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MIS380 - Data Visualization I
Course Description
This course will introduce students to best practices in data visualization. Effective design, choice of chart type, effective use of color, how to explore data visually, how to build data dashboards, and how to explain concepts and results visually in a compelling way with data will be covered.
Credit Hours: 3
MIS415 - Data Visualization II
Course Description
This course will continue the concepts of effective visualization learned in Data Visualization I. This course will use PowerBI to introduce students to using an industry tool for data visualization. Students will learn to use the PowerBI environment, prepare and transform data, create data models, create measures using DAX, create reports and dashboards.
Credit Hours: 3
MIS450 - Data Mining
Course Description
Course Description
Through this course students are provided with an overview of techniques for data mining. Students will use statistical software as the primary tool for this course. This course will cover various data mining methodologies and different analyses techniques. Recommended Prior Course: MIS445
Credit Hours: 3
MIS451 - Data Analysis I with Python
Course Description
This course will introduce students to the basic terminology of data science and the three domains. Students will also be introduced to Python. Students will also explore types of data and exploration of data. Probability will be explored in addition to visualizing probability as well as statistical knowledge needed for data science. Algorithms and models including pre-trained and learning transfer will also be introduced.
Credit Hours: 3
MIS410 - Databases and SQL
Course Description
This course will introduce students to databases and structured query language (SQL) needed to work with data. Students will learn how to create a database using SQL, add and update tables, and different clauses and functions for extracting and querying data. Additionally, students will learn how to execute SQL statements in Python.
Credit Hours: 3
MIS475 - Applied Analytics
Course Description
This course will continue to use of Python for advanced topics in web scraping. Students will use programming techniques and technologies, such as data analysis, natural language parsing, and information security. Students will learn how to collect, transform, and use data from different web sources.
Credit Hours: 3
