Generative AI Workshop

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20th & 22nd JAN 2023

11:00 AM to 4:00 PM

About Generative AI Workshop

The work of the future is here. The goal is to maximize the interactions between humans and AI. This course is for you if you need to accelerate your learning of how to use generative AI to automate workflows, create powerful communications, understand the full potential of your data, and more.

Our seven-day interactive and stimulating Generative AI Workshop dives into the details and applications of generative AI. The first things you’ll discuss are the advantages and drawbacks of generative AI, how it generates and analyzes language, and the best ways to write compelling prompts.

After that, you’ll explore actual situations and gain practical experience with generative AI tools to improve your business communications, make better decisions based on information, and automate repetitive work.

You’ll also discover the moral and ethical frameworks that should direct your usage of generative AI and why they are important throughout the entire process.

Advancements in generative models have resulted in realistic text, image, and video output that has the potential to completely transform human effort, content creation, and machine interaction. The entire life-cycle of developing and implementing such Generative AI systems—including data collection and processing, system development and necessary infrastructure, services it enables, and ethical considerations associated with such technology covering issues related to accountability, transparency, and fairness—will be covered in the workshop on Generative AI at Digital Brolly.

Generative AI Workshop

Curriculum

Day 1: Introduction to Generative AI and Fundamentals

Session 1: Welcome and Workshop Overview

Introduction to the workshop objectives and structure.
Overview of generative AI and its relevance.

Session 2: Basics of Machine Learning and Neural Networks

Review of essential machine learning concepts.
In-depth exploration of neural networks.
Understanding training and validation.

Session 3: Introduction to Generative Models

Overview of generative models.
Deep dive into autoencoders, variational autoencoders (VAEs), and generative adversarial networks (GANs).

Day 2: Hands-On with Autoencoders and VAEs

Session 4: Practical Implementation of Autoencoders

Hands-on coding session: Building and training an autoencoder.
Application scenarios and case studies.

Session 5: Variational Autoencoders (VAEs)

Understanding the probabilistic nature of VAEs.
Practical implementation: Developing a VAE for image generation.
Use cases and potential applications.

Session 6: Advanced VAE Techniques and Applications

Exploring advanced techniques for improving VAEs.
Hands-on exercises: Fine-tuning VAEs for specific tasks.

Day 3: Generative Adversarial Networks (GANs)

Session 7: Introduction to Generative Adversarial Networks (GANs)

In-depth examination of GAN architecture.
Coding session: Creating a basic GAN model.
Overview of GAN applications in various domains.

Session 8: Conditional GANs and Style Transfer

Understanding conditional GANs.
Hands-on: Implementing a conditional GAN.
Exploring style transfer applications and examples.

Day 4: Transfer Learning and Advanced Topics

Session 9: Transfer Learning in Generative Models

Introduction to transfer learning concepts.
Applying transfer learning to generative models.
Case studies and practical examples.

Session 10: Advanced Generative AI Concepts

Exploring cutting-edge advancements in the field.
Hands-on: Tackling advanced generative AI challenges.

Day 5: Ethical Considerations and Future Trends

Session 11: Ethical Considerations in Generative AI

Discussing ethical concerns related to generative AI.
Strategies for responsible AI development and deployment.

Session 12: Future Trends in Generative AI

Overview of the latest trends and emerging technologies.
Group discussions on potential future applications and challenges.

Day 6: Project Work and Consultation

Session 13: Project Work and Guidance

Dedicated time for participants to work on their generative AI projects.
Instructors provide one-on-one guidance and support.

Session 14: Project Collaboration and Feedback

Participants collaborate on projects.
Peer feedback sessions and group discussions.

Day 7: Project Showcase, Q&A, and Closing

Session 15: Participant Project Showcase

Participants present their generative AI projects.
Panel discussion and feedback from instructors.

Session 16: Q&A and Closing Remarks

Open forum for participant questions.
Summary of workshop highlights and key takeaways.
Distribution of certificates and resources for continued learning.

Enroll Now for Free Demo

Generative AI Workshop

Certifications

Generative Adversarial Networks (GANs) Specialization
Deep Learning and Generative Adversarial Networks (GANs) with PyTorch
AI for Healthcare
Practical Deep Learning for Coders
CS231n: Convolutional Neural Networks for Visual Recognition

Generative AI Workshop

Who Is This Workshop For?

Data Scientists
Machine Learning Practitioners
Software Engineers
Students and Researchers
Entrepreneurs
AI Enthusiasts

Generative AI Workshop

After This Workshop, You’ll Learn

The fundamentals of generative models include autoencoders, variational autoencoders (VAEs), and generative adversarial networks (GANs).
Gain hands-on experience in coding and implementing generative AI models.
Explore the creative potential of generative AI in various projects.
Apply learned skills to generate novel and artistic outputs, including image synthesis and style transfer.
Understand advanced techniques for improving the performance of generative models.
Explore transfer learning concepts and apply them to generative models.
Understand how generative AI can be used in real-world applications across different industries.
Gain insights into the ethical considerations and responsible development of generative AI.
Understand the implications of using generative models responsibly in various contexts.
Explore potential future applications and challenges in the rapidly evolving landscape.

Generative AI Workshop

Key Takeaways

Understanding Generative Models
Hands-On Implementation
Creative Applications
Advanced Techniques and Fine-Tuning
Transfer Learning Concepts
Ethical Considerations
Real-World Applications
Project Development Skills
Career Advancement Opportunities
Continuous Learning Resources

Generative AI Workshop Price & Packages

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Enter your title

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39
99
Monthly

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Generative AI Workshop Schedule

Day 1
Day 2
Day 3
Day 4
Day 5: Project Showcase, Q&A, and Closing
Day 1

Introduction to Generative AI and Fundamentals

9:00 AM – 9:30 AM: Registration and Welcome

Registration, check-in, and welcome participants to the workshop.

9:30 AM – 10:00 AM: Workshop Overview and Goals

Introduction to the workshop objectives, structure, and key learning goals.

10:00 AM – 11:30 AM: Basics of Machine Learning and Neural Networks

Overview of machine learning concepts and a deep dive into neural networks.

11:30 AM – 12:00 PM: Coffee Break and Networking

12:00 PM – 1:30 PM: Introduction to Generative Models

Understanding generative models, focusing on autoencoders, variational autoencoders (VAEs), and generative adversarial networks (GANs).

1:30 PM – 2:30 PM: Lunch Break

2:30 PM – 4:00 PM: Hands-On Session 1 – Practical Implementation of Autoencoders

Coding session: Building and training a basic autoencoder.

Discussion of use cases and applications.

4:00 PM – 4:30 PM: Q&A and Wrap-Up

Open floor for participant questions and a summary of key takeaways from the day.

Day 2

Advanced Generative Models and Techniques

9:00 AM – 9:30 AM: Recap of Day 1

A brief recap of the concepts covered on the first day.

9:30 AM – 11:00 AM: Variational Autoencoders (VAEs)

Understanding the probabilistic nature of VAEs.

Practical implementation: Building a VAE for image generation.

11:00 AM – 11:30 AM: Coffee Break and Networking

11:30 AM – 1:00 PM: Generative Adversarial Networks (GANs)

Introduction to GAN architecture.

Coding session: Creating a basic GAN model.

Discussion of GAN applications in various domains.

1:00 PM – 2:00 PM: Lunch Break

2:00 PM – 3:30 PM: Hands-On Session 2 – Conditional GANs and Style Transfer

Understanding conditional GANs.

Hands-on coding: Implementing a conditional GAN.

Exploring style transfer applications.

3:30 PM – 4:00 PM: Q&A and Group Discussion

Addressing participant questions and engaging in a group discussion on the day’s topics.

Day 3

Advanced Concepts and Ethical Considerations

9:00 AM – 9:30 AM: Recap of Day 2

A brief recap of the concepts covered on the second day.

9:30 AM – 11:00 AM: Transfer Learning in Generative Models

Introduction to transfer learning concepts.

Applying transfer learning to generative models.

Case studies and practical examples.

11:00 AM – 11:30 AM: Coffee Break and Networking

11:30 AM – 1:00 PM: Advanced Generative AI Concepts

Exploring cutting-edge advancements in the field.

Hands-on: Tackling advanced generative AI challenges.

1:00 PM – 2:00 PM: Lunch Break

2:00 PM – 3:30 PM: Ethical Considerations in Generative AI

Discussion on ethical concerns related to generative AI.

Strategies for responsible AI development.

3:30 PM – 4:00 PM: Q&A and Reflection

Open forum for participant questions and a reflection on the ethical considerations discussed.

Day 4

Project Work and Consultation

9:00 AM – 12:00 PM: Project Work Session

Dedicated time for participants to work on generative AI projects.

Instructors are available for a one-on-one consultation.

12:00 PM – 1:00 PM: Lunch Break

1:00 PM – 4:00 PM: Project Collaboration and Feedback

Participants collaborate on projects.

Peer feedback sessions and group discussions.

Day 5: Project Showcase, Q&A, and Closing

9:00 AM – 11:00 AM: Participant Project Showcase

Participants present their generative AI projects.

Panel discussion and feedback from instructors.

11:00 AM – 12:00 PM: Q&A and Participant Interaction

Open floor for participant questions and interaction.

12:00 PM – 1:00 PM: Closing Remarks and Certificates

Summary of workshop highlights and key takeaways.

Distribution of certificates and resources for continued learning.

Generative AI Workshop

About Speaker

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Generative AI Workshop

Generative AI Use Cases To Motivate Your Small Business Or Startup

Every day, generative AI is being used by more small and startup companies for both internal and external customer demands. Google Cloud is used by more than 70% of generative AI’s billion-dollar unicorns. With new products and features being announced virtually every day, technology is still developing quickly, and organizations are finding new applications for and methods to employ gen AI tools.

Popular use cases

Healthcare

Generative models contribute to generating synthetic medical images for training machine learning algorithms and augmenting datasets.
Generative models assist in generating molecular structures and predicting potential drug candidates, accelerating the drug discovery process.
Generative models are used for anomaly detection in patient data, helping identify unusual patterns that may indicate health issues.
Early disease detection, patient monitoring, and healthcare analytics.

Entertainment and Media

Generative models, especially GANs, are utilized for creating realistic images and videos in the entertainment industry, enhancing special effects.
Generative AI is employed to create personalized content experiences, tailoring recommendations based on user preferences.
Streaming services like Netflix and content platforms like YouTube use generative models to recommend movies, shows, or videos personalized to each user’s viewing history and preferences.

Manufacturing and Design

Generative design models explore a multitude of design possibilities based on specified parameters.
This leads to innovative and optimized product designs, pushing the boundaries of traditional design methodologies.
Industries involved in industrial design, engineering, and product development leverage generative design for creating unique and efficient product prototypes.

Financial Services

Generative models are employed in the financial sector to detect anomalies in transactions, aiding in fraud detection and risk management. These models learn normal transaction patterns and identify deviations.
Banks and financial institutions use generative AI to monitor transactions, identify suspicious activities, and enhance cybersecurity measures.

Technology and AI Development

Generative AI assists in code generation, automating parts of the software development process.
This includes auto-generating code snippets, completing code segments, and even suggesting solutions to programming problems.
Software developers benefit from increased productivity and efficiency as generative models aid in coding tasks, reducing manual effort and speeding up the development cycle.

FAQ’S

What is Generative AI?

Generative AI refers to a subset of artificial intelligence focused on creating new content, data, or artifacts. It includes various generative models, such as autoencoders, variational autoencoders (VAEs), and generative adversarial networks (GANs), which can generate synthetic data based on patterns learned during training.

Who is this workshop suitable for?

This workshop is suitable for data scientists, machine learning practitioners, software engineers, developers, students, researchers, entrepreneurs, and AI enthusiasts. It caters to a broad audience with varying levels of expertise, from beginners to experienced professionals.

What programming languages will be used in the workshop?

The workshop primarily uses Python for its hands-on coding sessions. Participants should have a basic understanding of Python or be willing to learn the basics to fully engage in the practical aspects of the workshop.

Are there any prerequisites for attending the workshop?

Participants should have a basic understanding of programming, preferably in Python. Familiarity with fundamental machine learning concepts, such as neural networks, is advantageous but not mandatory. The workshop will cover the necessary concepts to bring everyone up to speed.

How will the workshop address ethical considerations in generative AI?

The workshop includes a dedicated session on ethical considerations in generative AI. We will discuss the responsible development and deployment of AI models, emphasizing the importance of ethical considerations in the rapidly evolving field of generative AI.

How will the workshop benefit my career?

The workshop will equip you with practical skills in generative AI, enhancing your professional toolkit. The knowledge gained can be applied to various industries, making you a valuable asset in fields such as healthcare, entertainment, finance, and more.

Will there be resources for continued learning after the workshop?

Absolutely. Participants will receive access to a resource hub containing materials, references, and further learning opportunities. This ensures that you can continue your generative AI journey and stay updated on the latest advancements in the field.

Is there a certificate of completion for the workshop?

Yes, participants will receive a certificate of completion at the end of the workshop, acknowledging their proficiency in generative AI concepts and applications.