Python Training

Python for Predictive Data Analytics

This is a course for data analysts, financial analysts, statisticians, software developers, and other technical staff interested in learning to use Python as a unified language for automating and sharing data analysis and performing powerful predictive analytics. This is a course intended for seasoned programmers who are experienced in programming in other languages such as C#, Java, R, or Matlab.


Some familiarity with programming concepts (in any language) is assumed.

Expected Outcomes

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, visualising and predicting various kinds of data. You will have gained experience with using Python for various practical data-manipulation tasks with data in a variety of formats, including time-series data, in CSV, Excel spreadsheets, and SQL databases. You will have applied powerful tools for clustering, classification, and regression, in useful practical settings on small and large data sets. You will understand the elegance and power of the Python language and its powerful ecosystem of packages for data analytics, and you will be well- placed to continue learning more as you use it day-to-day.

Course Syllabus

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 Java, C#, R, Matlab ...
  • Setting up your Python development environment (IDE, IPython notebook)
  • Python syntax and concepts: an introduction through examples
  • Variables, values and operators
  • Conditions
  • Loops
  • Functions
  • Essential data structures: strings, tuples, lists
  • Input and output of text data (including CSV files)
  • String methods
  • Raising and handling exceptions
  • Day 2: Further Python essentials

    Day 2 introduces further important concepts for real-world scripting in Python. The syllabus is as follows:

  • Further important data structures: dictionaries and sets, and their applications
  • Modules and packages
  • Tour of the amazing standard library, including:
  • Handling CSV files
  • Handling dates and times
  • Fetching data from the web
  • Serialization
  • Compressing and uncompressing data
  • Day 3: Essential analytic tools and data formats

    The Pandas package is an amazingly productive tool for working with and analysing data in Python. Day 3 gives a thorough introduction to Pandas and related tools for working with different kinds of data, including spreadsheets, time-series data, and SQL databases. The syllabus is:

  • Fast, powerful data analysis with Pandas
  • Working with time-series data
  • Working with missing and noisy data
  • Reading and writing data: CSV, Excel, SQL databases, JSON, and spatial formats
  • Indexing, grouping, merging, reshaping, summarising data
  • Statistical graphics and visualisation of data using Pandas, Matplotlib, and Seaborn
  • Day 4: Machine Learning

    Day 4 introduces three of the most fundamental and powerful techniques for analysing many kinds of real-world data in Python. The datasets are selected from a range of industries: financial, geospatial, medical, and social sciences. The syllabus is:

  • Linear and nonlinear regression with statsmodels and scikit-learn, with application to quality assessment and forecasting
  • Clustering of data using scikit-learn, with application to outlier detection
  • Classification with scikit-learn, with application to diagnosis and prediction
  • Supplemental materials

    We will supply you with printed course notes and a USB stick containing a complete Python environment based on VirtualBox. This saves time in the course and allows us to focus on using Python rather than installing it. The USB stick also contains kitchen-sink Python installers for multiple platforms, solutions to the programming exercises, several written tutorials, and reference documentation on Python and the third-party packages covered in the course.

    Other information

    Personal help:
    Your trainer(s) will be available after the course each day for you to ask any one-on-one questions you like — whether about the course material and exercises or about specific problems you face in your work and how to use Python to solve them.
    Food and drink:
    We will provide lunch, morning and afternoon tea, and drinks.
    The course will run from 9:00 to roughly 17:00 each day, with a breaks of an hour for lunch and 15 minutes each for morning and afternoon tea.

    Upcoming Courses

    27/03/2017 at Sydney

    We also offer custom courses on-site for teams within organisations. These are particularly appropriate if your team uses particular tools or data sources in its workflow. Please contact us to discuss your requirements.

    Upcoming Public Courses


    Python for Network Engineering:
    22 Mar – 24 Mar 2017

    View Details Book Now


    Python for Predictive Data Analytics:
    27 Mar – 30 Mar 2017

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    Introduction to Python:
    27 Mar – 28 Mar 2017

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    Python for Scientists & Engineers:
    08 May – 12 May 2017

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    Python for Scientists & Engineers:
    10 Jul – 14 Jul 2017

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    Python for Scientists & Engineers:
    14 Aug – 18 Aug 2017

    View Details Book Now



    “One of the best programming courses I have attended - thanks!”

    - Giant Billen, IAG Insurance

    “Excellent training course, excellently presented. Perhaps the best that I have had in the area of IT / programming.”

    - George Grozev, CSIRO (Clayton)

    “Both Ed and Henry presented well…. The course structure was adjusted to suit the participants quickly and easily.”

    - Jenet Austin, CSIRO (Black Mountain Laboratory)

    “Course content was well presented and easily digested. Practical exercises were an essential part of the course – a good ratio of lecture/play was achieved. Well done Ed and Henry!”

    - Steve Zegelin, CSIRO (Black Mountain Laboratory)

    “Very comprehensive intro to every aspect of python. Highly qualified trainer. Beyond my expectation on every aspect. ”

    - Baichuan Sun, CSIRO (Clayton)

    “I loved it. Ed was inspiring.”

    - Onoriode Coast, CSIRO (Narrabri, NSW)

    “One of the best training courses I've been on.”

    - David Scurrah, Bureau of Meteorology (Melbourne)

    “Instructor was superb - very impressive. I really enjoyed the course - thanks!”

    - Steven Edgar, CSIRO (Hobart)

    “Simply awesome!!”

    - James Park, Cisco (St Leonards)

    “It was a pleasure ... Shared feedback from all involved was that it’s been one of the most beneficial and well delivered training courses we’ve been a part of.”

    - Dylan Matthews, Simply Energy / GDF Suez (Melbourne)

    “Very impressed with the course, delivery. And depth of knowledge of Ed and Henry. Far exceeded my expectations and has greatly improved my core skills as well as inspired so many new ideas for my current work / projects. Thank you!”

    - Kelsey Druken, National Computational Infrastructure (Canberra)

    “The course was delivered by trainers who were extremely knowledgeable in their field. It was really good to learn from the best!”

    - Marius Roman, Transurban (Melbourne)

    “Really impressed by Python's capability and excited to use as alternative to MatLab, as is free and better supported.”

    - Carsten Hofmann, OMC International (Melbourne)

    “Was the most fulfilling and rewarding class I have taken since "general relativity" at uni. Was extremely well run. Excellent all round!”

    - Dr Millicent Maier, Australian Astronomical Observatory (Sydney)

    “This course has shown me how I could have done the work I was doing just last week 10x more efficiently in Python.”

    - Maruf Rahman, Geoscience Australia (Canberra)

    “The VM setup and USB is great. Ed is an excellent instructor - he presents well and welcomes any questions. He is clearly a super smart guy who has a great grasp on what he is teaching - able to just prototype on the fly and the course overall really opened my eyes to python. ”

    - Jack Hendy, Optiver (Sydney)

    “Great course. Enjoyed it and will follow up with some practical implementation of some of the work.”

    - Adam Grace, Optus (Sydney)