Python Training

Python for Scientists & Engineers

This course teaches you powerful skills for scientific computing for various applications in science and engineering fields.

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 use Python to solve problems involving the use of various scientific data sets. You will know what's available with Python, how to structure your code, and how to use Python's data structures competently to write clean, efficient code. You will have had experience with using Python for various scripting and data manipulation tasks, including easily creating beautiful plots, performing Monte Carlo simulations and image analysis, analysing time-series data, constructing statistical models, and scaling up to handling medium-sized (sub-terabyte) data.

Course Syllabus

Day 1: Introduction to Python

Day 1 covers the basics of using Python for general programming tasks, including tips and tricks for making this easy:

  • Why use Python? What’s possible? Python versus other languages
  • How to install a complete Python development environment (with plotting etc.)
  • The Jupyter notebook and shell for rapid prototyping
  • Python syntax and concepts
  • Essential data types, tips and tricks
  • Modules and packages; handling exceptions
  • Tour of the amazing standard library
  • Worked example: fetching and ranking real-time temperature data for global cities
  • Day 2: Handling, Analysing, and Presenting Data in Python

    Day 2 gives a comprehensive introduction to reading and writing the most important data formats in science and engineering and how to analyse and visualise data easily:

  • Reading and writing essential data formats: CSV, Excel, SQL databases
  • Visualisation and statistical graphics with Seaborn
  • Indexing and selecting data in Pandas
  • Data fusion: joining & merging datasets
  • Summarisation with “group by” operations; pivot tables
  • Time-series analysis: parsing dates, resampling
  • Worked example: creating automated reports with Pandas and nbconvert
  • Day 3: Essentials of Scientific Computing with Python

    Day 3 teaches the use of Python for numerical and scientific computing. It covers array and matrix manipulation, working with labelled and tabular data, an overview of available scientific routines, and creating simple but beautiful 2D plots, with the packages NumPy, SciPy, and Matplotlib:

  • Introduction to numerical data manipulation with NumPy
  • Statistics in Python: modelling, confidence intervals, hypothesis testing, regression, Monte Carlo simulation, with scientific applications
  • Tour of SciPy and related packages for scientific data manipulation, with fancy demos: clustering, interpolation, optimisation, dense & sparse linear algebra, signal processing, image processing, unit conversions
  • 2D plotting with Matplotlib
  • Demos: interactive and 3D plotting with Plotly
  • Day 4: Real-world programming in Python

    Day 4 focuses on techniques for creating larger codebases in teams, interfacing Python with other data sources, scaling from small datasets and small problems to realistic ones that may be too big for memory or too slow for one computer to process:

  • Integrated development environments; tools for benchmarking and profiling code
  • Finding and installing packages with conda and pip
  • Writing maintainable code with classes
  • Working in teams: creating modules and packages; Python idioms and style
  • Interfacing Python with other languages: Excel, R, C/C++, Fortran, Matlab (topics on request)
  • Interfacing with NetCDF and/or HDF5 data (on request)
  • Introduction to parallel computing with Dask
  • 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

    10/07/2017 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)