Introduction to Data Science


One Semester or equivalent



Contact hours
48 Hours

Credit Points

Aims and learning outcomes

This unit aims at introducing students to the key concepts and techniques in data science and Big Data analytics. Students will be introduced to different stages in data analytics and given the opportunity to plan and design data science projects that address business and organisational needs.

After successfully completing this unit, you should be able to:

  1. Appreciate the roles of data science and Big Data analytics in business and organisational contexts.
  2. Appreciate the key concepts, techniques and tools for discovering, analysing, visualising and presenting data.
  3. Describe the processes within the Data Analytics Lifecycle.
  4. Analyse business and organisational problems and formulate them into data science tasks.
  5. Evaluate suitable techniques and tools for specific data science tasks.
  6. Develop analytics plan for a given business case study.
  7. Perform data analytics tasks using Microsoft Excel.

Unit information

Learning and teaching structures

2 hours lectures and 2 hours tutorial/laboratory per week.

In a Semester, you should normally expect to spend, on average, twelve and a half hours of total time (formal contact time plus independent study time) a week on a 12.5 credit point unit of study.


  • Introduction to data science and Big Data analytics
  • Roles of data science for businesses
  • Contemporary data structures and management
  • Basic statistics and probabilities
  • Data science tools and technologies
  • The Data Analytics Lifecycle
  • Analytical techniques and methods
  • Analytic plan development
  • Data analytics with Microsoft Excel

General skills outcomes

Key Generic Skills:

  • Analysis skills
  • Problem solving skills
  • Critical thinking skills
  • Ability to tackle unfamiliar problems
  • Teamwork skills
  • Written communication skills


  1. Assignment 1 (Group) 20%
  2. Assignment 2 (Group) 30%
  3. Online Test (Individual) 10%
  4. Final examination (Individual) 40%

Minimum requirements to pass this unit of study

In order to achieve a pass in this unit of study, you must:

  • achieve an aggregate mark for the subject of 50% or more, and
  • achieve at least 40% in the final exam

Study Resources

Resources and reference material

  • EMC Education Services, 2015. Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. John Wiley & Sons.
  • Foreman, J.W., 2013. Data Smart: Using Data Science to Transform Information into Insight. John Wiley & Sons.
  • O’Neil, C. & Schutt, R. 2014. Doing Data Science. O’Reilly Media Inc.