Foundations of Artificial Intelligence (AI) and Prompt Engineering
Introduction to AI, its history, machine learning basics, deep learning, neural networks, and NLP.
Our training approach is human‑centred and outcomes‑driven. We focus on what learners can apply confidently.
Introduction to AI, its history, machine learning basics, deep learning, neural networks, and NLP.
Learn the essential principles of effective prompting, including giving directions, formatting responses.
Explore AI tools like ChatGPT, GPT-4, DALL-E 2, and specialized models, as well as understanding their practical applications.
Focus on advanced prompting techniques such as zero-shot, few-shot, chain-of-thought, prompt chaining.
Study the use of image models, style modifiers, image generation techniques, and practical applications.
Engage in hands-on projects to apply AI concepts, select themes, design AI projects, integrate text and image models.
Understand AI ethics, bias and fairness in models, privacy concerns, data security, transparency in AI.
Specializes in designing and optimizing AI prompts to improve model performance.
Focuses on designing the user experience (UX) by creating intuitive interactions between users and AI systems.
UX Engineers specialize in creating AI systems that prioritize user experience.
Communication Developers focus on building AI-driven systems that support communication tasks, such as chatbots or virtual assistants.
70%
50 multiple-choice/multiple-response questions
| Foundations of Artificial Intelligence (AI) and Prompt Engineering | 11% |
| Principles of Effective Prompting | 15% |
| Introduction to AI Tools and Models | 15% |
| Mastering Prompt Engineering Techniques | 20% |
| Mastering Image Model Techniques | 15% |
| Project-Based Learning Session | 12% |
| Ethical Considerations and Future of AI | 12% |
LangChain
OpenAI's GPT-4