Course Outline
Introduction
- Definition and core concepts of generative AI.
- Distinguishing generative AI from other AI paradigms.
- A survey of key techniques and models within the generative AI landscape.
- Real-world applications and use cases.
- Current challenges and inherent limitations.
Image Generation with Generative AI
- Synthesizing images from textual descriptions.
- Leveraging GANs to produce realistic and varied imagery.
- Utilizing VAEs for image creation involving latent variables.
- Applying style transfer techniques to imprint artistic styles onto images.
Text Generation with Generative AI
- Producing text outputs from specific prompts.
- Employing transformer-based models to ensure context and coherence.
- Generating concise summaries from lengthy texts using summarization algorithms.
- Paraphrasing text to offer alternative expressions of the same meaning.
Audio Creation with Generative AI
- Converting text into spoken speech.
- Transcribing speech into text.
- Composing music based on textual or audio inputs.
- Generating speech with specific vocal characteristics.
Creating Diverse Content with Generative AI
- Generating code from natural language instructions.
- Producing product sketches from textual descriptions.
- Synthesizing video content from text or image inputs.
- Building 3D models from text or visual references.
Evaluating Generative AI Performance
- Measuring content quality and variety in generative outputs.
- Applying metrics such as Inception Score, Fréchet Inception Distance, and BLEU.
- Incorporating human feedback via crowdsourcing and surveys.
- Implementing adversarial evaluation methods, including Turing tests and discriminators.
Ethical and Social Dimensions of Generative AI
- Promoting fairness and accountability in AI systems.
- Preventing misuse and ensuring responsible deployment.
- Protecting the rights and privacy of creators and consumers.
- Encouraging collaborative creativity between humans and AI.
Recap and Future Directions
Requirements
- Foundational knowledge of core AI concepts and terminology
- Proficiency in Python programming and data analysis techniques
- Familiarity with deep learning frameworks like TensorFlow or PyTorch
Target Audience
- Data scientists
- AI developers
- AI enthusiasts
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 2900 € + VAT*
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Testimonials (4)
Understanding of AI and LLM. How it works and ehat the watchouts and opportunities are!
Henk Jan Beltman - genuine business
Course - Advanced AI Concepts with Perplexity
Comprehensiveness about the backround; how to do a prompt.
Olaf Kannt - Helios Klinikum Krefeld
Course - Generative AI and Prompt Engineering in Healthcare
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
