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Analysing Data Course Outline
Who should attend
This is for anybody who would like to be able to better interpret and analyse datasets.
Learning Objectives
The course teaches students how to explore, analyse data and to ask the right questions that lead to better insights.
Course Length
1 day
Pre-requisites
None. No prior experience in data analysis is required, but basic computer literacy is assumed.
Course Content
Understanding tabular data
- tables rows and columns
- categorical, numerical and ordinal types
- column data types: dates, strings, numbers
Data quality and data cleaning
- Aspects of data quality: incomplete data, missing values, incorrect data, irrelevant data, outliers
- Approaches to fixing bad data.
An introduction to descriptive statistics
Descriptive statistics help us explain and summarise our data.
- measures of central tendency (mean, median, mode)
- measures of dispersion (minimum, maximum, range, standard deviation)
Overview and demos of common data analysis tools
- the data analysis features of Excel
- data cleaning in Power BI’s Query Editor
- data analysis with Python and Jupyter notebooks
- write SQL queries to extract data from relational databases
We use AI tools such as ChatGPT to help analyse data.
Recap and Resources
We will summarise the lessons learned during the day and suggest a few resources for attendees who would like to learn more about data analysis.
There is a short list of learning resources here.