This module covers concepts such as Supervised and Unsupervised Learning. You will learn to use open source Python libraries like Scikit-learn, Pandas, as well as Numpy to preprocess datasets, train, test and evaluate different Machine Learning (ML) models. Choose between ML models such as Linear Regression, k-NN, Naïve Bayes and K-Means to solve problems through regression, classification and/or clustering.
Upon completing the module, you will be able to explain the essential principles of machine learning, and possess hands-on experience in building, training, validating and deploying machine learning models using Python.
Machine Learning Fundamentals is a module selected from the Specialist Diploma in Applied Artificial Intelligence. It enables you to either reskill or upskill without the need to pursue a full specialist diploma. As this is a stackable course, you may choose to complete the remaining modules within the validity period of 2 years to receive the full Specialist Diploma qualification.
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