Introduction to Python Scripting, Data Analysis and Machine Learning

AUSTRALIA (PERTH): 4-8/5/26
AUSTRALIA (MELBOURNE): 11-15/5/26
AUSTRALIA (BRISBANE): 18-22/5/26

Course Brief

Python is the most popular coding language for data science and machine learning, used by major corporations, professionals, academics, and students. It is a high-level scripting language that combines components from various compiled packages. Python can access modules in other software packages, merge these with data visualization tools like matplotlib, or apply machine learning modules from sci-kit learn in a single script. This eliminates the need to export, import, and run each package separately.

Python is superior to Excel and most commercial software for Exploratory Data Analysis in functionality and versatility as workflows can be customized easily. It also makes documenting workflows easy for record keeping and is fully auditable.

Python is the most commonly used language for Machine Learning due to its ease of use, versatility and wide community support. I is suitable for beginners and experienced coders and offers a extensive library of packages to carry out most data analysis, machine learning and data visualization tasks.

This course uses examples of data analytics and statistical processing of data encountered in subsurface materials sampling (i.e. soils and rocks, ). Scripts and examples used in this course will be appropriate to the needs of scientists and engineers.

Course Outline

Introduction to Python and Setup

Basic Python Programming

Data Preprocessing and Exploration

Building and Evaluating Models

Building Models, Model Deployment and Getting Help