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Unlock the Power of Generative AI in just 8 Days

Generative AI

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Join us for an intensive 8-day course designed to delve into the world of Generative AI, a groundbreaking area of artificial intelligence that enables machines to create new content across various media.

This course will cover fundamental concepts, advanced techniques, and hands-on projects, equipping participants with the skills to develop and evaluate generative models.

Key Topics:

  • Generative Adversarial Networks (GANs)
  • Variational Autoencoders (VAEs)
  • Advanced generative techniques

Please scroll down to read the detailed daily course curriculum of Generative AI. 

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Prof. Dr. Sandjai Bhulai

Prof. Dr. Sandjai Bhulai is a full professor specialising in Business Analytics with a long and outstanding track record in data science and business analytics. He has taught and developed courses on topics such as data wrangling, advanced machine learning, and generative AI. He is also fluent in Python and its most popular deep-learning packages.

Hereby the curriculum per day:

  • Day 1: Introduction to Generative AI

    Morning Session: Overview of AI and Machine Learning

    • Definitions and key concepts
    • Historical context and evolution of AI
    • Types of AI: Narrow vs. General AI

    Afternoon Session: What is Generative AI?

    • Definition and significance
    • Applications in various domains (art, music, text, etc.)
    • Ethical considerations and societal impact

  • Day 2: Foundations of Generative Models

    Morning Session: Key Concepts in Machine Learning

    • Supervised vs. unsupervised learning
    • Basics of neural networks

    Afternoon Session: Types of Generative Models

    • Overview of generative vs. discriminative models
    • Introduction to Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs)


  • Day 3: Deep Dive into GANs

    Morning Session: Understanding GAN Architecture

    • Generator and discriminator roles
    • Loss functions and optimization

    Afternoon Session: Training GANsChallenges and techniques (mode collapse, stability)

    • Hands-on: Building a simple GAN using TensorFlow/PyTorch


  • Day 4: Exploring VAEs

    Morning Session: VAE Architecture and Components

    • Encoder-decoder structure
    • Loss functions: reconstruction loss vs. KL divergence

    Afternoon Session: Training and Applications of VAEs

    • Use cases (image generation, anomaly detection)
    • Hands-on: Implementing a VAE using TensorFlow/PyTorch

  • Day 5: Advanced Generative Techniques

    Morning Session: Other Generative Approaches

    • Flow-based models and diffusion models
    • Introduction to Transformer-based generative models (e.g., GPT)

    Afternoon Session: Text Generation and Natural Language Processing

    • Overview of language models
    • Hands-on: Fine-tuning a pre-trained language model

  • Day 6: Creative Applications of Generative AI

    Morning Session: Generative AI in Art and Music

    • Techniques for generating visual art and music
    • Case studies of notable generative projects

    Afternoon Session: Ethical Considerations in Creative AI

    • Copyright issues and ownership
    • Addressing bias and fairness

  • Day 7: Evaluating Generative Models

    Morning Session: Metrics for Model Evaluation

    • Common metrics (FID, IS)
    • Qualitative vs. quantitative assessment

    Afternoon Session: Practical Evaluation Techniques

    • Peer review of generated outputs
    • Hands-on: Using evaluation metrics on course projects

  • Day 8: Future Trends and Capstone Project

    Morning Session: The Future of Generative AI

    • Emerging trends and research directions
    • Discussion on responsible AI development

    Afternoon Session: Capstone Project Presentations

    • Participants present their projects
    • Feedback and discussion
    • Course wrap-up and Q&A

For more information?

Feel free to contact us via:

Vrije Universiteit Amsterdam

Nieuwe Universiteitgebouw
Faculty of Science
1081 HV AMSTERDAM

Contact

  • Prof. Dr. Sandjai Bhulai
  • Professor in Business Analytics
  • s.bhulai@vu.nl

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