18 courses with the subject ANLY, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
ANLY 2500Introduction to Business Analytics3
Credit(s) | $19.50 Fee This course covers prevalent methods and tools for data management, processing, and visualization. Students are introduced to the Python programming language for processing, visualizing, and analyzing data. In addition, the course includes an overview of the Tableau software for data visualization. Course emphasis is on mastering basic software functionality and developing intermediate to advanced skills in working with and presenting data. (Fall, Spring, Summer) [Graded Letter]
Credit(s) | $63 Fee An introduction to the management and organization of data, with a particular emphasis on the current database tools for industry analytics. Students will learn how to develop a successful data strategy to create business value from data assets. Topics include the logical structure of databases as well as the methods and technology for efficient data storage, retrieval, and presentation. (Fall) [Graded Letter]
Credit(s) | $63 Fee An introduction to data science methods in business, finance, and economics. Includes an introduction to an appropriate programming language for data manipulation and modeling. Provides an overview of descriptive, predictive, and prescriptive methods in data analytics. (As Needed) [Graded Letter]
( MATH 1040 or MATH 1190 or MATH 3700 ) and ( MATH 1100 or MATH 1210 ) -
ANLY 6010Business Analytics I3
Credit(s) | $63 Fee An introduction to data science methods in business. Includes an introduction to programming for data manipulation and modeling. Provides an overview of descriptive, predictive, and prescriptive methods in data analytics from a practical business perspective, with a focus on direct application to current data-driven decision-making. (Fall - 1st Session, Spring - 2nd Session) [Graded Letter]
Credit(s) | $63 Fee A continuation of ANLY 6010 . Covers the primary analytic techniques involved in data mining for business problem-solving, including advanced regression, decision trees, kNN, and others. Introduces unsupervised learning methods. Builds on the programming skills established in Business Analytics I. (Fall - 2nd Session, Summer - 1st Session) [Graded Letter]
Credit(s) | $63 Fee An introduction to the methods and tools for database management and data visualization with a particular focus on industry analytics. Database topics include the logical structure of databases as well as the methods and technology for efficient data storage, retrieval, and presentation. Visualization topics include an overview of the Tableau software for data visualization and discussion of data visualization principles. Emphasizes skills in retrieving and presenting data for business presentation. (Spring - 1st Session, Summer - 2nd Session) [Graded Letter]
Credit(s) | $63 Fee Introduction to programming basics, binary computation, problem-solving methods and algorithm development. Includes procedural and data abstractions, program design, debugging, testing, and documentation. Covers data types, control structures, functions, parameter passing, library functions, arrays, inheritance and object-oriented design. Laboratory exercises in Python. (Fall - 2nd Session, Summer - 1st Session) [Graded Letter]
Credit(s) | $63 Fee An introduction to data science methods in business, finance, and economics. Includes an introduction to an appropriate programming language for data manipulation and modeling. Provides an overview of descriptive, predictive, and prescriptive methods in data analytics. (As Needed) [Graded Letter]
Credit(s) | $63 Fee A continuation of ANLY 6100 . Covers the primary analytic techniques involved in data mining, including logistic regression, decision trees, kNN, naive Bayes, and others. Introduces unsupervised learning methods. Builds on the programming skills established in ANLY 6100. (As Needed) [Graded Letter]
Credit(s) | $63 Fee This course introduces methods and tools for data processing, database management, and data visualization used in modern business analytics. Students will learn relational database concepts and SQL for retrieving and preparing data, apply Tableau for building effective visualizations, and explore principles of visual design and data storytelling. The course emphasizes the development of metrics and KPIs, integrating AI tools to enhance KPI ideation and visualization design. By the end of the course, students will be able to design, query, and visualize data in a way that supports strategic decision-making and communicates analytical insights clearly. (Fall) [Graded Letter]
Credit(s) | $63 Fee This course introduces the management and organization of data with an emphasis on modern database tools used in business analytics. Students will gain hands-on experience designing and querying relational and columnar databases using Structured Query Language (SQL). Topics include data modeling, database design, cloud databases, analytic functions, and data movement techniques. Students will also explore how data strategy, governance, and architecture enable organizations to extract value from their data assets. The course incorporates appropriate use of artificial intelligence (AI) tools to assist in evaluating and generating SQL code, optimizing database design, and supporting data strategy and governance planning. By the end of the course, students will be able to design, query, and manage databases; prepare and visualize data for analysis; and develop data strategies that align with business goals. (Fall) [Graded Letter]
Credit(s) | $63 Fee This course provides an overview of the most important analytics methods used in marketing decision making. Students are introduced to common marketing models such as probit, multinomial, and structural equation modeling. Well-established marketing research methods are covered, such as survey and experimental design, along with more recent marketing research tools such as sentiment mining and social-network analysis. (As Needed) [Graded Letter]
ANLY 6350Advanced Data Management and Organization3
Credit(s) | $63 Fee This course explores the research and application of advanced database and cloud-based data systems with a focus on enabling artificial intelligence and advanced analytics at scale. Students will learn to design and manage AI-ready architectures that support scalable storage, intelligent pipelines, semantic data layers, and real-time inference. Emphasis is placed on leveraging cloud-native tools and AI-augmented development practices to automate data processing, streamline model integration, and ensure secure and ethical data use. ANLY 6350 is a continuation of ANLY 6250 , building on foundational concepts to advance students’ technical and strategic understanding of data systems. Upon completion, students will be able to evaluate modern data technologies, describe and implement AI-enabled architecture concepts, and apply advanced design principles to build or enhance enterprise data systems. The course also prepares students to deploy intelligent data pipelines, assess AI-optimized technologies, and design governed, explainable strategies for data consumption across analytics and machine learning environments. (Fall - 1st Session) [Graded Letter]
Credit(s) | $63 Fee This course introduces the theory of an “Internet of Things (IoT)” and how to deal with the massive amounts of data generated by the connections of the IoT. The course includes an introduction to the open-source technologies commonly used to deal with unstructured big data problems, such as Hadoop, Spark, Pig, Hive, and Amazon Web Services. Along with familiarizing students with big data techniques and tools, the course presents real-world business applications and gives students hands-on experience with obtaining valuable information from big datasets. (Spring) [Graded Letter]
Credit(s) | $63 Fee This course provides a hands-on introduction to advanced deep learning techniques with a focus on modern applications in image and text analysis. Students will gain practical experience using Python and PyTorch to build, train, and evaluate deep learning models for regression, classification, and natural language processing (NLP) tasks. Key topics include activation and loss functions, dataset management, learning rate schedulers, and transfer learning. The course also introduces Large Language Models (LLMs) and the Hugging Face Transformers library for sentiment analysis, named entity recognition, and text generation. By the end of the course, students will be able to design and implement end-to-end deep learning solutions for real-world data analytics problems. Designed to prepare students for data-centric careers, this course offers a rigorous, hands-on experience, equipping them with the tools needed for roles in management information systems, data analysis, and related fields. (Fall - 2nd Session) [Graded Letter]
Credit(s) | $63 Fee This course is an introduction to the use of generative AI Systems in business settings. The skills and knowledge you pick up along the way will be valuable in our increasingly AI-centric economy. (Spring - 1st Session, Summer - 2nd Session) [Graded Letter]
Credit(s) | $63 Fee With faculty input and supervision, students carry out a complex analytics project that applies methodologies from their coursework to enhance the performance of a business. (As Needed) [Graduate Thesis/Capstone Pass/Fail]
ANLY 6110 and ANLY 6400 and ECON 6110 and instructor permission -
ANLY 6901Capstone Project Continuation1
Credit(s) | $21 Fee This course serves the MSBA student who needs additional support for a capstone project after completing ANLY 6900 . (As Needed) [Graduate Thesis/Capstone Pass/Fail]
