Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Review of Generative AI Basics
- Quick recap of Generative AI concepts
- Advanced applications and case studies
Deep Dive into Generative Adversarial Networks (GANs)
- In-depth study of GAN architectures
- Techniques to improve GAN training
- Conditional GANs and their applications
- Hands-on project: Designing a complex GAN
Advanced Variational Autoencoders (VAEs)
- Exploring the limits of VAEs
- Disentangled representations in VAEs
- Beta-VAEs and their significance
- Hands-on project: Building an advanced VAE
Transformers and Generative Models
- Understanding the Transformer architecture
- Generative Pretrained Transformers (GPT) and BERT for generative tasks
- Fine-tuning strategies for generative models
- Hands-on project: Fine-tuning a GPT model for a specific domain
Diffusion Models
- Introduction to diffusion models
- Training diffusion models
- Applications in image and audio generation
- Hands-on project: Implementing a diffusion model
Reinforcement Learning in Generative AI
- Reinforcement learning basics
- Integrating reinforcement learning with generative models
- Applications in game design and procedural content generation
- Hands-on project: Creating content with reinforcement learning
Advanced Topics in Ethics and Bias
- Deepfakes and synthetic media
- Detecting and mitigating bias in generative models
- Legal and ethical considerations
Industry-Specific Applications
- Generative AI in healthcare
- Creative industries and entertainment
- Generative AI in scientific research
Research Trends in Generative AI
- Latest advancements and breakthroughs
- Open problems and research opportunities
- Preparing for a research career in Generative AI
Capstone Project
- Identifying a problem suitable for Generative AI
- Advanced dataset preparation and augmentation
- Model selection, training, and fine-tuning
- Evaluation, iteration, and presentation of the project
Summary and Next Steps
Requirements
- An understanding of fundamental machine learning concepts and algorithms
- Experience with Python programming and basic usage of TensorFlow or PyTorch
- Familiarity with the principles of neural networks and deep learning
Audience
- Data scientists
- Machine learning engineers
- AI practitioners
21 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (2)
Going over the various use cases and application of AI was helpful. I enjoyed the walkthrough of the various AI Agents.
Axel Schulz - CANARIE Inc
Course - Microsoft 365 Copilot: AI Productivity Across Word, Excel, PowerPoint, Outlook, and Teams
I liked that trainer had a lot of knowledge and shared it with us
