CU75108

Foundations of Data

Credits
5
Type
Data Science
Scheduled
Y1 – B3
Assessment
(Assignment)
Miller
2: Knows How
ZelCom
(I: 0 C: 0)
Course Owner
Massar, Hugo
Designers
Description
In this course, you will be introduced to the data life cycle. You will learn to design relational databases using SQL and apply CRISP-DM principles to assess and clean data using Python, bridging the gap between software development and data science.
Learning Outcome
You define and apply foundational data modeling and preparation techniques to design relational structures and resolve data quality issues, to ensure data is fit for purpose in both software engineering and basic data analysis.
Indicators
  • Categorization of data based on its characteristics
  • Translation of requirements into a data model
  • Application of normalisation principles
  • Identification and verification of data quality dimensions
  • Application of data preparation techniques
Activities
  • You will design and normalise relational databases
  • You will implement and query these databases using SQL.
  • You will analyse data quality and patterns using Python and Pandas.
  • You will clean unorganised datasets to prepare them for software or analysis.
  • You will discuss data ethics, bias, and privacy standards
Notes
Activities
Analysis
Design
Realisation
Evaluation
Process
Competences
Analysis Advise Design Realise Manage and Control
User Interaction
Organisational Processes 1
Infrastructure S
Software 1 1 1 1 1
Hardware Interfacing
Professional Skills
Future-Oriented Organisation
Organisation Context
Ethics
Process Management
Investigative Ability
Methodical Problem Approach
Research✓
Solution✓
Personal Leadership
Entrepreneurial Mindset
Personal Development
Personal Profiling✓
Targeted Interaction
Partners
Communication
Collaboration