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2026 Spring: January 7 - May 5

Course Class No. Section Start & End Date Day Time Status Location
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
2955 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Kinzel, Beate Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
3062 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Kamai, Moses M Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
3069 6382 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Moretto, Laila Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
3086 6383 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Kulkarni, Shankar A Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
3147 6384 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Gathoni, Priscilla Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
3350 6385 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Saknee, Ayad Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
3447 6386 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Moustafa, Rida E Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
4557 6980 11 Feb 2026-07 Apr 2026 Open Online
Faculty: Bunnell, Patricia D Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
4578 6981 11 Feb 2026-07 Apr 2026 Open Online
Faculty: Crombie, George W Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
4658 6982 11 Feb 2026-07 Apr 2026 Open Online
Faculty: Green, Toni Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
4707 6983 11 Feb 2026-07 Apr 2026 Open Online
Faculty: Eltomy, Reham Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
4740 6984 11 Feb 2026-07 Apr 2026 Open Online
Faculty: Alvarado, Eric Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
6115 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Kinzel, Beate Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
6252 7381 11 Mar 2026-05 May 2026 Closed Online
Faculty: Moretto, Laila Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
6279 7382 11 Mar 2026-05 May 2026 Closed Online
Faculty: Kulkarni, Shankar A Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
6327 7383 11 Mar 2026-05 May 2026 Closed Online
Faculty: Gathoni, Priscilla Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
6962 7384 11 Mar 2026-05 May 2026 Closed Online
Faculty: Ekpagu, Kelechi Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
7046 7385 11 Mar 2026-05 May 2026 Open Online
Faculty: Chen, Xiaodong Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
7537 4025 07 Jan 2026-03 Mar 2026 Th 6:30P-9:30P Open College Park (Hybrid)
Faculty: Pomietto, Robert J Bldg/Room: Susquehanna Hall 1105 Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
9521 6387 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Goldberg, Katherine Leaming Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
9584 6388 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Dogan, Tuncay Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
9674 6389 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Thomas, Sunela S Syllabus Course Materials
DATA 200 Data Literacy Foundations (3)
An introduction to data and data literacy for students of all majors to enhance their ability to understand and work in today's data-driven world. The aim is to collect, manage, evaluate and apply data in a critical manner and examine the role, significance, and implications of data, including ethical issues within a society, in organizations, or for individuals. Developing skills in data manipulation, analysis, and visualization, students will generate insights from data, build knowledge, and make decisions. Topics include the effective use of cloud-based data storage, collaboration and communication techniques.
Start date has passed. Please register for the next start date.
9765 6390 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Jha, Manoj K Syllabus Course Materials
DATA 230 Mathematics for Data Science (3)
Prerequisites: STAT 200 and MATH 115 (or MATH 107 and MATH 108) or higher. A practical introduction to the mathematical principles applied within the context of data science. The aim is to understand the mathematical basis of data science and increase awareness of machine learning algorithm assumptions and limitations. Machine learning topics include linear regression, dimensionality reduction, and classification. Projects involve application of linear algebra, probability, vector calculus, and optimization to build data science solutions.
Start date has passed. Please register for the next start date.
3248 6380 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Holmes, Matthew R Syllabus Course Materials
DATA 230 Mathematics for Data Science (3)
Prerequisites: STAT 200 and MATH 115 (or MATH 107 and MATH 108) or higher. A practical introduction to the mathematical principles applied within the context of data science. The aim is to understand the mathematical basis of data science and increase awareness of machine learning algorithm assumptions and limitations. Machine learning topics include linear regression, dimensionality reduction, and classification. Projects involve application of linear algebra, probability, vector calculus, and optimization to build data science solutions.
Start date has passed. Please register for the next start date.
3315 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Martin, Ulyana P Syllabus Course Materials
DATA 230 Mathematics for Data Science (3)
Prerequisites: STAT 200 and MATH 115 (or MATH 107 and MATH 108) or higher. A practical introduction to the mathematical principles applied within the context of data science. The aim is to understand the mathematical basis of data science and increase awareness of machine learning algorithm assumptions and limitations. Machine learning topics include linear regression, dimensionality reduction, and classification. Projects involve application of linear algebra, probability, vector calculus, and optimization to build data science solutions.
6401 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Moustafa, Rida E Syllabus Course Materials
DATA 230 Mathematics for Data Science (3)
Prerequisites: STAT 200 and MATH 115 (or MATH 107 and MATH 108) or higher. A practical introduction to the mathematical principles applied within the context of data science. The aim is to understand the mathematical basis of data science and increase awareness of machine learning algorithm assumptions and limitations. Machine learning topics include linear regression, dimensionality reduction, and classification. Projects involve application of linear algebra, probability, vector calculus, and optimization to build data science solutions.
6429 7381 11 Mar 2026-05 May 2026 Open Online
Faculty: Ezzati, Parinaz Syllabus Course Materials
DATA 230 Mathematics for Data Science (3)
Prerequisites: STAT 200 and MATH 115 (or MATH 107 and MATH 108) or higher. A practical introduction to the mathematical principles applied within the context of data science. The aim is to understand the mathematical basis of data science and increase awareness of machine learning algorithm assumptions and limitations. Machine learning topics include linear regression, dimensionality reduction, and classification. Projects involve application of linear algebra, probability, vector calculus, and optimization to build data science solutions.
7536 7615 07 Jan 2026-03 Mar 2026 T 6:30P-9:30P Open Dorsey Station (Hybrid)
Faculty: Chan, Philip W Syllabus Course Materials
Note: Dorsey Station: Classroom assignments are subject to change. Please view the electronic board in the hallway for your classroom assignment.
DATA 230 Mathematics for Data Science (3)
Prerequisites: STAT 200 and MATH 115 (or MATH 107 and MATH 108) or higher. A practical introduction to the mathematical principles applied within the context of data science. The aim is to understand the mathematical basis of data science and increase awareness of machine learning algorithm assumptions and limitations. Machine learning topics include linear regression, dimensionality reduction, and classification. Projects involve application of linear algebra, probability, vector calculus, and optimization to build data science solutions.
Start date has passed. Please register for the next start date.
7737 6382 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Wong, Sze Wing Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
Start date has passed. Please register for the next start date.
3044 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Zimmer, Janet M Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
Start date has passed. Please register for the next start date.
3064 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Shpaner, Leonid Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
Start date has passed. Please register for the next start date.
3338 6382 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Eng, Richard F Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
Start date has passed. Please register for the next start date.
3932 6383 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Wardeh, Mohammed A Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
6116 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Momtaz, Maliha Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
6248 7381 11 Mar 2026-05 May 2026 Closed Online
Faculty: Dogan, Tuncay Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
6271 7382 11 Mar 2026-05 May 2026 Closed Online
Faculty: Eng, Richard F Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
7534 5065 11 Mar 2026-05 May 2026 Th 6:30P-9:30P Open LaPlata (Hybrid)
Faculty: Hunter, Demond S Bldg/Room: BU 117 Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
Start date has passed. Please register for the next start date.
7739 6384 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Dennis, Yancy Syllabus Course Materials
DATA 300 Foundations of Data Science (3)
Prerequisite: STAT 200. An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.
7740 7383 11 Mar 2026-05 May 2026 Open Online
Faculty: Eltomy, Reham Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
Start date has passed. Please register for the next start date.
3036 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Dean, Michael Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
Start date has passed. Please register for the next start date.
3037 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: King, Brandon I Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
Start date has passed. Please register for the next start date.
3838 6382 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Kiwa, Lesosa Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
Start date has passed. Please register for the next start date.
4574 6980 11 Feb 2026-07 Apr 2026 Open Online
Faculty: Goldberg, Katherine Leaming Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
6225 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Dean, Michael Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
6257 7381 11 Mar 2026-05 May 2026 Closed Online
Faculty: Kiwa, Lesosa Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
6452 7382 11 Mar 2026-05 May 2026 Open Online
Faculty: Thomas, Sunela S Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
7532 7665 11 Mar 2026-05 May 2026 Th 6:30P-9:30P Open Dorsey Station (Hybrid)
Faculty: Jacob-Sampson, Diandre Syllabus Course Materials
Note: Dorsey Station: Classroom assignments are subject to change. Please view the electronic board in the hallway for your classroom assignment.
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
Start date has passed. Please register for the next start date.
7741 6383 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Clay, Christopher Syllabus Course Materials
DATA 320 Introduction to Data Analytics (3)
Formerly DATA 220. Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure that data is relevant and properly manipulated to solve problems and address a variety of real-world projects and business scenarios. Focus is on the application of foundational statistical concepts to describing datasets with summary statistics, simple data visualizations, statistical inference, and predictive analytics. The objective is to use data to draw conclusions about the underlying patterns that drive everyday problems through probability, hypothesis testing, and linear model building.
7742 7383 11 Mar 2026-05 May 2026 Open Online
Faculty: Holmes, Matthew R Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
Start date has passed. Please register for the next start date.
3693 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Mintz, Rhonda S Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
Start date has passed. Please register for the next start date.
3694 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Chen, Xiaodong Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
Start date has passed. Please register for the next start date.
3695 6382 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Pearson, Christy Lynn Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
6737 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Mintz, Renae S Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
6738 7381 11 Mar 2026-05 May 2026 Open Online
Faculty: Mintz, Rhonda S Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
6739 7382 11 Mar 2026-05 May 2026 Closed Online
Faculty: Tran, Anh L Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
6740 7383 11 Mar 2026-05 May 2026 Closed Online
Faculty: Wardeh, Mohammed A Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
Start date has passed. Please register for the next start date.
9275 6383 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Phiri, Mwalimu Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
Start date has passed. Please register for the next start date.
9522 6384 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Mintz, Renae S Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
Start date has passed. Please register for the next start date.
9670 6385 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Rai, Paritosh Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
9799 7384 11 Mar 2026-05 May 2026 Closed Online
Faculty: Al-Dhaheri, Sami Syllabus Course Materials
DATA 330 Business Intelligence and Data Management (3)
A hands-on, project-based introduction to databases, business intelligence, and data management. The aim is to design secure industry-standard databases and utilize business intelligence and data management techniques and technologies to support decision making. Topics include data and relational databases, SQL queries, business intelligence tools and overall alignment with business strategy. Students may receive credit for only one of the following courses: DATA 330 or IFSM 330.
9944 7385 11 Mar 2026-05 May 2026 Open Online
Faculty: Manda, Prashanti Syllabus Course Materials
DATA 335 Data Visualization (3)
Prerequisite: DATA 320. An overview of the fundamentals of data visualization principles in the context of business and data science. Practical focus on data visualization of different data types including time series, multidimensional data, creating dynamic tables, heatmaps, infographs, and dashboards. Hands on projects will require exploring data visually at multiple levels to find insights to create a compelling story and incorporating visual design best practices to better communicate insights to the intended audience, such as business stakeholders. Projects are selected from a wide range of content areas such as retail, marketing, healthcare, government, basic sciences, and technology.
Start date has passed. Please register for the next start date.
3043 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Goldberg, Katherine Leaming Syllabus Course Materials
DATA 335 Data Visualization (3)
Prerequisite: DATA 320. An overview of the fundamentals of data visualization principles in the context of business and data science. Practical focus on data visualization of different data types including time series, multidimensional data, creating dynamic tables, heatmaps, infographs, and dashboards. Hands on projects will require exploring data visually at multiple levels to find insights to create a compelling story and incorporating visual design best practices to better communicate insights to the intended audience, such as business stakeholders. Projects are selected from a wide range of content areas such as retail, marketing, healthcare, government, basic sciences, and technology.
Start date has passed. Please register for the next start date.
3256 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Vuppalapaty, Parthasaradhy Syllabus Course Materials
DATA 335 Data Visualization (3)
Prerequisite: DATA 320. An overview of the fundamentals of data visualization principles in the context of business and data science. Practical focus on data visualization of different data types including time series, multidimensional data, creating dynamic tables, heatmaps, infographs, and dashboards. Hands on projects will require exploring data visually at multiple levels to find insights to create a compelling story and incorporating visual design best practices to better communicate insights to the intended audience, such as business stakeholders. Projects are selected from a wide range of content areas such as retail, marketing, healthcare, government, basic sciences, and technology.
6117 7380 11 Mar 2026-05 May 2026 Open Online
Faculty: Clay, Christopher Syllabus Course Materials
DATA 335 Data Visualization (3)
Prerequisite: DATA 320. An overview of the fundamentals of data visualization principles in the context of business and data science. Practical focus on data visualization of different data types including time series, multidimensional data, creating dynamic tables, heatmaps, infographs, and dashboards. Hands on projects will require exploring data visually at multiple levels to find insights to create a compelling story and incorporating visual design best practices to better communicate insights to the intended audience, such as business stakeholders. Projects are selected from a wide range of content areas such as retail, marketing, healthcare, government, basic sciences, and technology.
6256 7381 11 Mar 2026-05 May 2026 Closed Online
Faculty: Pearson, Christy Lynn Syllabus Course Materials
DATA 335 Data Visualization (3)
Prerequisite: DATA 320. An overview of the fundamentals of data visualization principles in the context of business and data science. Practical focus on data visualization of different data types including time series, multidimensional data, creating dynamic tables, heatmaps, infographs, and dashboards. Hands on projects will require exploring data visually at multiple levels to find insights to create a compelling story and incorporating visual design best practices to better communicate insights to the intended audience, such as business stakeholders. Projects are selected from a wide range of content areas such as retail, marketing, healthcare, government, basic sciences, and technology.
Start date has passed. Please register for the next start date.
7743 6382 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Tran, Anh L Syllabus Course Materials
DATA 335 Data Visualization (3)
Prerequisite: DATA 320. An overview of the fundamentals of data visualization principles in the context of business and data science. Practical focus on data visualization of different data types including time series, multidimensional data, creating dynamic tables, heatmaps, infographs, and dashboards. Hands on projects will require exploring data visually at multiple levels to find insights to create a compelling story and incorporating visual design best practices to better communicate insights to the intended audience, such as business stakeholders. Projects are selected from a wide range of content areas such as retail, marketing, healthcare, government, basic sciences, and technology.
7744 7382 11 Mar 2026-05 May 2026 Open Online
Faculty: Alvarado, Eric Syllabus Course Materials
DATA 430 Foundations of Machine Learning (3)
Prerequisite: DATA 300. A hands-on introduction to machine learning principles and methods that can be applied to solve practical problems. Topics include supervised and unsupervised learning, especially linear regression, logistic regression, decision tree, naïve Bayes, and clustering analysis. Focus is on using data from a wide range of domains, such as healthcare, finance, marketing, and government, to build predictive models for informed decision-making. Discussion also covers handling missing data, performing cross-validation to avoid overtraining, evaluating classifiers, and measuring precision.
Start date has passed. Please register for the next start date.
3042 6380 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Momtaz, Maliha Syllabus Course Materials
DATA 430 Foundations of Machine Learning (3)
Prerequisite: DATA 300. A hands-on introduction to machine learning principles and methods that can be applied to solve practical problems. Topics include supervised and unsupervised learning, especially linear regression, logistic regression, decision tree, naïve Bayes, and clustering analysis. Focus is on using data from a wide range of domains, such as healthcare, finance, marketing, and government, to build predictive models for informed decision-making. Discussion also covers handling missing data, performing cross-validation to avoid overtraining, evaluating classifiers, and measuring precision.
Start date has passed. Please register for the next start date.
3397 6381 07 Jan 2026-03 Mar 2026 Closed Online
Faculty: Nath, Tanmay Syllabus Course Materials
DATA 430 Foundations of Machine Learning (3)
Prerequisite: DATA 300. A hands-on introduction to machine learning principles and methods that can be applied to solve practical problems. Topics include supervised and unsupervised learning, especially linear regression, logistic regression, decision tree, naïve Bayes, and clustering analysis. Focus is on using data from a wide range of domains, such as healthcare, finance, marketing, and government, to build predictive models for informed decision-making. Discussion also covers handling missing data, performing cross-validation to avoid overtraining, evaluating classifiers, and measuring precision.
6118 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Guevara, Yamil E Syllabus Course Materials
DATA 430 Foundations of Machine Learning (3)
Prerequisite: DATA 300. A hands-on introduction to machine learning principles and methods that can be applied to solve practical problems. Topics include supervised and unsupervised learning, especially linear regression, logistic regression, decision tree, naïve Bayes, and clustering analysis. Focus is on using data from a wide range of domains, such as healthcare, finance, marketing, and government, to build predictive models for informed decision-making. Discussion also covers handling missing data, performing cross-validation to avoid overtraining, evaluating classifiers, and measuring precision.
6414 7381 11 Mar 2026-05 May 2026 Open Online
Faculty: Martin, Ulyana P Syllabus Course Materials
DATA 430 Foundations of Machine Learning (3)
Prerequisite: DATA 300. A hands-on introduction to machine learning principles and methods that can be applied to solve practical problems. Topics include supervised and unsupervised learning, especially linear regression, logistic regression, decision tree, naïve Bayes, and clustering analysis. Focus is on using data from a wide range of domains, such as healthcare, finance, marketing, and government, to build predictive models for informed decision-making. Discussion also covers handling missing data, performing cross-validation to avoid overtraining, evaluating classifiers, and measuring precision.
Start date has passed. Please register for the next start date.
7745 6382 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Elizes, Romerl Syllabus Course Materials
DATA 445 Advanced Data Science (3)
Prerequisites: DATA 335 and DATA 430. A project-based introduction to the concepts, approaches, techniques, and technologies for managing and analyzing large data sets in support of improved decision making. Activities include using technologies such as Spark, Hive, Pig, Kafka, Hadoop, HBase, Flume, Cassandra, cloud analytics, container architectures, and streaming real-time platforms. Discussion covers how to identify the kinds of analyses to use with big data and how to interpret the results.
Start date has passed. Please register for the next start date.
3030 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Dave, Linesh Ramesh Syllabus Course Materials
DATA 445 Advanced Data Science (3)
Prerequisites: DATA 335 and DATA 430. A project-based introduction to the concepts, approaches, techniques, and technologies for managing and analyzing large data sets in support of improved decision making. Activities include using technologies such as Spark, Hive, Pig, Kafka, Hadoop, HBase, Flume, Cassandra, cloud analytics, container architectures, and streaming real-time platforms. Discussion covers how to identify the kinds of analyses to use with big data and how to interpret the results.
Start date has passed. Please register for the next start date.
3802 6381 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Burkhardt, Michael H Syllabus Course Materials
DATA 445 Advanced Data Science (3)
Prerequisites: DATA 335 and DATA 430. A project-based introduction to the concepts, approaches, techniques, and technologies for managing and analyzing large data sets in support of improved decision making. Activities include using technologies such as Spark, Hive, Pig, Kafka, Hadoop, HBase, Flume, Cassandra, cloud analytics, container architectures, and streaming real-time platforms. Discussion covers how to identify the kinds of analyses to use with big data and how to interpret the results.
6221 7380 11 Mar 2026-05 May 2026 Open Online
Faculty: Dave, Linesh Ramesh Syllabus Course Materials
DATA 445 Advanced Data Science (3)
Prerequisites: DATA 335 and DATA 430. A project-based introduction to the concepts, approaches, techniques, and technologies for managing and analyzing large data sets in support of improved decision making. Activities include using technologies such as Spark, Hive, Pig, Kafka, Hadoop, HBase, Flume, Cassandra, cloud analytics, container architectures, and streaming real-time platforms. Discussion covers how to identify the kinds of analyses to use with big data and how to interpret the results.
6965 7381 11 Mar 2026-05 May 2026 Open Online
Faculty: Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: ARIN 440 (or DATA 440), DATA 445, and ARIN 450 (or DATA 450). A project-based, practical application of the knowledge, technical skills, and critical-thinking skills acquired during previous study designed to showcase one's data science expertise. Individually selected projects include all phases of the machine learning life cycle and a peer-reviewed final report and presentation. Topics are selected from student-affiliated organizations or employers, special government/private agency requests, or other faculty-approved sources in a wide range of domains, such as healthcare, financial services, marketing, sciences, and government.
Start date has passed. Please register for the next start date.
3250 6380 07 Jan 2026-03 Mar 2026 Open Online
Faculty: Chesney, Steve L Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: ARIN 440 (or DATA 440), DATA 445, and ARIN 450 (or DATA 450). A project-based, practical application of the knowledge, technical skills, and critical-thinking skills acquired during previous study designed to showcase one's data science expertise. Individually selected projects include all phases of the machine learning life cycle and a peer-reviewed final report and presentation. Topics are selected from student-affiliated organizations or employers, special government/private agency requests, or other faculty-approved sources in a wide range of domains, such as healthcare, financial services, marketing, sciences, and government.
6403 7380 11 Mar 2026-05 May 2026 Closed Online
Faculty: Chesney, Steve L Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: ARIN 440 (or DATA 440), DATA 445, and ARIN 450 (or DATA 450). A project-based, practical application of the knowledge, technical skills, and critical-thinking skills acquired during previous study designed to showcase one's data science expertise. Individually selected projects include all phases of the machine learning life cycle and a peer-reviewed final report and presentation. Topics are selected from student-affiliated organizations or employers, special government/private agency requests, or other faculty-approved sources in a wide range of domains, such as healthcare, financial services, marketing, sciences, and government.
6412 7381 11 Mar 2026-05 May 2026 Open Online
Faculty: Rai, Paritosh Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: ARIN 440 (or DATA 440), DATA 445, and ARIN 450 (or DATA 450). A project-based, practical application of the knowledge, technical skills, and critical-thinking skills acquired during previous study designed to showcase one's data science expertise. Individually selected projects include all phases of the machine learning life cycle and a peer-reviewed final report and presentation. Topics are selected from student-affiliated organizations or employers, special government/private agency requests, or other faculty-approved sources in a wide range of domains, such as healthcare, financial services, marketing, sciences, and government.
7692 7382 11 Mar 2026-05 May 2026 Open Online
Faculty: George, Ajish D Syllabus Course Materials
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