Introduction to Data Science
This course introduces data science in python. It is both an introduction to data science itself, as well as learning how to achieve those goals in Python.
Prerequisites
Python familiarity is required. We recommend having completed our Introduction to Python course, or having at least 6 months experience using Python regularly.
The course will teach and use statistical concepts. A late high school / early university level of statistics and mathematics is recommended, but not required.
Expected Outcomes
You will learn how to perform data science to analyse data, run simulations, and validate the results. You will learn how to do this with the Python programming language, as well as understanding libraries including Polars, Plotly, and SciPy, and how they fit into the broader data science workflow.
Topics covered in the course include:
- Data analysis with Polars
- Plotting best practices to go beyond simple visualisations with Plotly
- Statistic methods for analysing data
- Running simulations on data to confirm hypothesis
- A broad overview of relevant parts of the Python ecosystem
Course Syllabus
Personal help
We are happy to offer on-the-spot problem-solving after each day of the training for you to ask one-on-one questions — whether about the course content and exercises or about specific problems you face in your work and how to solve them. If you would like us to prepare for this in advance, you are welcome to send us background info before the course.
Other information
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Format:
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Courses are conducted online via video meeting using Python Charmers' cloud notebook server for sharing code with the trainer(s).
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Computer:
Hardware: we recommend ≥ 8 GB of RAM and a webcam. Preferably also multiple screens and a quiet room (or headset mic).
Software: a modern browser: Chrome, Firefox, or Safari (not IE or Edge); and Zoom.
Coding: we have a cloud-based coding server that supports running code and sharing code with the trainer(s).
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Timing:
Most courses will run from 9:00 to roughly 17:00 (AEST/AEDT) each day, with breaks of 50 minutes for lunch and 20 minutes each for morning and afternoon tea.
Certificate of completion:
We will provide you a certificate if you complete the course and successfully answer the majority of the exercise questions.
Materials:
You will have access to all the course materials via the cloud server. We will also send you a bound copy of the course notes, cheat sheets, and a USB stick containing the materials, exercise solutions, and further resources.
Upcoming Public Courses
Online
Deep Learning with PyTorch:
26–29 July 2026
- 26 Jul 2026 23:00 - 27 Jul 2026 07:00 UTC
- 27 Jul 2026 23:00 - 28 Jul 2026 07:00 UTC
- 28 Jul 2026 23:00 - 29 Jul 2026 07:00 UTC
Online
Creating Dashboards in Python:
30–31 July 2026
- 30 Jul 2026 23:00 - 31 Jul 2026 07:00 UTC
Online
Real World Programming in Python:
9–11 August 2026
- 09 Aug 2026 23:00 - 10 Aug 2026 07:00 UTC
- 10 Aug 2026 23:00 - 11 Aug 2026 07:00 UTC
Online
Data Analysis with Polars:
23–25 August 2026
- 23 Aug 2026 23:00 - 24 Aug 2026 07:00 UTC
- 24 Aug 2026 23:00 - 25 Aug 2026 07:00 UTC
Online
Introduction to Python:
30 August 2026 – 1 September 2026
- 30 Aug 2026 23:00 - 31 Aug 2026 07:00 UTC
- 31 Aug 2026 23:00 - 01 Sep 2026 07:00 UTC
Online
Open Office Hour - Q&A on Python for Beginners:
10 September 2026
- 05:30 UTC: 1 hour
Online
Open office - Q&A on Machine Learning:
17 September 2026
- 05:30 UTC: 1 hour
Online
Introduction to Python:
18–20 October 2026
- 18 Oct 2026 22:00 - 19 Oct 2026 06:00 UTC
- 19 Oct 2026 22:00 - 20 Oct 2026 06:00 UTC
Online
Introduction to Python:
29 November 2026 – 1 December 2026
- 29 Nov 2026 22:00 - 30 Nov 2026 06:00 UTC
- 30 Nov 2026 22:00 - 01 Dec 2026 06:00 UTC
Register your interest
Other courses and locations
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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!”
“Great course. Enjoyed it and will follow up with some practical implementation of some of the work.”
“One of the best training courses I've been on.”
“I loved it. Ed was inspiring.”
“Really impressed by Python's capability and excited to use as alternative to MatLab, as is free and better supported.”
“Very comprehensive intro to every aspect of python. Highly qualified trainer. Beyond my expectation on every aspect.”
“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.”
“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!”
“Simply awesome!!”
“Both Ed and Henry presented well…. The course structure was adjusted to suit the participants quickly and easily.”
“Excellent training course, excellently presented. Perhaps the best that I have had in the area of IT / programming.”
“One of the best programming courses I have attended - thanks!”
“This course has shown me how I could have done the work I was doing just last week 10x more efficiently in Python.”
“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.”
“Was the most fulfilling and rewarding class I have taken since "general relativity" at uni. Was extremely well run. Excellent all round!”
“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!”
