Course Description

This hybrid, credit-bearing course provides both a grounding in the technologies of data science and their potential uses in manufacturing enterprises. Through weekly lectures and hands-on computer workshops students will be introduced to the python programming language and apply some of the tools it provides for manipulating and analysing various forms of data that are common to manufacturing businesses.

The overall aim is to provide students with insights and direct experience of how data handling, visualization and analysis can be applied at different stages of a ‘product lifecycle’ by accessing information from Supply Chains and ERP, PLM, CAM and CAM systems. This holistic approach will develop an understanding of the potential capabilities of enterprise-wide information systems for companies engaged in product development and manufacturing.

The course is NOT

• about all ascpects of machine learning and data science,
• a visualisation library programming course,
• a commercial tool course.

This course WILL

• help you use data science and analytical techniques to create data-driven solutions ,
• teach you how to handle ambiguity in your data,
• help you develop analytical thinking
• assist you discover a way to use data strategically to complement your domain expertise with creativity for problem solving and knowledge discovery,
• help you develop solutions to analyzing and visualizing data coming from various manufacturing sources

Learning Outcomes

1. Program : Identify and deploy strategies for writing, understanding and managing computer programs using Python and version control.
2. Data : The ability to wrangle, analyse, learn from and visualise a range of data, in a way that demonstrates its relevance to digital manufacturing.
3. Evaluation: : Critically reflect on the results and suggest constructive solutions.
4. Communicate : Communicate around manufacture relevant issues, supported by the use of multiple data sources and appropriate analysis.
5. Apply : Competently apply data science techniques and tools.
6. Professionalism : Working in collaborative, interdisciplinary teams to a high professional standard.
7. Understand : Have knowledge of the data ecosystem of manufacturing companies

Takeaways

• A certificate to reflect a 10 credit-bearing course at Masters level (SCQF Level 11)
• Visual representation of your dataset that enables you to answer the challenge you defined around it before and during the course.
• Skills to use data science effectively on manufacture related problems.

Course Summary

This course teaches general knowledge about theory, application, design, and evaluation of data in the context of manufacturing. The goal of the course is to enable participants to understand the potential of data science.

The course targets professionals working in the manufacturing sector and is designed for an interdisciplinary audience, targeting participants with a background in manufacturing, data analysis, and other areas. In addition to core, mandatory topics that aim to develop data analysis literacy, participants can chose from a variety of optional, more specialised topics during the course.

General programming skills are not required. The course will give you an overview of a range of commercial and open source tools to help you decide what works best for your project and skills.

The final assessment will require participants to work on a manufacturing related data science project of their choice, which can, e.g., include their own data or use open data.

In addition to self-directed, online learning, individual help and feedback will be provided through forums and email, drop-in online-sessions, and local workshops in Edinburgh.

Tutorials and talks will be held at the University of Edinburgh, and along with external seminars, will be live-streamed and recorded for an online audience.

We aim to ensure course delivery is as flexible as possible to accommodate each participant’s work schedule. Course content is delivered through recorded online video lectures, suggested readings, online tutorials, quizzes, exercises that can be handed in to obtain feedback as well as optional advanced modules.

Prior to course start, we aim to work with selected participants to shape the course to best accommodate specific needs of working professionals. If you would like to take part in a workshop or taster session please complete a brief interest survey, or e-mail us.