都柏林城市大學

Data Science involves the study of information where it comes from and the patterns it forms and how to turn this data into a resource for business, government and social strategies. Data Scientists are investigators, story-tellers and problem-solvers who organize information, find unique ways to communicate its salient points, and think of creative ways to apply it to real world situations.

As a DCU Data Science undergrad, you’ll learn theory in mathematics, statistics, programming, cloud technologies and machine learning. Your qualification will be highly marketable, with global demand across numerous sectors.

About the course

The DCU BSc in Data Science combines the three key skill sets of computing, mathematics and enterprise to provide the core knowledge needed to succeed in this growing area. The course will introduce students to the major concepts in data analytics, management, processing, modelling, visualisation and enterprise. Partnering with industry provides opportunities to engage with real-world problems and data sets. You will learn to program, to study mathematics and learn to apply these skills to data from the real world, communicating the results to different audiences.

Modules taught on this programme:

Year 1

• Computer Programming 1
• Data Science and Databases
• Collaboration and Innovation
• Linear Mathematics 1
• Calculus
• Computer Programming 2
• Linear Mathematics II
• Digital Innovation Management & Enterprise
• Probability 1

Year 2

• Computer Programming 3 (Data Structures and Algorithms)
• Probability II
• Data Processing & Visualization
• Statistics 1
• Calculus of Several Variables
• Computer Programming 4 (Object Oriented Programming)
• Data Warehousing and Data Mining
• Introduction to Machine Learning
• Programming for Data Analysis
• Statistics 2

Year 3

• Data Analysis at Speed and Scale
• Data Exploration Using Graph Theory
• Building Complex Computational Models
• Software Engineering: Building Better Software
• Application Domains 1
• INTRA (Job placement - paid)

Year 4

• Research and Experimental Methods
• Natural Language Technologies
• Advanced Machine Learning
• Application Domains 2
• Time Series (Mathematics)
• Professional Practice for Data Science
• Application Domains 3
• Final Year Project

Careers

• Business Intelligence Analyst
• Chief Data Scientist
• Customer Insight Lead
• Data Programmer
• Data Scientist
• Director of Analytics
• Knowledge Engineer
• Team Leader