Generative AI: Driving Innovation in Data Practices
Generative AI: Driving Innovation in Data Practices
This course helps organisations navigate the opportunities and challenges of generative AI, exploring its benefits across the data lifecycle while promoting responsible data practices to ensure compliance and minimize harmful or unintended impacts.
At the ODI, we combine a deep understanding of data principles with practical expertise in emerging technologies like generative AI. Our mission is to help organisations not only adapt to change but lead the way in using data responsibly and effectively. This course draws on our legacy of pioneering tools and training, offering participants unique insights into generative AI systems grounded in real-world applications.
Through four comprehensive sessions, participants will engage with real-world case studies that highlight the opportunities and risks of generative AI. We demystify the technology, clarify key terminology, and provide actionable strategies to become informed, responsible, and effective users and customers of generative AI.
£213 + VAT
£225 + VAT
£250 + VAT
What you'll learn
Assess the ethical, legal, and operational considerations associated with generative AI systems
Why choose the ODI?
The ODI has a proven track record in advancing data practices through tools, standards, and training. We bring together expertise in data, AI, and ethics to ensure that organisations not only adopt the latest technologies but do so responsibly and effectively. Our approach bridges technical understanding with practical application, enabling participants to make informed decisions and achieve meaningful outcomes with generative AI.More about the course
Who is this course for?
This course is designed for both technical and non-technical professionals who make decisions or derive insights from data. It’s ideal for roles such as decision-makers, data analysts, policy advisors, business consultants, IT professionals, and educators—anyone looking to understand and apply generative AI systems to enhance workflows, uncover insights, and inform strategies. Accessible to all skill levels, the course bridges the gap between technical understanding and practical application, empowering participants to harness the potential of generative AI.
Course prerequisites
No specific prior experience is required to take this course. However, participants will benefit from familiarity with generative AI systems, an understanding of the importance of crafting effective prompts or questions, and some awareness of the challenges involved in working with large-scale quantitative and qualitative data. These insights will help you get the most out of the course content and practical exercises.
Learning experience and course delivery
This course can be run for groups of up to 16 people. And, we can tailor our content to your context and needs.
We can work with you to identify the data skills required across your business, creating training that meets your organisation’s needs.
Contact our Data Skills Experts to discuss how we can improve your organisations data literacy.
Course Cost
ODI members: £213 (+VAT where applicable) (from 18.09.23)
General admission: £250 (+VAT where applicable.)
Not an ODI member?
Click here to find out more about ODI membership.
FAQs
How many places/people are on each course?
Each course date will consist of up to 16 participants.
Is there a limit to the number of people from my company that can attend?
No
About this course
This course was created by and is © The Open Data Institute.
Inclusivity
To ensure inclusivity, we offer discounted pricing for customers from lower or middle-income countries.
Please contact us for further information.
If you represent a business interested in purchasing four or more course spaces, please reach out to us for personalised discounted rates.
Course instructors
Dr David Tarrant
Senior Technical ConsultantDigital Analyst, Boots
"The assignments were the highlight of the course. They were well designed – it’s good to use real live data from a different sphere than I’m used to working in. And I really liked how they built on the previous assignment learnings.”
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