Who is this course for?
- This course is for individuals interested in entering the field of data science but unsure where to start. It provides foundational skills essential for various professions, addressing the soaring demand for data scientists in the UK. Open to residents or workers in Angus, Dundee, North East Fife and Perth & Kinross, particularly encouraging women to apply to close the gender gap in the digital technology sector. Supported by Data Skills for Work at The Data Lab, and funded by the Scottish Government.
What qualifications will I gain?
- Data literacy
- Data ethics and governance
- Data analytics
- Statistical software
- Data visualisation
What will I learn on the course?
This course is intended to introduce aspects of Data Science to those already working with data. By the end of this course, you will understand:- what data is and how to assess the quality of a dataset;
- how to interpret data presented in visual form;
- how to create your own visualisations, and why;
- how to create and interpret descriptive statistics;
- and, some of the legal and ethical considerations that must be taken into account when working with data.
(Day 1) Interpreting Data
- Types of data
- Features of data
- Spotting errors
(Day 2) Data Visualisation
- Tools
- Excel - standard features - graphs and charts
- Analyse data sets
- Focus on interpretation e.g.
- Using graphs with context and brainstorm what these mean
- What conclusions we can draw
- What further analysis they suggest
- Introduction to statistics and how to interpret them
- Data Protection and Legislation
(Day 3) Data Visualisation
- Tools
- Excel – advanced features – pivot tables, power query
- Tableau – includes interactive dashboards
- Analyse data sets
- Creating and explaining summary statistics in Excel
- Using visualisations in Tableau to draw further conclusions
- Data Ethics/Bias
Application Information
What further course options are available?
- Signposting to appropriate FE courses and NPA Data Science courses.
How will this help my career?
- Data Worker
- Digital Roles