Data Science for Manufacturing Success

Data is the driving force behind decision-making and powering innovation. To thrive in this data-driven era it’s crucial for engineers to harness these capabilities. Data science provides engineers with the insights required to optimise processes, reduce costs, and enhance innovation.

This module is designed to equip engineers with essential knowledge and skills needed to harness the potential of data. The learning experience we provide will bridge the gap between the conventional mechanics of manufacturing and the modern science of data analytics.

Why This Module?

By embracing data-driven strategies, companies can harness the power of analytics, visualisation, and modelling to drive efficiency, innovate faster, and compete more effectively.

Key Learning Outcomes:

Demystifying Data: Delve deep into data collection, interpretation of large datasets, and the subtle art of understanding analytics within these repositories.

Advanced Analytics: Gain robust knowledge on the lifecycle, sampling theories, and the magic of visualisation.

Hands-on Software Utilisation: Become familiar with software tools to analyse data, transforming raw numbers into actionable insights.

Mastering Data Mining: Unveil the potential of data mining, encompassing regression, classification, and anomaly detection techniques.

Scripting for Success: Learn to write scripts in relevant software platforms, becoming an active player in the data mining process.

Our Learning Strategies:

Experiential Learning: Through lectures combined with lab-based practical sessions, learners get a balanced mix of theoretical knowledge and hands-on experience.

Problem-Solving: Learners will tackle practical and analytical challenges, simulating real-world scenarios.

Flipped Classroom Model: Stay ahead by accessing the online content before the lectures. This flexible approach lets learners progress at a comfortable pace, ensuring deeper comprehension.

Course Information

Module Title: Data Science

NQF Level: 8

Academic Credits: 5

Duration: 1 Semester

Contact Hours: 24

Delivery Mode: Blended

Assessment Type: Continuous assessment

Start Date: TBC

Cost: TBC

This course is part of the Micro-Credentials Learner Fee Subsidy from the HEA. Learners can avail of 50%, to find out more about eligibility criteria visit the link below.

Whether you’re looking to upskill your yourself or your team, this module will help to enhance your knowledge in value stream mapping.

To learn more about this programme contact Dr Fiona Boyle [email protected]

Accredited Education: Munster Technological University is a registered training provider with Engineers Ireland