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Fundamentals of Data Science (Non-Technical)

University of Southampton - Offered by CEG Digital, United Kingdom
Overview Course Requirements Syllabus
Fundamentals of Data Science (Non-Technical)
Next enrollment cycle February 2025 See all cycles
Total Cost KES 314,650
Course Accredited By PC
6 Weeks Online Postgraduate Certificate

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, providing the support you need
  • Continuing Professional Development (CPD) accredited - this will help you demonstrate your commitment to upskilling at your next work appraisal
  • Hands-on - learn how to apply AI capabilities within your own workplace
  • Developed by our pioneering Data Science team - the University of Southampton is ranked among the top 100 universities globally.

Who is this course for?

  • This 6-week, part-time, online course is for professionals who want to develop the knowledge and practical skills needed to work more effectively with data. You will learn how to talk about data to those with, and without, technical knowledge. You’ll take a hands-on approach to the learning of data skills through interactive exercises that allow you to experience real examples of the techniques and concepts covered in the taught material. The course will empower you to make better-informed business decisions grounded on data evidence

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.

Assessment methods and feedback

  • You'll complete four assignments during the course - three practical and one set of graded discussions. Your online tutor will provide feedback at the end of the course, consisting of marks and comments on each assignment. After passing the course, you'll receive a downloadable electronic certificate

Enrollment Cycles

  • February 2025

Entry Requirements

  • Comfortable using Excel. No coding required.

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

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