{"id":241,"title":"Introduction to Machine Learning using Python: Introduction \u0026 Linear Regression","url":"https://intersect.org.au/training/course/python205","description":"Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries.\n\n- Understand the difference between supervised and unsupervised Machine Learning.\n- Understand the fundamentals of Machine Learning.\n- Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training.\n- Understand the Machine Learning modelling workflows.\n- Use Python and scikit-learn to process real datasets, train and apply Machine Learning models\n\nThis course assumes a good deal of Python, and data manipulation in Python. Learners should have attended [Learn to Program: Python](https://intersect.org.au/training/course/python101/), and either [Data Manipulation in Python](https://intersect.org.au/training/course/python201), or [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/).  \n If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries.  \n Maths knowledge is not required. However, there are a few mathematical formulae covered in this course and the references will be provided. Having an understanding of the mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them.","doi":"10.5281/zenodo.6423722","licence":"Reserved","contact":"training@intersect.org.au","keywords":["Python"],"remote_updated_date":null,"remote_created_date":null,"created_at":"2022-06-07T05:14:39.066Z","updated_at":"2025-12-15T14:00:20.387Z","content_provider_id":5,"target_audience":[],"authors":["Intersect Australia"],"contributors":[],"subsets":[],"resource_type":[],"other_types":null,"version":null,"status":"active","date_created":null,"date_modified":null,"date_published":null,"prerequisites":null,"syllabus":null,"learning_objectives":null,"fields":[],"scientific_topics":[],"operations":[]}