Courses in Artificial Intelligence & Machine Learning

Three Springs Technology is offering hands-on training workshops for companies in the Oil & Gas and Mining space in Western Australia. The goal is to enhance the digital competencies of your personnel. Whether you’re a geoscientist or engineer, the workshop is designed to give users an overview of Data Science and Machine Learning tools. Three Springs Technology teaches results-oriented approaches to real-wold problems using Python programming. The program runs for two weeks and is preferably hosted at your premises.

Time Series

Automatically predict time-series problems


Cluster data in a self-supervised manner


Think about your domain problems by information content

Part‎‎‎‎‎‎ Training descriptionCourse durationMax. number of participants per course
1Foundations of Python3 days20
2Data science and visualisation3 days20
3Artificial Intelligence & Machine Learning3 days20
4Onsite support & mentoring while participants continue to learn or extend materialAs requested20

Part 1: Foundations of Python

This course takes a hands-on approach to teach participants to automate tasks using industry examples where possible. At the end of this, you should be able to import files, change the data, and export them. You will also see how NumPy and Pandas can be used as an alternative to Excel and Matlab. Learn how you can use Python to interact with applications to automate the mundane parts of your job.


  • Basics of Python
  • Load and saving data
  • Basics of data visualisation
  • Basics of NumPy and Pandas
  • Practical project

Part 2: Data Science and Visualisation

This course takes you a step further and teaches you data visualisation and analysis in Python. Use interactive plotting with spatial or tabular data to create notebooks with interactive visualisations.


  • Basic SQL with SQLite 3
  • Tabular data with Pandas
  • Data visualisation
  • Plotting geographical data
  • Interactive plotting and dashboards
  • Time series
  • Data Science Basics
  • Supervised learning
  • Unsupervised learning
  • Practical project

Part 3: Artificial Intelligence and Machine Learning

This course teaches you how to frame problems using an array of Machine Learning approaches. We take a hands-on approach taking you through examples from various industries using Jupyter notebooks. In the end, the goal is to understand the main approaches and have some intuition about suitability for different problems.


  • Types of machine learning approaches
  • Introduction to neural networks
  • Machine learning tools
  • Large data and Dask
  • Tabular Data and Pandas
  • Time series and Prophet
  • Advanced NN architectures
  • Image segmentation
  • Object detection
  • Explainability
  • Practical project

Interested? For bookings and more information email us: