/Institute of Coding Summer School, University of Exeter

Provided by: Exeter University

Course Area: All areas

Course Type: Short Course

Start date: 22/06/2020

End date: 10/07/2020

Subjects: Artificial Intelligence, Coding, Computational Thinking, Information Visualisation, Machine Learning, Python, Social Data Analytics

Price: Under £500

Delivery Method: Online

Course overview

This course is run over 3 separate weeks.  Students can sign up to attend one, two or all three weeks.  Each week focuses on a particular coding topic:

  1. Coding bootcamp (22nd – 26th June 2020)
  2. Social data analytics (29th June – 3rd July 2020)
  3. Machine learning and AI (6th – 10th July 2020)

The summer school will include guest lectures from industry and sector specialists from within the wider University across the whole course.

 

We assume that you have no or little programming experience before joining the course.  We use Python in week 1 and week 3 for demonstrating the philosophy of programming as Python is an easy-to-learn fast-growing programming language.  In week 2, we use R as a tool for social data analytics.  All skills that are learnt across the course are also transferable to other programming languages too.

Who Is This Course For

In general, this summer school provides an introduction to coding and is open to all UK university students who do not have experience in coding or computer science.  To attend week 3 on machine learning and AI,  it would be helpful if you have some familiarity with programming.  This could be gained from attending week 1 of the IoC summer school, or from experience that you may have from outside of the school.  However, we will not assume any in-depth knowledge of coding, artificial intelligence or machine learning for this summer school.

What will I learn

Coding Bootcamp (week 1):

This week starts with writing simply python scripts and then builds on your programming skills by learning algorithms, functions, lists, loops, conditions and other basic programming concepts and skills.

 

Social data analytics (week 2):

This weeks is aimed at covering data analysis using R coding.  Students will develop new skills in R coding, handling data in R, data visualisation and statistical comparisons of group means.

 

Machine learning and AI (week 3):

This week aims to demonstrate the basics of artificial intelligence (AI) and machine learning, including thinking about AI and machine learning in a wider context, exploring some of the implications of AI for society through a series of expert lectures providing different perspectives regarding the applications of AI and machine learning.  An additional thread running through the week is a more detailed and practical introduction to ideas in machine learning, focusing on classification, clustering and generalisation.

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