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Overview
In this Python for Data Analysis and Visualisation from University of St Andrews you will learn about good practices of developing Python code. Python code is supplied and explained for each topic. Your key learning outcomes are:
- Master concepts of modelling, design, and programming in Python and gain practical skills in applying these concepts
- Be confident with effective documentation, layout, debugging and testing
- Be able to use Python programming and development tools
- Be able to load into Python data from standard formats and perform some descriptive data analysis
Teaching format
This is a self-paced online learning short course with lecture content, interactive elements, and access to a masterclass with the course leader after completion of the course.Programme Structure
- Structuring Python code: functions, classes, exceptions, modules.
- Software engineering practices: testing, debugging, profiling, documenting, organising, storing under version control.
- Using Python for data analytics: collecting data (API interaction, web scraping, interfacing databases) and using popular Python libraries (numpy, pandas, matplotlib) for their processing and visualisation
Key information
Duration
- Part-time
- 41 days
Start dates & application deadlines
- StartingApply anytime.
Language
English
Delivered
Online
Campus Location
- St Andrews, United Kingdom
Disciplines
Data Analytics View 26 other Short Courses in Data Analytics in United KingdomWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is suitable for those who are competent in programming using Python (including notebooks, packages, data manipulation, design and use of pipelines, model evaluation functions) but are not expert programmers.
- Coursework involves creating code to solve a specific problem, together with a short report that describes the approach taken and critically evaluates the results. This code can be developed either using learners’ equipment (such as a laptop or PC), or with cloud-based tools such as CoLab and Kaggle Notebooks, or Jupyter notebook. A good internet connection is more important than powerful computational equipment.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residents1250 GBP / full≈ 1250 GBP / full -
Domestic Applies to you
Applies to youCitizens or residents1250 GBP / full≈ 1250 GBP / full
Funding
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