Python Training

Python for Scientists & Engineers

This is a course for scientists and engineers interested in using Python for solving computational problems that arise in daily work and automating the processing of different kinds of scientific data.

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 how to use Python for basic scripting and automation tasks, including tips and tricks for making this easy:

  • Why use Python? What’s possible?
  • The Jupyter notebook for rapid prototyping and automated reporting
  • Modules and packages
  • Python syntax and concepts: an introduction through examples
  • Essential data types: strings, tuples, lists, dicts
  • Worked example: fetching and and ranking real-time data from a web API
  • Raising and handling exceptions

Day 2: Handling, Analyzing, and Presenting Data in Python

Python offers amazingly productive tools like Pandas for working with different kinds of data. Day 2 gives a thorough introduction to analyzing and visualizing data easily:

  • Reading and writing essential data formats: CSV, Excel, SQL, time-series (others on request)
  • Indexing and selecting data in Pandas
  • Data fusion: joining & merging datasets
  • Summarization with “group by” operations; pivot tables
  • Time-series analysis: parsing dates, resampling
  • Interactive visualization and statistical graphics with Altair

Day 3: Essentials of Scientific Computing with Python

Day 3 teaches you how to use Python for numerical and scientific computing. It covers array and matrix manipulation and an overview of available scientific routines, including an introduction to statistical modelling:

  • Introduction to manipulating vectors and matrices with NumPy
  • Statistics in Python: modelling, confidence intervals, hypothesis testing, regression, Monte Carlo simulation
  • Tour of SciPy and related packages for scientific data manipulation, with fancy demos: unit conversions, interpolation, optimization, dense & sparse linear algebra, image processing, signal processing

Day 4: Real-world programming in Python

Day 4 focuses on techniques for creating larger codebases in teams and scaling up from small datasets to large ones that are too big for memory or too slow for one computer to process. It also introduces machine learning for automatically inferring complex models from large datasets:

  • Best practices: creating scripts, modules and packages
  • Using IDEs and revision control with Git
  • Python idioms and style
  • Speeding up code by 4x to 10,000x: profiling, vectorization, JIT compilation, parallel computing
  • Introduction to machine learning: classification, non-linear regression, clustering with scikt-learn
  • Validation and model selection

Supplemental materials

We will supply you with printed course notes, cheat sheets, and a USB stick containing 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 breaks of 50 minutes for lunch and 20 minutes each for morning and afternoon tea.

Upcoming Courses

Brisbane

Python for Scientists & Engineers:
19 Aug – 22 Aug 2019

Cliftons, Level 3, 288 Edward Street, Brisbane CBD

Brochure Book Now

Melbourne

Python for Scientists & Engineers:
21 Oct – 24 Oct 2019

Cliftons, Level 1, 440 Collins Street, Melbourne CBD

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Canberra

Python for Scientists & Engineers:
02 Dec – 05 Dec 2019

Cliftons, Level 2, 10 Moore Street, Canberra CBD

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Other Locations

Python for Scientists & Engineers:
Dates TBA

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Testimonials

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

- Marius Roman

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

- Adam Grace

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

- David Scurrah

“I loved it. Ed was inspiring.”

- Onoriode Coast

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

- Carsten Hofmann

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

- Baichuan Sun

“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

“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

“Simply awesome!!”

- James Park

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

- Jenet Austin

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

- George Grozev

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

- Giant Billen

“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

“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

“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

“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