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This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. By the end of this course, students will be able to identify the difference between a supervised (classification/regression) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis.

Level: L2
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