jrayatt / Python-for-Analysts

A Python for Analysts Training course - UK GOV

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Python for Analysts Training

Hi! And welcome to the Python for Analysts training course. This covers everything you need to know to start using Python for data analysis and visualisation as well as showcasing some more advanced and snazzy stuff, including Statistics, Machine Learning, Web Scraping / Interaction etc.

The course assumes no prior knowledge of Python and will teach you everything you need to know in order to use Python for data analysis and visualisation, including interfacing with Python via the Jupyter interface, using Text Editors / Integrated Development Environments (IDEs), upgrading Python, working with the command line etc.

Lastly, note that the course can only hope to give you an introduction to Python for Data Analysis over the 3 days. You'll no doubt want to continue your learning afterward, and the course provides links to relevant material with which to further your development.

Structure of the Course

The course is designed to cover the best part of 2 days with time for exercises and consolidation in between.

You will be expected to have a project to practice with ideally for days 1 and 2 but definitely for day 3! This will allow you to consolidate your Python training and continue to learn and develop.

The structure of the course is as follows:

The Basics

  • Interfacing with Python
  • Basic Python Sytnax
  • Data Structures
  • Coding concepts
  • Looping
  • Enhancing Python with Packages

Working with data

  • Data Analysis Libraries
  • Advanced Data Structures
  • Importing / Exporting Data
  • Working with DataFrames
  • Summary Statistics
  • Tables

Visualisation

  • Static Visualisation
  • Statistical Visualisation
  • Interactive Visualisation

Advanced Concepts

  • Using APIs
  • Web Scraping
  • Statistics
  • Machine Learning
  • Natural Language Processing

It also contains the Training Cookbook.py file containing pre-baked useful code for you to pinch at your leisure.

Credits

Massive thanks to Emma Beynon for her work on the Statistics and Machine Learning notebooks and also for her help in QA'ing and delivering this.

Also another massive thanks to Jose Portilla whose excellent Python For Analysis and visualisation served as much of the inspiration for this course. You can check out his course on Udemy here: https://www.udemy.com/learning-python-for-data-analysis-and-visualization/

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A Python for Analysts Training course - UK GOV


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