Overview
This course offers you a one-day comprehensive introduction to the world of Generative Artificial Intelligence (AI) tailored for business professionals.
We begin by demystifying the basics of AI and delve deep into the nuances of Generative AI, contrasting it with Discriminative models. You will discover the capabilities and limitations of these models, supported by real-world case studies as well as how models are fine tuned for specific business scenarios.
By considering the transformative potential of Generative AI across various industries you will have time to reflect on it’s potential impact in your organisation and draft proposals to take back for wider consideration.
Please note - If you would prefer a shorter course, private deliveries are available in which you may choose any two of the course modules for you and your group to experience. Please contact us to request your combination.
Target Audience
The Artificial Intelligence Business Essentials course is focussed on individuals with an interest in, (or need to implement) AI in an organisation, especially those working in the following capacities:
- C-Suite
- Senior Managers
- Organisational change practitioners and managers
- Business change practitioners and managers
- Program and planning managers
- Service provider portfolio strategists / leads
- Process architects and managers
- Business strategists and consultants
Prerequisites
Access to OpenAI ChatGPT would be beneficial but not mandatory. There are no other prerequisites.
Delegates will learn how to
- Introduce Generative AI: Provide participants with a foundational understanding of Generative AI and its distinction from Discriminative models.
- Explore Capabilities & Limitations: Delve into the strengths and challenges associated with Generative AI, emphasizing aspects like content creation, ethical considerations, and potential biases.
- Highlight Real-World Applications: Showcase the transformative potential of Generative AI across various sectors, including marketing, design, and financial forecasting.
- Foster Collaborative Learning: Encourage group activities and discussions, fostering collaborative learning and the exchange of innovative ideas.
- Promote Ethical Use: Emphasize the ethical considerations and responsibilities when deploying Generative AI in a business context.
- Guide Implementation Strategies: Offer insights into best practices for implementing and scaling Generative AI in businesses, from pilot projects to widespread adoption.
- Facilitate Hands-on Experience: Engage participants in workshop, role-playing, and group projects, ensuring they can practically apply the knowledge gained.
Outline
Module 1: Introduction to Generative AI
This module introduces Generative AI, discusses what it is and how it differs from Discriminative models. You will trace the historical evolution of Generative Models and receive an overview of ChatGPT and related models.
- Explore the capabilities of Generative AI models
- Use generative AI tools to create: text, images, music, and videos
- Discuss and compare available Generative AI models.
Module 2: Understanding Capabilities and Limitations
A deep dive into how Generative Models work. Highlighting the strengths such as content creation and data augmentation. As well as the limitations and challenges including ethical considerations, biases and unpredictability.
- Discuss and envision unique applications of Generative AI
- Consider feasibility, challenges, and opportunities.
- Consider ethical concerns and implications
Module 3: Real-world Applications in Business
Explore how creativity in design can be enhanced, customer experiences can be personalised, and many other applications such as forecasting. An insight into the best practices for implementing Generative AI projects in an organisation from strategic planning to execution while emphasising the importance of ethical considerations.
- Create a pitch for a business scenario where Generative AI may add value
- Consider example use cases in marketing, design, customer experiences, financial forecasting
- Consider stakeholder concerns, feasibility, cost, and return on investment and the roadmap from pilot to scale.
- Work as part of a group to adapt and refine project plans and pitches
Module 4: Prompt Engineering and Fine-tuning Models
Introduces prompt engineering and the art and science behind crafting effective prompts. As well as considering how fine-tuning can allow models to cater to specific business needs.
- Identify when prompt engineering is important
- Design prompts by examining effective prompting strategies and tips & tricks
- Examine the potential impact on a business if using effective prompt engineering
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