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Fundamentals of Data Science (Non-Technical) - an online course

About this course

This course equips you with the theoretical knowledge and both practical and technical skills to participate in the flourishing data revolution, helping you to contribute to and benefit from the new data-driven economy. The course emphasises a hands-on approach to learning data skills, offering a number of interactive, online exercises that will let you try out many of the techniques and concepts covered in the taught material against real examples.

Taking place over six weeks, each week will contain a mix of taught material, self-study, activities and practical exercises all carried out online.

To find out more please fill in our enquiry form, email us via info@southamptondata.science or call 01223 447775

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For those wishing to apply technical approaches to this topic, please see the parallel course currently running: Fundamentals of Data Science (Technical) 

Course overview

The course is broken into six weeks.

Week 1 - What data science is and key examples of data science in action. You will also learn about open data and the overlap with data journalism to look at how data science is changing the way we tell stories. 

Week 2 - The process of data science, from gathering to visualisation. You will begin your hands on experience of data management with the first assignment, based upon a real case study of hospital performance data in Tanzania to focus on collecting, organising and cleaning data. 

Week 3 - The major case study of the course is introduced. You will begin looking at a large piece of data analysis using real incident records from the London Fire Brigade, to review the decision to close several stations.  This week looks at the data processing and analysis that can help reveal the impact. 

Week 4 - Focus on data visualisation. This week introduces many of the different types of visualisations available, challenges you to spot when you are being deceived, and applies your knowledge to create a visualisation from the analysis in week 3.

Week 5 - Data science is taken to a new scale, looking at how to handle live data and the use of cloud services. We discover at how Transport for London has used open data and the cloud to deliver £130m of economic benefit a year.

Week 6 - Wrap up of the course. We look at the future of data science in your discipline and how to overcome the cultural and management challenges in making more of data in your organisations.

Aims and learning outcomes

This course aims to provide you with the knowledge and expertise to work better with data and data scientists.

Having successfully completed this course, you will be able to:

  • Explain the key concepts in data science and its real-world application.
  • Classify the different types of data available along with rights for usage.
  • Implement an effective data collection and management strategy.
  • Prepare data ready for analysis
  • Analyse a large amount of data to reveal insight.
  • Create a number of data visualisations.
  • Start working with live data and understand the opportunities presented by cloud services.
  • Critically evaluate the challenges and opportunities of exploiting data science in your organisation.

Hands-on experience

Week 2 contains a data management assignment in a spreadsheet application using a real dataset from Tanzania.

Week 3 contains a data analysis assignment in a spreadsheet application using a real dataset from the London Fire Brigade. You will need to apply your learning from week 2 in order to complete this assignment.

Week 4 contains a data visualisation assignment where you will be asked to create a story from your data analysis in week 3. You will be able to use any tool that suits your need and have two weeks to complete this assignment.

Week 5 contains a hands-on exercise with live data where students will be exploring data available from Transport for London.

  • Excel or other capable spreadsheet application (not Google Docs)
  • OpenRefine
  • Optional: visualisation tools including Tableau, CartoDB, Dataseedapp, D3 etc.

Week 1: Introduction to data science

Topics:

  • 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

Topics:

  • 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)?

Topics:

  • 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)?

Topics:

  • 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

Topics:

  • From spreadsheets to web based identifiers
  • Having a REST with API design

Week 6: Applications

Outcomes:

  • Explain how data science creates value
  • Identify the benefits and business opportunities for data science for your discipline

Fees

The Fundamentals of Data Science (Non-Technical) course is £1000 per person, inclusive of VAT.

For corporate packages, please see here.

How to Pay

You can pay by phone, email or Flywire, using the application form here.

Paying Online

  • To make a payment using this method, fill out the application form and select "Pay by Cebit / Debit Card".
  • A 2% fee is charged for payment by credit card and we do not accept American Express. 
  • Fees paid by this method will be charged in British pounds sterling.

Paying by Phone

  • To make a payment using this method, fill out the application form and select "Pay by Phone". 
  • A 2% fee is charged for payment by credit card and we do not accept American Express. 
  • Fees paid by this method will be charged in British pounds sterling.

Pay by Email

  • To arrange a payment using this method, please contact us once you have received confirmation of your place. Contact your course advisor, agent, or email us on payments@southamptondata.science 

Flywire

  • To make a payment using this method, fill out the application form and select "Pay by Flywire".
  • Best for international participants: accepting over 70 currencies via credit card, debit card, or bank transfer.

  • Simply visit www.flywire.com/southamptondata and follow the instructions on the website. Please use the same email address that you used when you applied to the course.