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2024 Spring: January 10 - June 25

Course Class No. Section Start & End Date Day Time Status Location
DATA 610 Decision Management Systems (6)
An examination of the process of decision making in large organizations and the technologies that can be used to enhance data-driven decision making. Focus is on the underlying framework of good decision making, featuring operational decisions as reusable assets that can be automated through the creation of business rules. How data can add analytic insight to improve decisions is explored. Discussion covers best practices for long-term success of an analytics project in terms of project management and communications with an emphasis on the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology.
Start date has passed. Please register for the next start date.
24949 9040 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Moretto, Laila Syllabus Course Materials
DATA 610 Decision Management Systems (6)
An examination of the process of decision making in large organizations and the technologies that can be used to enhance data-driven decision making. Focus is on the underlying framework of good decision making, featuring operational decisions as reusable assets that can be automated through the creation of business rules. How data can add analytic insight to improve decisions is explored. Discussion covers best practices for long-term success of an analytics project in terms of project management and communications with an emphasis on the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology.
Start date has passed. Please register for the next start date.
24982 9041 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Heboyan, Vahe Syllabus Course Materials
DATA 610 Decision Management Systems (6)
An examination of the process of decision making in large organizations and the technologies that can be used to enhance data-driven decision making. Focus is on the underlying framework of good decision making, featuring operational decisions as reusable assets that can be automated through the creation of business rules. How data can add analytic insight to improve decisions is explored. Discussion covers best practices for long-term success of an analytics project in terms of project management and communications with an emphasis on the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology.
Start date has passed. Please register for the next start date.
25110 9080 14 Feb 2024-07 May 2024 Open Online
Faculty: Larson, Deanne M Syllabus Course Materials
DATA 620 Data Management and Visualization (6)
Prerequisite: DATA 610. A presentation of the fundamental concepts and techniques in managing and presenting data for effective data-driven decision making. Topics in data management and design include data design approaches for performance and availability, such as data storage and indexing strategies; data warehousing, such as requirement analysis, dimensional modeling, and ETL (extract, transform, load) processing; and metadata management. Topics in data visualization include data types; data dimensionalities, such as time-series and geospatial data; forms of data visualization, including heat maps and infographs; and best practices for usable, consumable, and actionable data/results presentation.
Start date has passed. Please register for the next start date.
24950 9040 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Beam, Caroline M Syllabus Course Materials
DATA 620 Data Management and Visualization (6)
Prerequisite: DATA 610. A presentation of the fundamental concepts and techniques in managing and presenting data for effective data-driven decision making. Topics in data management and design include data design approaches for performance and availability, such as data storage and indexing strategies; data warehousing, such as requirement analysis, dimensional modeling, and ETL (extract, transform, load) processing; and metadata management. Topics in data visualization include data types; data dimensionalities, such as time-series and geospatial data; forms of data visualization, including heat maps and infographs; and best practices for usable, consumable, and actionable data/results presentation.
Start date has passed. Please register for the next start date.
24978 9041 10 Jan 2024-02 Apr 2024 Open Online
Faculty: AL-Ghandour, Majed N Syllabus Course Materials
DATA 620 Data Management and Visualization (6)
Prerequisite: DATA 610. A presentation of the fundamental concepts and techniques in managing and presenting data for effective data-driven decision making. Topics in data management and design include data design approaches for performance and availability, such as data storage and indexing strategies; data warehousing, such as requirement analysis, dimensional modeling, and ETL (extract, transform, load) processing; and metadata management. Topics in data visualization include data types; data dimensionalities, such as time-series and geospatial data; forms of data visualization, including heat maps and infographs; and best practices for usable, consumable, and actionable data/results presentation.
Start date has passed. Please register for the next start date.
25111 9080 14 Feb 2024-07 May 2024 Open Online
Faculty: Ajayi, Rosiji O Syllabus Course Materials
DATA 620 Data Management and Visualization (6)
Prerequisite: DATA 610. A presentation of the fundamental concepts and techniques in managing and presenting data for effective data-driven decision making. Topics in data management and design include data design approaches for performance and availability, such as data storage and indexing strategies; data warehousing, such as requirement analysis, dimensional modeling, and ETL (extract, transform, load) processing; and metadata management. Topics in data visualization include data types; data dimensionalities, such as time-series and geospatial data; forms of data visualization, including heat maps and infographs; and best practices for usable, consumable, and actionable data/results presentation.
Start date has passed. Please register for the next start date.
26875 9042 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Cross, George M Syllabus Course Materials
DATA 630 Machine Learning (6)
Prerequisite: DATA 620. A practical survey of several modern machine learning techniques that can be applied to make informed business decisions. Discussion covers supervised and unsupervised learning techniques, including naïve Bayes, regression, decision trees, neural networks, nearest neighbor, and cluster analysis. How each of these methods learns from past data to find underlying patterns useful for prediction, classification, and exploratory data analysis is examined. Discussion covers significant tasks in real-world applications, including handling of missing data, evaluating classifiers, and measuring precision. Major software tools are used to apply machine learning methods in a wide range of domains such as healthcare, finance, marketing, and government.
Start date has passed. Please register for the next start date.
24951 9040 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Gates, Ami M Syllabus Course Materials
DATA 630 Machine Learning (6)
Prerequisite: DATA 620. A practical survey of several modern machine learning techniques that can be applied to make informed business decisions. Discussion covers supervised and unsupervised learning techniques, including naïve Bayes, regression, decision trees, neural networks, nearest neighbor, and cluster analysis. How each of these methods learns from past data to find underlying patterns useful for prediction, classification, and exploratory data analysis is examined. Discussion covers significant tasks in real-world applications, including handling of missing data, evaluating classifiers, and measuring precision. Major software tools are used to apply machine learning methods in a wide range of domains such as healthcare, finance, marketing, and government.
Start date has passed. Please register for the next start date.
24983 9041 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Bati, Firdu Syllabus Course Materials
DATA 640 Predictive Modeling (6)
Prerequisite: DATA 630. An introduction to advanced concepts in predictive modeling and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models. Advanced statistical and machine learning algorithms such as support vector machines (SVM), regression, deep learning, and ensemble models are used to develop, assess, compare, and explain complex predictive models. Topics include high-performance modeling, genetic algorithms, and best practices for selecting methods and tools to build predictive models. Major software tools are used to apply predictive modeling in a wide range of domains for improved decision-making in real business situations.
Start date has passed. Please register for the next start date.
24966 9040 10 Jan 2024-02 Apr 2024 Closed Online
Faculty: Knode, Charles S Syllabus Course Materials
DATA 640 Predictive Modeling (6)
Prerequisite: DATA 630. An introduction to advanced concepts in predictive modeling and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models. Advanced statistical and machine learning algorithms such as support vector machines (SVM), regression, deep learning, and ensemble models are used to develop, assess, compare, and explain complex predictive models. Topics include high-performance modeling, genetic algorithms, and best practices for selecting methods and tools to build predictive models. Major software tools are used to apply predictive modeling in a wide range of domains for improved decision-making in real business situations.
Start date has passed. Please register for the next start date.
25018 9041 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Herranz, Edward Syllabus Course Materials
DATA 650 Big Data Analytics (6)
Prerequisite: DATA 640. An introduction to concepts, approaches and techniques in managing and analyzing large data sets for improved decision-making in real business situations. Topics include text analytics, sentiment analysis, stream analytics, AI and cognitive computing. Discussion also covers how to identify the kinds of analyses to use with big data and how to interpret the results. Advanced tools and basic approaches are used to query and explore data using Hadoop Platform and in-memory analytical tools like Spark ML.
Start date has passed. Please register for the next start date.
24968 9040 10 Jan 2024-02 Apr 2024 Closed Online
Faculty: Ozcan, Ozan Syllabus Course Materials
DATA 650 Big Data Analytics (6)
Prerequisite: DATA 640. An introduction to concepts, approaches and techniques in managing and analyzing large data sets for improved decision-making in real business situations. Topics include text analytics, sentiment analysis, stream analytics, AI and cognitive computing. Discussion also covers how to identify the kinds of analyses to use with big data and how to interpret the results. Advanced tools and basic approaches are used to query and explore data using Hadoop Platform and in-memory analytical tools like Spark ML.
Start date has passed. Please register for the next start date.
26864 9041 10 Jan 2024-02 Apr 2024 Open Online
Faculty: Gortcheva, Elena A Syllabus Course Materials
DATA 670 Data Analytics Capstone (6)
Prerequisite: DATA 650. Completion of a major analytics project designed to integrate knowledge and skills gained from previous coursework and provide a complete analytics experience, including problem scoping (framing), data set preparation, comprehensive data analysis and visualization, and predictive model development. Several peer-reviewed presentations are included to enhance the ability to "tell the story" and explain project approach and results. Projects are selected from student organizations, special government agency requests, or other faculty-approved sources. The project culminates in a complete analytics report and presentation.
Start date has passed. Please register for the next start date.
24969 9040 10 Jan 2024-02 Apr 2024 Open Online
Faculty: McKeeby, Jon W Syllabus Course Materials
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