Python Training

Python for Predictive Data Analytics

This is a course for data analysts, quants, statisticians, software developers, and other technical staff interested in learning to use Python for analysing and visualising data and performing powerful predictive analytics.

Prerequisites

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 processing, analysing, modelling, and visualising various kinds of data, with a focus on time series. You will have had experience with using Python for various scripting, data-manipulation and plotting tasks with data in a variety of formats, including CSV, Excel spreadsheets, SQL databases, JSON, and API endpoints. You will have applied powerful tools for optimisation, regression, classification, and clustering, in useful practical settings on a variety of 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.

  • Why use Python for data analytics? What’s possible?
  • Python syntax and concepts: an introduction through examples
  • Essential data types: strings and lists
  • Input and output of text data (including CSV files)
  • String methods
  • Dictionaries and their applications
  • Worked example: fetching and ranking real-time web data
  • Day 2: Further Python essentials

    Day 2 introduces further important concepts for real-world scripting in Python.

  • 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
  • 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.

  • Fast, powerful data analysis with Pandas
  • Reading and writing data formats: CSV, Excel, SQL databases, JSON
  • Indexing, grouping, merging, reshaping, summarising data
  • Working with missing and noisy data
  • Working with time-series data
  • Statistical graphics and visualisation of data
  • 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.

  • 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.
    Timing:
    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

    11/09/2017 at Sydney

    09/10/2017 at Melbourne

    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

    Melbourne

    Introduction to QGIS:
    19 Jun – 20 Jun 2017

    View Details Book Now

    Melbourne

    Python for Scientists & Engineers:
    10 Jul – 13 Jul 2017

    View Details Book Now

    Melbourne

    Python for Geospatial Analysis:
    10 Jul – 14 Jul 2017

    View Details Book Now

    Sydney

    Python for Finance:
    24 Jul – 26 Jul 2017

    View Details Book Now

    Sydney

    Python for Predictive Data Analytics:
    11 Sep – 14 Sep 2017

    View Details Book Now

    Melbourne

    Python for Predictive Data Analytics:
    09 Oct – 12 Oct 2017

    View Details Book Now

    Location

    Testimonials

    “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)