Course Details
This course is designed to provide learners with foundational knowledge of Generative AI, including foundational principles, key technologies and algorithms, as well as some key use cases for this transformative and rapidly developing area of Artificial Intelligence.

Kevin Moore
Mpirical Trainer
An experienced educator/trainer in the field of Computer Science, Kevin has over 15 years of experience in instructional design, implementation, and delivery. As an Mpirical trainer Kevin’s specialism is the application of cloud technology within 5G, although Kevin also teaches a range of topics around 5G and earlier 4G technologies.
£95
Individual Course
Course Contents
Introduction to Generative AI:
- Generative AI Fundamentals:
- What is Generative AI?
- Evolution of Generative AI.
- Neural Networks and Large Language Models.
- Loss Functions.
- Training Datasets.
Key Models and Algorithms:
- Generative Adversarial Networks.
- VAEs (Varational Autoencoders).
- Diffusion Models.
- Transformers.
- Other Generative Models.
Building and Training Generative AI Models:
- Datasets and Models.
- Dimensionality Reduction.
- What is Latent Space and Why is it Important?
- Sampling Processes.
- Evaluating Model Performance.
Generative AI Use Cases:
- Overview.
- Content Creation.
- Synthetic Data Generation.
- Personalisation and Recommendation.
- Customer Service.
Legal, Ethical and Moral Considerations:
- Legal and Ethical Concerns.
- Bias and Fairness.
- Privacy & Data Protection Concerns.
- Intellectual Property and Copyright Issues.
- Deep Fakes and Misinformation.
- AI Legislation & Regulation.
£95
Individual Course
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