2 day course

Supporting material

Private

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

Introduction

Python History
Users of Python
Installing Python
Installing IDE

Datatypes

Numbers
Sequences
File
Tuples
Dictionaries

Logic

“If” statement
“If Else” statement
“Switch” statement

Loops

While Loop
Do... While Loop
For Loop
For-each Loop

Functions

Declarations
Variable scope
Passing values

Objects

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

APIs

Connecting to an API
Public BigQuery APIs
Google Analytics API