$1,650

Introduction to Python - Sydney - September 2017

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Level 4, 60 Clarence Street

Sydney, NSW 2000

Australia

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Description

An introductory 2-day course for Introduction to Python.

Please note this course is run concurrently, as the first 2 days of our 4-day Python for Predictive Data Analytics course.

Dates: Monday 11th - Tueday 12th September 2017.

Prerequisites: The course requires some familiarity with programming concepts.

Overview: By the end of the course, you will have all the knowledge you need to start using Python competently for automating various processes involving analysis, modelling, visualisation of various kinds of data. You will have had experience with using Python for various practical data-manipulation tasks with data in a variety of formats, including CSV, Excel spreadsheets, and SQL databases. You will understand the elegance and power of the Python language and its powerful ecosystem of packages for data analysis, and you will be well-placed to continue learning more as you use it day-to-day.

Format: The course is a mixture of hands-on exercises and instruction from experts. Places are strictly limited to ensure there is plenty of hands-on help available for the exercises.


Day 1: Python Basics

Day 1 covers how to use Python for basic scripting and automation tasks, including tips and tricks for making this easy. The syllabus is as follows:

  • Why use Python for predictive analytics? What’s possible? Python versus other languages ...
  • Setting up your Python development environment (IDE, Jupyter)
  • Python syntax and concepts: an introduction through examples
  • Essential data types: strings, tuples, lists, dicts, sets
  • Input and output of text data (including CSV files)
  • Worked example: fetching and ranking real-time temperature data for global cities
  • Raising and handling exceptions


Day 2: Further Python essentials

Day 2 introduces important standard and 3rd-party libraries for real-world scripting and analytics in Python, including working with various important data formats:

  • Modules and packages
  • Finding and installing third-party Python packages
  • Tour of the amazing standard library, including:
  • Handling dates and times
  • Working with files and paths
  • Fetching data from the web
  • Serialization
  • Compressing and uncompressing data
  • Reading and writing essential data formats: CSV, Excel, SQL databases, JSON, time-series
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Training Choice

Level 4, 60 Clarence Street

Sydney, NSW 2000

Australia

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