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Fundamentals of Data Science (Non-Technical)

Why this course?

This course will enable you to gain valuable insights from the power of data science and adopt a real-world approach to data.

Key benefits:

  • Tutor-led - University of Southampton academics will guide you through the content and answer your questions, unlike other online courses where you're left to your own devices
  • Continuing Professional Development (CPD) accredited, helping you demonstrate your commitment to upskilling at your next appraisal
  • Hands-on - learn how to use data evidence to solve problems within your own workplace.

Developed by the pioneering Data Science team at the University of Southampton – ranked among the top 100 universities globally – this course is designed to equip you with the theoretical knowledge, practical and technical skills you need to work more effectively with data.

Taught by industry-leading experts in data science using a practical approach to learning data skills, this 6-week flexible online course will empower you to make better-informed business decisions grounded on data evidence, and to meet the demands of today’s increasingly data-driven economy.

The course runs over 6 weeks and is broken down into manageable weekly topics:

Week 1: Introduction to data science

  • Welcome and introduction to the course
  • What data science is and why it’s important
  • Creating impact from data science
  • Introduction to data storytelling
  • Understanding your rights to use data
  • The data spectrum
  • Unlocking value from open data
  • Gathering data

Week 2: Health check – Cleaning and visualising hospital data

  • The 4 steps of data science
  • Organising and cleaning data
  • Choosing and designing schemas
  • Annotating and describing data
  • Open data and open standards
  • Data formats and structures

Week 3: Case study – How can we improve the performance of the London Fire Brigade? (Part 1)

  • Filtering and pivot tables
  • Introduction to quantitative data analysis
  • Introduction to qualitative data analysis

Week 4: Case study – How can we improve the performance of the London Fire Brigade? (Part 2)

  • Data visualisation formats and 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

  • How data science creates value
  • The benefits of and business opportunities for applying data science within your organisation

After successfully completing the course, you’ll be able to:

  • Explain the key concepts of data science and its real-world application
  • Classify the different types of data available and usage rights
  • Implement an effective data collection and management strategy
  • Prepare data for analysis
  • Analyse a large amount of data to gain valuable insights
  • Create data visualisations
  • Effectively work with live data and understand the opportunities presented by cloud services
  • Critically evaluate the challenges and opportunities arising from utilising data science within your organisation

Professor

Les Carr

Les is Professor of Web Science at the University of Southampton’s School of Electronics and Computer Science. He’s also a Director of the Web Science Institute and former Director of the Web Science Centre for Doctoral Training. His research on Open Access and Open Data led to the establishment of Eprints – offering Open Access publication and data services, training and support to the research industry.

Professor

Elena Simperl

Elena is a Professor of Computer Science within the Web and Internet Science research group – part of the University of Southampton’s School of Electronics and Computer Science. Her primary research domain concerns the intersection between knowledge technologies and crowd computing. Elena is interested in socially and economically-motivated aspects of creating and using semantically-enabled content on the Web, and in paradigms, methods and techniques to facilitate large-scale collaboration and incentivise participation.

Dr

Rob Blair

Rob is Visiting Fellow at the University of Southampton’s School of Electronics and Computer Science. He holds an MSc Information Systems from the University of East Anglia and an MSc Web Science from the University of Southampton. Qualified to teach Physics, Mathematics and Computer Science, Rob is a highly-experienced classroom teacher and online tutor specialising in data science.

Dr

David Millard

Dave is Associate Professor of Computer and Web Science at the University of Southampton, David is a founding member of the Web and Internet Science research group within the School of Electronics and Computer Science (ECS). He represents ECS on the steering group for the Web Science Centre for Doctoral Training. David is currently Vice-Chair for ACM SIGWEB.

Dr

Manuel León Urrutia

Dr. Manuel León Urrutia is Research Fellow in the Web and Internet Science research group of the Electronics and Computer Science department of the University of Southampton. Manuel is specialised in learning technologies, with experience in learning design and research interests in MOOCs and learning analytics. Prior to joining the Computer Science department in 2012, he worked for 6 years as an editor in a publishing company, and 6 more years as a language teacher in the University of Southampton. Manuel currently has an academic, senior tutoring and learning design role in the Southampton Data Science Academy.

Dr

Gary Wills

Gary is an Associate Professor in Computer Science at the University of Southampton. He graduated from the University of Southampton with an Honours degree in Electromechanical Engineering, followed by a PhD in Industrial Hypermedia Systems. Gary is a Chartered Engineer, a member of the Institute of Engineering Technology, and a Principal Fellow of the Higher Educational Academy. He is also a visiting Associate Professor at University of Cape Town and a research professor at RLabs.

How you'll learn

Guidance thoughout the course

A key benefit of choosing Southampton Data Science Academy over some of the other online courses available is that our courses are tutor-led. A tutor is just as important with an online course as it is in a physical classroom. A good tutor’s passion for the subject will motivate you and inspire you, making the content stick in your mind.

Our tutors are data science experts who can make complex ideas accessible. If you don’t understand the course material right away they can provide an alternative explanation or use a different example. If you have a question about the content, our tutors are available to answer it. They will work with you to make sure you understand the subject fully and are on track to complete the course successfully.

Hands-on learning that you can immediately apply to your work

Learning is hands-on, using real-life business examples to demonstrate how you can immediately harness and apply the power of data science to your work. Our online learning platform is easy to access via smartphone, tablet or desktop – anytime and from anywhere in the world. You’ll join a global online network of like-minded professionals and take part in group discussions, Q&A sessions and video tutorials.

Our courses are also CPD-accredited. Many employers will ask you at appraisals to show evidence of the impact of Continual Professional Development (CPD) on your professional work. A CPD-accredited Southampton Data Science course is a great way to demonstrate your commitment to upskilling, especially as you will learn practical techniques and tools that you can immediately apply to your workplace.

Find out more about how you'll learn with Southampton Data Science Academy.

Ready to boost your data literacy?

Take our flexible online course and learn how to leverage data to achieve your business goals.

Apply now