Digital Skills for Growth (How can machine learning transform your business)*
University Certificate in Professional Development

Course overview

Machine learning enables us to make business forecasts or decisions by analysing existing data rather than needing to know how to explicitly program the calculations. This module will introduce you to the subject and explore a typical machine learning workflow using popular and freely available online tools and technologies. It is suitable for anybody wishing to understand how they could apply machine learning to their business.

In order to complete this course you will need access to the Internet and a PC or Laptop. Any software required will be provided by Teesside University

To apply for this course you need to be employed by a company of any size or sector in Darlington, Durham, Hartlepool, Middlesbrough, Redcar and Stockton on Tees including the Public Sector.

* Subject to University approval

Course details

What you study

What machine learning can do:
• Classification
• Regression
• Clustering

Supervised vs. unsupervised machine learning

Typical machine learning workflow:
• Data preparation
• Model selection
• Model creation
• Model validation

Common Machine Learning models:
• Neural networks
• Decision trees
• Support vector machines
• Regression (linear and non-linear)
• Nearest neighbour

Online digital environments:
• Using an online digital environment for machine learning
• Managing machine learning models
• Executing machine learning on datasets
• Appropriate sharing and remote collaboration within a digital environment

How you learn

The delivery of this module will be via blended learning, which uses a combination of face-to-face learning and online delivery.

Prepared asynchronous learning activities will be used to construct the essential knowledge and understanding.

Face-to-face sessions will consolidate these topics and provide an opportunity to discuss, plan and demonstrate suitable practical learning activities to undertake in response. The results of these learning activities will build into the final portfolio for assessment.

Collaborative asynchronous learning activities will be used to digitally share and review the work done, providing essential formative feedback to guide the work towards a successful pass standard.

How you are assessed

100% in-course assessment on a pass/fail basis. Students will prepare and submit a portfolio of work demonstrating application of the typical machine learning workflow to a small collection (usually 2-3) of business-related problems. The problems will be negotiated and agreed with the tutor, and the number required will be based upon the size and complexity of them. Each solution will include the dataset, model and results together with a short narrative (equivalent of 250 words in either written, audio or video format) explaining what was done. The work will be completed throughout the module as part of the weekly learning activities, with frequent formative feedback available as part of the digital sharing and collaboration activities.

The assessment operates on a pass/fail basis.

Entry requirements

Entry requirements

Must work for a company of any size or sector in Durham, excluding Darlington, including Public Sector.

Employability

Career opportunities

• Support career change
• Retraining opportunity