Course Overview
Learning Objectives
- Describe and define basic concepts in data mining and analytics.
- Describe and define the basic procedure in data mining and analytics.
- Explain and use prominent algorithms in data analytics, including predictive analytics, clustering, association rule mining, text mining, and visual analytics.
- Explain the process of inferring knowledge and insights from heterogeneous data sources.
- Choose appropriate tools and algorithms to solve the data analytics task.
- Use data analytics tools with a graphical user interface (e.g., Orange Data Mining) to perform basic data analytics tasks such as data cleaning, data visualization, clustering, association rule mining, predictive modeling, and text mining.
- Use Python in Jupyter Notebook to perform basic data analytics tasks such as data cleaning, data visualization, and predictive modeling.
- Interpret the results of data analytics while acknowledging their limitations.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):