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Learner Reviews & Feedback for Introduction to Machine Learning: Supervised Learning by University of Colorado Boulder
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About the Course
In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM.
Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course. In this course, you will need to have a solid foundation in Python or sufficient previous experience coding with other programming languages to pick up Python quickly.
We will be learning how to use data science libraries like NumPy, pandas, matplotlib, statsmodels, and sklearn. The course is designed for programmers beginning to work with those libraries. Prior experience with those libraries would be helpful but not necessary.
College-level math skills, including Calculus and Linear Algebra, are required. Our hope for this course is that the math will be understandable but not intimidating.
This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more:
MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder
MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
Top reviews
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I was happy not much with the shoddiness in the assignments but by the fact that this course was centered more about practicing and reading by the student themselves.
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Peer review requirements are too specific and contain some minor errors that can be confusing.
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26 - 27 of 27 Reviews for Introduction to Machine Learning: Supervised Learning
By Red R 2
•Jul 6, 2024
Lab errors and malfunction! Hardly or slow response to action
By Pran K M
•Dec 18, 2023
frustrating lecture zero level assignment super level