商业数据分析

This survey course will look at today's American 业务 systems including a study of various types of 业务es and the information they gather, 商店, 和过程, including administration and management of people, 设施, 和信息. Course will include relevant computer experience simulating 业务 situations.

This is an introductory course teaching applied job skills in close connection to the concepts and theories that drive the daily decisions relevant to data analysis and 业务 intelligence. Each module focuses on a primary theme with real world cases where students will start by grappling with 业务 problems and the underlying data to methodically drill down and solve problems from a technical approach. 这些主题包括, 统计学的应用, 数据可视化工具在Excel, 线性回归, 时间量系列, 分类算法, 数据偏差.

Data wrangling transforms and maps raw data into formats highly useful for analytics and improved decision making. The course is structured to provide students with in‐demand job skills in SQL focusing on real‐world applications from companies such as YouTube and Kickstarter. 在线讲座的组合, live discussions with course instructors and classmates refine student capability in applying SQL tools (no coding experience is required) to 业务 situations. 前提条件:BDA 337.

Data 可视化 is an interdisciplinary field that deals with the visual representation of information and data through graphs, 地图和图表来识别, 了解和沟通趋势, 模式，有时是异常值. This course is structured to provide students the tools to design usable dashboards using real‐world datasets from Uber, 《赌博十大平台排行》, 美国人口普查局和其他机构. 在线讲座的组合, live discussions with course instructors and classmates refine student capability in applying Tableau (no coding experience is required) to 业务 situations. 前提条件:BDA 337.

This course focuses on developing programming skills relevant to data analysis and machine learning with a focus on real‐world applications. State‐of‐the‐art low‐code solutions are used throughout the course, allowing students to immediately begin running models that focus on understanding conceptual material first before diving deeper into technical details. Students use the Python programming language, along with a complete set of open source tools. The material covers the various phases of exploratory data analysis: importing data, 清理和转换数据, 算法思想, 分组和聚合, 可视化, prediction and communication of results. 前提条件:BDA 337和BUS 261.

As a basic statistics course applicable to education, 业务, 以及自然科学, this course will include topics such as descriptive statistics, 正常的, 二项, F-, 和卡方分布, 假设检验. Optional topics might include additional non-parametric tests and ANOVA. A TI-83 graphing calculator or Microsoft Excel is required. 前提条件:C-或C以上 AMTH 101 or CMTH 101 or m 201 or m 252 or m 271 或同等.