Python for Data Science

Python has become the go-to programming language for data science. On our two-day course you’ll learn how to use it for next-level data analysis that will give you a competitive edge.

Book this course
2 day course
Supporting material
A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

Python is one of the most searched topics on Stack Overflow. Due to its flexibility and the range of applications that it can be used for, it's fast becoming the most sought-after language in any developer’s portfolio.

This course will start from the very beginning; installing Python 3, setting up your development environment and writing your first lines of code. By the end of the two days, you’ll have a solid understanding of Python and will have gained experience in working with data.

Through project-based learning you’ll have the chance to learn through practical experiences, as you’ll be working with all the general concepts of the python language as well as performing exercises in retrieving, processing and visualizing data.

Our Python for Data Science course is available as a private training session that can be delivered via Virtual Classroom or at a location of your choice in Australia.

Course overview

Who should attend:

If you want to take your first steps toward becoming a Python developer or want to get into the growing industry of Data Science, this course is ideal for you.

What you'll learn:

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

  • Describe why we use programming in Python Syntax
  • Enable Python libraries
  • Collect data from various sources
  • Clean and prepare data
  • Visualize data

Course agenda

  • Python History
  • Users of Python
  • Installing Python
  • Installing IDE
  • Numbers
  • Sequences
  • File
  • Tuples
  • Dictionaries
  • “If” statement
  • “If Else” statement
  • “Switch” statement
  • While Loop
  • Do... While Loop
  • For Loop
  • For-each Loop
  • Declarations
  • Variable scope
  • Passing values
  • OO Programming
  • Class declaration
  • Methods and properties
Data Science Introduction
  • Why Python for Data Science?
  • Popular packages
  • Use cases
  • Popular Libraries
  • Panda
  • Numpy
  • SeaBorn
  • Stats
  • Matplotlib
  • Scikit-learn
Working with Data
  • Reading & Writing to different data sources
  • Cleaning data
  • Visualization
  • Data transformation
  • Automation
  • Connecting to an API
  • Public BigQuery APIs
  • Google Analytics API
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