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Beginner’s Python for Data Analysis

Overview

This two-day online course will introduce you to basic data analysis skills in the Python programming language.

Day 1 introduces Python programming including data types, packages, data cleaning, data exploration and visualisation. We take a practical approach and aim to get you starting to code early, with short explanations followed by practical exercises to work through. On the first day all learning materials and an online coding environment are provided to ensure you can start without any software issues. At the end of day 1 will help you get started installing Python on your own machine.

Day 2 builds upon the skills learnt in day 1 and introduces spatial data analytics including visualisation and spatial data manipulation. In the afternoon participants have the opportunity to put their newfound Python data analysis skills into practice in a supportive environment, with help from our tutoring team.

Next course – 29 – 30 November 2023- Open for internal bookings

Is this course for me?

This two-day course assumes no prior knowledge of Python or other programming languages and is aimed at a beginner audience who want to start their journey with data analysis in Python. We aim to provide participants with confidence in applying newly learned coding skills in an analytics and visualisation context. Day 1 provides an introduction to coding and visualisation with Day 2 building upon this knowledge in an applied setting.

Basic IT skills are required. As this courses covers the installation of software at the end of Day 1 it is recommended participants use their personal machines to assist with future usage following the course.

By the end of this course you will be able to:

  • Understand and work with different data types in Python.
  • Run different Python IDEs on your own machine and understand how to update versions and packages, as well as package dependencies.
  • Conduct basic data explorations and manipulations to prepare data for analysis.
  • Produce a wide range of effective data visualisations, both spatial and non-spatial.
  • Load, read in, manipulate and analyse spatial data sets.

Course Tutors

Ryan Urquhart, Teaching Fellow in Data Science, Consumer Data Research Centre (University of Leeds).
Since 2017 Ryan has been studying for his PhD, focussed on commercial spatial data analysis, with the School of Geography at the University of Leeds and is due to submit late 2022. During his time at the University he has contributed to academic research with journal publications and has supported in the delivery of student education across undergraduate and postgraduate level courses. Prior to PhD studies he completed an MSc in Consumer Analytics and Marketing Strategy at the University of Leeds Business School after studying BA Journalism at the University of Derby.

CPD Accreditation

This training course is CPD certified. CPD (Continuing Professional Development) describes the learning activities professionals engage in to develop and enhance their abilities throughout their careers. 

Completing CPD-accredited courses encourages individuals to maintain consistent and high standards, making it easier to demonstrate commitment and dedication to personal and professional development and for individuals to build a career progression plan.

More information about CPD can be found here: https://cpduk.co.uk/explained

Further Information

Next course – 29 – 30 November 2023 –  Book Beginner’s Python for Data Analysis.

This training course will take place in LIDA, Level 11 of the Worsley building, University of Leeds. Directions will be provided ahead of the course and catering is provided for both days. The CDRC offers this course twice a year. Further details about our spring workshop for the course is to follow.

If you have benefited from our Beginners Python for Data Analysis course and want to continue your learning journey, or already have a basis in the Python programming language, the CDRC will be offering an Intermediate Python training course. More details on our spring 2024 dates is to follow.