
Intro to Data Mining
Course Description
In this course, you will learn data mining concepts. These concepts include pattern recognition, visualization, and artificial intelligence. Additionally, you will have a few “hands-on” opportunities using tools to assist in these efforts. This is an asynchronous, self-paced online course with no live instructor. The schedule is flexible, allowing learners to complete coursework and assignments on their own time.
Learning Outcomes
At the end of this course, you should be able to:
- Examine foundational concepts in data mining.
- Differentiate between descriptive and predictive elements of data mining.
- Contrast the strengths and weaknesses of supervised and unsupervised methods.
Course Schedule and Duration
Below is the course schedule. It is recommended that you work through one module per week. The entire course is estimated to take 15 hours to complete. Each module is estimated to take 15-18 hours to complete. Learners will be awarded a course completion certificate upon submitting the four module knowledge checks with an 80% completion score. The certificate is delivered within the Awards tool in the Brightspace course. *Schedule and assignments are subject to change. Any changes will be posted in Brightspace.
Module |
Topic & Readings |
Assignments |
1 – Foundations of Data Mining |
Topic 1: Data Concepts 1 |
Module 1 Quiz – 10 points |
Topic 2: Data Concepts 2 |
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Topic 3: Data Quality |
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2 – Components of Data Mining |
Topic 4: Pattern Recognition |
Module 2 Quiz – 10 points |
Topic 5: Visualization |
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Topic 6: Large-scale Data |
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3 – Methods for Data Mining |
Topic 7: Supervised Machine Learning |
Module 3 Quiz – 10 points |
Topic 8: Unsupervised Machine Learning |
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Topic 9: Deep Learning |

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