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Data Science for Beginners Online Short Course

Course description

Driven by the massive growth in data generated by our digitalised world, data science is one of the fastest growing jobs in the UGood data scientists are in demand in all areas of communications: design, journalism, advertising, PR, film; TV, VR/AR and VFX. Get started in this exciting field by learning how to prepare, analyse and visualise data using Python.

Course Outcomes

By the end of the course you should be able to:

  • Understand the typical tasks and activities of a data scientist
  • Load and manipulate data sets
  • Write Python code to analyse data using machine learning and other techniques
  • Write Python code to visualise data

Who Should Attend

This course is ideal for you if you are working in a role that works with data, such as a advertising, journalism, design or computing, and you want to know more about getting value from data.

All our Online Short Courses include:

  • Live online lessons with the same tutors
  • The same course content and learning outcomes
  • Lesson recordings, for review
  • Access to VLE with course content
  • Forums for support
  • 2 weeks online access
  • Certificate upon completion

Further details about preparing for your online course, and the equipment you need, can be found here.

Please note that all courses are taught in UK time. To check and compare times please click here.

Available dates

Materials

Online short course materials

To take part in the Online sessions you will need:

  • An up-to-date web browser (we recommend Chrome)
  • Microphone and headphones (a headset with a microphone function is recommended. The built-in microphone in your device would also be fine)
  • Webcam
  • Strong Internet connection - we recommend a minimum of 2 Mbps download, and 1 Mbps upload, faster if possible. You can test your network speed here - https://www.speedtest.net

Please bring for the first session:

  • notebook and pen

Details

Topics covered

  • Introduction to Data Science: looking at what data science is and some typical data science applications
  • Being a Data Scientist: looking at what data scientists do and the tools they use
  • The Machine Learning Process: working through a small example project, understanding the general approach and process for organising and executing a typical machine learning task using Python
  • Use of “unplugged” (i.e. non-computer based) activities to reinforce understanding
  • Build more Machine Learning Techniques: building on the first exercise, we will learn new techniques such as classification, regression, and evaluating algorithms using  Python
  • Acquiring and Cleaning Data: looking at where to collect data from and how to clean it and manipulate it into the right format using Python
  • Data Visualisation: looking at ways to present and visualise data and implement some code to visualise our data using  Python
  • Data Science Challenge: looking at some typical data science questions and then working collaboratively to investigate and report back our answers

Reviews

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We're working through our student reviews and will add to this section shortly! In the meantime, why don't you check out our stories where you will find out lots about our students and their experiences.
Meet the Tutor:

Data science is one of the fastest growing jobs in the UK and good data scientists are in demand in all areas. Learn to get started in this exciting field by learning how to prepare, analyse and visualise data using Python.

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