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Fundamentals of Data Science

An ever-increasing volume of research and industry data is being collected on a daily basis. Skilled data scientists are needed to process and filter the data, to detect new patterns or anomalies within the data, and gain deeper insight from the data.

This course provides students with a foundation in basic data mining, data analysis, and predictive modelling concepts and algorithms. Using practical exercises, students will learn data analysis and machine learning techniques for model and knowledge creation through a process of inference, model fitting, or learning from examples. 

Practical experience:

  • Hands-on data mining projects

Software: Python is used for class assignments. There is no additional cost for this product.

Course typically offered: Online in Fall and Spring

Prerequisites: Before enrolling in the course, students need to have prior knowledge of statistics for data analytics or equivalent practical experience, as well as a basic understanding of the Python Programming Language. For students who do not have knowledge of statistics for data analytics, it is recommended to take the Statistics for Data AnalyticsIntroduction to Statistics or Linear Algebra for Machine Learning course. You can test your level of statistical knowledge by taking the online Self-Assessment quiz. For students who do not have basic knowledge of Python programming language, it is recommended to take Introduction to Programming course.

Next Steps: Upon completion of this course, consider taking other courses in Machine Learning Methods program to continue learning. 

More Information: For more information about this course, please contact

Course Number: CSE-41258
Credit: 3.00 unit(s)
Related Certificate Programs: Machine Learning Methods

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