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Applying machine learning and AI techniques to data

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Learn to apply machine learning and AI techniques to data

On this 5 hour course you will learn to apply machine learning and AI techniques to data and discover how ethical frameworks can help you avoid teaching your machines bad habits. Essential for anyone needing a theoretical understanding of the opportunities and limitations of using machine learning on data.

The course takes a practical approach to understand the key machine learning techniques, how they can be applied and what implications each has.

Best of all, the course is designed to be non-technical. All practical exercises use drag and drop interfaces with virtual pens, post-its and paper.

By the end of the course you will be able to:

  • Describe the key knowledge and skills to engage in machine learning, AI and ethics
  • Identify applications of machine learning
  • Examine shapes and trends in data
  • Apply a machine learning technique to real world data
  • Evaluate the risks of using machine learning without statistical knowledge
  • Analyse the limits of applications of machine learning data
  • Analyse the implications of using big data
  • Analyse the ethical risks of making automated decisions from data

More about the course

Who is this course for?
This non-technical course is essential for anyone needing a theoretical understanding of the opportunities and limitations of using machine learning on data. This includes (but isn’t limited to) project leaders, C-suite managers, statisticians, data analysts, data scientists and developers.
Course prerequisites
No previous experience of data is required, however it does help if you are confident with a few basic mathematical techniques such as averages, reading statistical charts. It also helps if you are confident in spreadsheet applications, but this is not essential.
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 learning team to discuss how we can improve your organisation’s data literacy.

Course Cost

This course is currently available for group bookings only (up to 16 participants). Content can be tailored to your organisation’s context and needs.

Contact our learning team to discuss dates, pricing and a delivery plan. Discounted rates are available for lower or middle-income countries and larger cohorts.

Public-sector teams can also book via Government Campus (listed as Empowering data innovation through machine learning and AI).

FAQs

How many places/people are on each course? 

Each group booking is for up to 16 participants.

Is there a limit to the number of people from my company that can attend?

Yes, there is a maximum of 3 places per organisation. If you are interested in booking more than 3 places for your organisation, please contact training@theodi.org.

About this course

This course was created by and is © The Open Data Institute. It was developed with the help of funding from the Erasmus+ programme of the European Union under the Open Data Education project.

What you'll learn

Key knowledge and skills to engage in machine learning, AI and ethics
Apply a machine learning technique to real world data.
How to identify applications of machine learning
Analyse the implications of using big data

Book Applying machine learning and AI techniques to data

Book a group with the ODI

This course is tutor-led and currently available for group bookings only (up to 16 people). We can tailor the content to your organisation’s context and needs.

Contact our learning team to discuss dates, pricing and a delivery plan. Discounted rates are available for lower or middle-income countries and larger cohorts.

Book via Government Campus

Government Campus

Public-sector teams can book this course through Government Campus as Empowering data innovation through machine learning and AI.

Digital 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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