Bachelor of Science in Data Science

3学分

This course introduces practices in data analytics foundational to the industry and the field of data analytics. Covered are theories of analytics, the phases of the analytics lifecycle, analysis and 探索 of data, relevant statistics for data 建模, data visualization, and the tools used for data analytics.

3学分

This course provides students with a basic understanding of 编程 发展 practices. Concepts covered include the application of algorithms and logic to the design and 发展 of procedural and object oriented computer programs to address the problem solving requirements associated with 业务 information systems. This course will cover procedural 编程 concepts, including 数据类型, controls structures, functional decomposition, 数组, 文件, 类, 和对象.

3学分

This course covers the three most popular data 编程 languages: Python, Java®, and Ruby. 学生s will be introduced at a high level to the 编程 languages as they relate to database design, 发展, and management.

3学分

This course provides an overview of advanced spreadsheet 功能 used in data analysis. Topics include filters, 排序, 查找, 公式, 功能, 宏, 数据透视表, graphs and charts, 指示板, 形式, 报告, 查询, statistical analyses, and data validation.

3学分

This course provides a foundational 作品hop on data structures, which is a functional component of 业务 intelligence (BI) within an organization. Building upon basic 编程 and database structure, this course builds competencies for the student to recognize the structure of data contained in deployed enterprise information systems.

3学分

This course provides an introduction to the Python 编程 language. 学生s will review the function and use of 变量, 数据类型, 列表, 元组, 功能, 类, 文件, 异常, search/排序 algorithms, memory management, and code testing. Additional topics may include Integrated Development Environments (IDEs), data visualization, global data sets, and Web Application 编程 Interfaces (APIs).

3学分

This course covers fundamental database concepts including SQL, non-relational databases, distributed databases and database architectures. 学生s are provided an overview for how to manage, 显示, 排序, 集团, 检索, and organize data for the application or tool associated with the software 发展 taking place within an organization

3学分

This course provides an overview of R, which is a 编程 language commonly used for data science, statistical analysis, and data visualization. Topics include syntax, 变量, 运营商, 功能, data structures, statistical data sets, and graphical presentation.

3学分

This course provides an overview of applied 业务 research, statistical tools, and data analytics used to support strategic decision making. 学生s will examine methods used to frame 业务 problems, conduct research, collect and evaluate data for validity and reliability, determine patterns and trends in performance, and effectively present conclusions.

3学分

Structured Query Language (SQL) is a domain-specific language used to store, 查询, and 操作 data within databases. This course provides an overview of SQL and relational database applications with a focus on SQL syntax, 数据类型, 关键字, 功能, structured and unstructured data, and data 建模.

3学分

This course provides an overview of database administration, including database 实现ation, configuration, authentication, 监控, 备份, and security. 学生s will examine database architecture with a focus on 业务 requirements, data integrity, and the ethical handling of private data.

3学分

This course provides an overview of Exploratory Data Analysis (EDA), including the cleaning, 准备, 探索, and visualization of data. 学生s will review machine learning algorithms, neural net作品, and Artificial Intelligence (AI) concepts used to 分析 data sets and build intelligent applications.

3学分

This course will introduce students to data analytics and 建模 through contemporary 业务 tools. 学生s will examine how data is architected and organized. After completion of this course, students will be able to understand the different data models used to store data, several schemas that drive how data is structured, and provide other database concepts relating to the design and architecture of data.

3学分

This course covers 数据挖掘 techniques for structured and unstructured data. Learn 编程 techniques and algorithms to transform large quantities of data into usable 业务 Intelligence (BI).

3学分

This course introduces students to tools and techniques needed to present data, both simple and complex, to gain support and recommend 业务 decisions. 学生 will use graphical tools such as graphs, 动画, and presentation techniques to communicate the message behind the data and improve decision making. Topics include requirement gathering, graphical representation of data sets, visualization techniques and tools, and data validation.

3学分

This course reviews the origin and applications of big data within the framework of current 业务es. Topics include data validation, 处理, and predictive analytics used in a timely manner to make informed decisions.

3学分

This course provides an overview of machine learning, including the use of algorithms, neural net作品, and supervised, 无人管理的, and reinforcement learning to automate advanced computer tasks.

3学分

This course provides an overview of predictive 建模 techniques, with a focus on statistical analyses, 数据挖掘, and machine learning tools used to find patterns and trends, identify potential risks, and forecast probable outcomes within various data sets.

3学分

This capstone course combines the 技能 and applies the knowledge 从 various courses in the Bachelors of Science in Data Science program. 学生 teams working with large data sets combine the concepts of statistics, 编程, 数据挖掘, data analysis, and data visualization to design, 实现, and present a data science project representing a real-world application to decision-making executives.