learning

  • Introduction to Deep Learning: Basics, architectures, and frameworks
  • Neural Networks: Perceptron, multilayer perceptron, and backpropagation
  • Convolutional Neural Networks (CNNs): Architecture, applications, and techniques
  • Recurrent Neural Networks (RNNs): Architecture, applications, and techniques

Module 3. Generative Adversarial Networks (GANs): Types of GANs : DCGAN, CGAN, WGAN, and more

  • Introduction to GANs: Architecture, loss functions, and training
  • Types of GANs: DCGAN, CGAN, WGAN, and more
  • GAN applications: Image generation, style transfer, and data augmentation
  • GAN challenges and limitations: Mode collapse, instability, and evaluation metrics

Module 4. Variational Autoencoders (VAEs): VAE variants : Conditional VAEs, VAE-GAN hybrids, and more

  • Introduction to VAEs: Architecture, loss functions, and training
  • VAE applications: Dimensionality reduction, anomaly detection, and generative modeling
  • VAE variants: Conditional VAEs, VAE-GAN hybrids, and more
  • VAE challenges and limitations: Posterior collapse, over-regularization, and evaluation metrics

Module 5. Autoregressive Models: Types of : PixelCNN, WaveNet, and more

  • Introduction to Autoregressive Models: Architecture, loss functions, and training
  • Types of Autoregressive Models: PixelCNN, WaveNet, and more
  • Autoregressive Model applications: Image generation, text generation, and music generation
  • Autoregressive Model challenges and limitations: Computational complexity, sampling, and evaluation metrics

Module 6: Advanced Generative AI Topics

  • Transfer Learning and Fine-tuning: Adapting pre-trained models to new tasks
  • Multimodal Learning: Integrating multiple data modalities and sources
  • Explainability and Interpretability: Understanding and visualizing Generative AI models
  • Ethics and Fairness: Addressing bias, fairness, and accountability in Generative AI

Module 7: Real-world Applications and Case Studies

  • Art and Design: Generative art, fashion, and product design
  • Healthcare: Medical imaging, disease diagnosis, and personalized medicine
  • Entertainment: Content generation, game development, and special effects
  • Marketing and Advertising: Personalized marketing, content generation, and customer engagement

Module 8: Hands-on Projects and Capstone

  • Project 1: Image Generation with GANs: Implementing a GAN-based image generation model
  • Project 2: Text Generation with Autoregressive Models: Implementing an autoregressive text generation model
  • Capstone Project: Developing a comprehensive Generative AI solution for a real-world problem


Course Features

  • Interactive and Engaging: Video lectures, hands-on projects, and discussions
  • Comprehensive and Up-to-date: Covering the latest advancements and trends in Generative AI
  • Personalized Learning: Adaptive learning paths and mentorship
  • Expert Instructors: Industry experts and researchers in Generative AI
  • Certification: Receive a certificate upon completion issued by The Art of Service
  • Flexible Learning: Self-paced learning with lifetime access to course materials
  • User-friendly and Mobile-accessible: Access the course on any device, anywhere
  • Community-driven: Discussion forums and community support
  • Actionable Insights and Hands-on Projects: Practical skills and real-world applications
  • Bite-sized Lessons: Modular learning with focused topics
  • Gamification and Progress Tracking: Engaging learning experience with progress tracking


What You'll Receive

  • A comprehensive understanding of Generative AI and its applications
  • Practical skills in designing and developing Generative AI models
  • A certificate upon completion issued by The Art of Service
  • Lifetime access to course materials and updates
  • Support from the community and expert instructors
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