Data Science Path
To Boost Up Your Career.

Course 1

Intro to Data Science - Clustering with Unsupervised Methods

Students will learn about the practices of data science. As an unsupervised method, students will gain modeling skills with real-world data with clustering algorithms (top-down, bottom-up, and k-means). Students will improve the models built and develop intuition behind data analysis procedures.

Intro to Data Science - Clustering with Unsupervised Methods

4 Levels options | 4 Time options
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Course 2

Intro to Data Science - Prediction with Supervised Methods

In this course, data science goals and its methods are introduced. Some supervised techniques along with performance metrics will be covered including Logistic Regression, Decision Trees and Neural Networks.

Intro to Data Science - Prediction with Supervised Methods

4 Levels options | 4 Time options
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Course 3

Feature Selection Methods

Students will learn a variety of effective methods and perspectives to determine what features to keep in data modeling using statistical and heuristics methods.

Feature Selection Methods

4 Levels options | 4 Time options
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