About this course
Developed to provide you with the theoretical knowledge, alongside the practical and technical skills, needed to take part in the data revolution, the six-week course helps you to contribute to and benefit from the expanding data-driven economy. It takes a hands-on approach to the learning of data skills through a number of interactive, online exercises, designed to allow you to experience real examples of the techniques and concepts covered in the taught material.
The course is delivered online, and each week is taught using a mixture of self-study and tutor-led material, activities and practical exercises.
If you are interested in the technical approaches to this topic, we currently have a parallel course in Fundamentals of Data Science (Technical)
The course bridges the skills gap identified by many organisations where people are unable to talk about data science, specifically across the technical/non-technical skills divide.
Week 1: What is data science? We give key examples of data science in action and talk about open data and the overlap with data journalism, to see how data science changes the way we tell stories.
Week 2: Welcome to the process of data science, from gathering to visualisation. Your first assignment gives you first-hand experience of data management. Based on a real case study of hospital performance data in Tanzania, it focusses on the collection, organisation and cleaning of data.
Week 3: Introducing your major case study. With real incident records from London Fire Brigade, you will examine a large piece of data analysis reviewing the decision to close several stations. In particular, this week looks at how data processing and analysis can help reveal the impact.
Week 4: A focus on data visualisation. This week introduces different types of visualisations and challenges you to spot when you are being deceived. You will be asked to apply your knowledge to create a visualisation from the analysis in Week 3.
Week 5: Data science is taken to a new scale. With a look at the handling of live data and the use of cloud services, we discover how Transport for London used open data and the cloud to deliver an economic benefit to the tune of £130m a year.
Week 6: Wrapping up. To round off the course, you will look at the future of data science in your discipline, and identify ways to overcome possible cultural and management challenges in order capitalise the use of data in your organisations.
Aims and learning outcomes
The course aims to equip you with the knowledge and expertise to collaborate with data and data scientists.
Upon successful completed, you will be able to:
- Explain the real-world application of data science and understand its key concepts.
- Classify different types of data and identify the rights for usage.
- Implement a successful data collection and management strategy.
- Prepare data to be analysed.
- Analyse significant amounts of data to reveal insight.
- Create several data visualisations.
- Begin to work with live data and appreciate the opportunities presented by cloud services.
- Critically evaluate the opportunities and challenges of making full use of data science in your organisation.
Week 2 features a data management assignment using a real dataset from Tanzania in a spreadsheet application.
Week 3 uses a real dataset from the London Fire Brigade for its data analysis assignment in a spreadsheet application. To complete this, you will be required to apply your learning from week 2.
Week 4 contains a data visualisation assignment where you will use your data analysis from Week 3, to create a story. You will have two weeks to complete this assignment and can use any tool suitable for your needs.
Week 5 asks you to explore live data from Transport for London, to complete a hands-on exercise.
There will be four assignments: three practical and one set of graded discussions.
- Excel or equivalent spreadsheet application (except Google Docs)
- Optional: visualisation tools, including CartoDB, Tableau, Dataseedapp, D3 etc
Week 1: Introduction to data science
- Welcome and introductions
- What data science is and why it's important
- Creating impact from data science
- Introduction to data science
- Introduction to data storytelling
- Understanding your rights to use data
- What is open data?
- The data spectrum
- Unlocking value from open data
- Why do we need to license?
- Gathering data
Week 2: Health check: Cleaning and visualising hospital data
- The four-step process of data science/journalism
- Organising data
- Cleaning data
- Choosing & designing schemas
- Annotating and describing data
- Open data and open standards
- Data formats and structures
Week 3: How can we improve the performance of the London Fire Brigade (Part one)?
- Filtering & pivot tables
- Introduction to quantitative data analysis
- Introduction to qualitative data analysis
Week 4: How can we improve the performance of the London Fire Brigade (Part two)?
- Data visualization formats
- Data visualisation best practice
- Mapping open data
- Narrating your story
- Visual description
- Practical data visualisation
Week 5: Rolling your own: Building a business with live data
- From spreadsheets to web-based identifiers
- Having a REST with API design
Week 6: Applications
- Explain how data science creates value
- Identify the benefits and business opportunities for data science for your discipline
This school offers programs in:
Last updated November 14, 2018