1. What is Artificial Intelligence (AI)
An introduction to AI, and high level concepts.

2. Overview of AI Technologies & Capabilities
A description of essential AI technologies like Machine Learning (ML), Deep Learning (DL) and Generative AI.
A look at AI’s practical applications, including Pattern Recognition and Data Analysis, Text to Speech/Speech to Text, Computer Vision and Image Recognition, and Natural Language Processing (NLP).

3. Everyday AI systems
An exploration of AI-powered tools and systems commonly used in daily life, such as voice assistants, recommendation systems, and AI-enhanced design tools.

4. AI Challenges
Discussion of the challenges including Bias, explainability, and ethics.

1. What is Human-Centered AI (HCAI)?
An overview of Human-Centered AI, focusing on how it prioritizes the user in technology development by aligning AI objectives with human values.

2. Augmenting Human Abilities
Reflections on choice between substitution and amplification of human decision making, and the HCAI positioning.

3. Principles of HCAI

A discussion on the key principles and emerging patterns in HCAI, exploring how they are being applied in the design of AI products. A curated Notion database of these patterns will also be shared for future reference.

4. Challenges to HCAI

A review of real-world challenges to implement HCAI.

1. What is an AI Co-Pilot
An introduction the concept of AI co-pilots, exploring how they function as intelligent assistants that collaborate with users in real-time.

2. Roles of an AI Co-Pilot
A discussion of the various roles that AI co-pilots can play in different industries and tasks.

3. Top Use Cases
Exploring real-world applications of AI co-pilots, highlighting how companies like Microsoft are using them to transform workflows. Participants will look at specific examples, such as Microsoft Co-Pilot for business applications, Perplexity AI for search enhancement, and Midjourney and DALL·E for creative content generation, and others.

4. Building GPTs with OpenAI
The final section of this module focuses on giving learners an understanding of how GPT-based AI systems can be developed using OpenAI’s platform. This part is especially practical, providing insights into the tools and processes needed to build custom AI-powered co-pilots for various applications and lessons learned with the platform. We will also provide an overview of  OpenAI´s GPT marketplace.

The final section will focus on developing custom AI co-pilots using OpenAI's platform. Participants will follow step-by-step instructions provided during the workshop to create their own GPT. For each AI co-pilot, participants will define key elements such as:

. Aim: Determine the purpose and focus of your GPT.
. Instructions: Clearly define the GPT's tasks by specifying what it should emphasise and avoid, how it communicates with users, and other parameters.
. Knowledge base: Upload the relevant documents to shape the interaction with the GPT.
. Capabilities: Activate one or more of the existing GPT capabilities, including Web Browsing, DALL·E Image Generation, and Code Interpreter & Data Analysis.
. Actions (optional): Enable the customisation of specific use cases by allowing your GPTs to interact with third-party services via API calls. This will enhance interoperability with external services.

At the end participants will experiment and present their GPT to the group.