Course Catalog

3 Unit(s)

This course will introduce the basic concepts of data analytics as applied in various business contexts. After learning the basic concepts, students will learn how to differentiate between various topics such as statistical analysis, data mining, business intelligence, business analytics, and data science to describe which approach is most suitable given a certain problem. Finally, students will gain exposure to the various tools and programming languages that are relevant to both business and data analytics, and how these tools yield critical analysis leading to improved business decisions.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

4 Unit(s)

This course is the first in a two-part series, the second of which culminates in achievement of a Google Data Analytics Professional Certificate. In this first course, students will be introduced to basic foundations of data analytics and data-driven decision making. They will explore how to prepare data for analysis, including processing and cleaning data. In addition to furnishing students with critical thinking and asking skills, these exercises will prepare students for the second course in the series, DATA 60B. This course is offered in partnership with Outlier.org and is available to all undergraduate students. In addition to earning academic credit, students may receive a professional certificate from Coursera.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

4 Unit(s)

This course is the second in a two-part series which culminates in achievement of a Google Data Analytics Professional Certificate. The first course, DATA 60A, introduces students to the fundamentals of data analysis along with processes to prepare data for analysis. In this course, students will dive deeper into data analysis. This course covers data-driven decision making, data visualization, data ethics, and data analysis with R programming. The course includes a final capstone case study tailored to prepare students for competitive jobs in the field. This course is offered in partnership with Outlier.org and is available to all undergraduate students. In addition to earning academic credit, students may receive a professional certificate from Coursera. Prerequisite(s): DATA 60A.

View Course Sections: Summer 2024 , Spring 2024

3 Unit(s)

This course will introduce the concept of data visualization that will include theory as well as a hands-on component. Students will examine how to represent data for exploratory data analysis in a variety of business contexts. Students will have the opportunity to design and build interactive dashboards using advanced data visualization platforms such as Excel and Tableau for presenting enterprise performance data, and for performing business analysis quickly and easily. Prerequisite(s): MATH 40.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

3 Unit(s)

This course introduces the students to the technologies, applications, platforms, and practices for the collection, integration, analysis, and presentation of business data and information. The purpose of business intelligence (BI) is to support better business decision making. This course provides an overview of BI and hands-on practical exercises in a variety of business contexts to address organizational strategies and goals. Topics include fundamental of data integration, data warehousing and data lakes, data visualization, and business performance management. Prerequisite: DATA 50 and MATH 104.

View Course Sections: Spring 2024 , Fall 2023

3 Unit(s)

This course introduces students to core data analysis techniques using SAS. Students will learn to access data files, manipulate and transform data, combine data sets, and create basic detail and summary reports using SAS procedures. They will also conduct statistical estimations such as Chi-square tests, t-test, and multiple regressions. This course introduces basic concepts found in the SAS Certified Base Programming exam. Prerequisite: DATA 50 and MATH 104.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

3 Unit(s)

In this course, students will learn and apply R programming language for exploratory data analysis. Students will use R for data access, entry, cleansing, and manipulation for data exploration and visualization. They will also use R to conduct basic descriptive and inferential statistical analysis. Prerequisite(s): DATA 102.

View Course Sections: Summer 2024 , Fall 2023

3 Unit(s)

In this course, students will learn the basics of analysis of social media and web data, using R programming language. Students will also learn the basics of text mining. Students will use and apply R for techniques such as sentiment analysis in order to gain behavioral insights from social media and web data utilizing various application programming interfaces (API) and will take a critical approach to the benefits and limits of such analysis. Prerequisite(s): DATA 104.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

3 Unit(s)

In this course, students will learn and apply the Python programming language as well as the basics of machine learning (ML), from basic classifications to decision trees and clustering. Prerequisite(s): DATA 105.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

3 Unit(s)

In this course, students will apply the Python programming language as well as the basics of natural language processing (NLP), including sentiment analysis, summarization, and dialogue state tracking. Prerequisite(s): DATA 110.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

3 Unit(s)

This course introduces students to Generative Artificial Intelligence (GenAI) that can create new content, such as text, audio, images, and video. The course will incorporate emerging open-source platforms to teach GenAI concepts and related fields, such as prompt engineering. It will leverage the capabilities of GenAI platforms to enhance the learning experience of students by providing real-time assistance, personalized feedback, and interactive problem solving.

3 Unit(s)

This course introduces students to the world beyond SQL and the concept of Big Data (structured and unstructured), its characteristics, and the existing and emerging ecosystems. Students will address the challenges of managing and handling big data in a business or organizational context, as well as the larger cultural and ethical implications. Students will learn about NoSQL databases, and how to use existing and emerging software tools such as Hadoop for data access, manipulation and reporting. Prerequisite: DATA 102 and ITM 108.

View Course Sections: Spring 2024 , Fall 2023

3 Unit(s)

Artificial Intelligence (AI) is increasingly being viewed by a variety of businesses as a strategic value. This course introduces students to the basics of AI and how different businesses view the role and strategic value of AI. This is done by examining business applications of AI in a range of vertical business segments, such as finance, healthcare, transportation, among others, and identification of key business values and benefits afforded by AI across each of these verticals. Prerequisite(s): DATA 50 and DATA 110.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

3 Unit(s)

This course provides the students an opportunity to apply knowledge and skills they have gained through the degree program to a hands-on project based on a case study using real data. Alternatively, students may choose, with the permission of their management, to work with an organization within their place of employment, conducting quantitative analysis on actual operational data, providing findings back to their organization. Prerequisite: DATA 105, DATA 111, ITM 108, and DATA 120.

View Course Sections: Summer 2024 , Spring 2024 , Fall 2023

13 Unit(s)

Provides individual study of selected topics under supervision of a faculty member. Students are limited to one directed study course per trimester. Prerequisite: consent of the department.