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2025 Spring: January 8 - May 6

Course Class No. Section Start & End Date Day Time Status Location
CYOP 300 Building Secure Python Applications (3)
(Formerly SDEV 300.) Prerequisite: CMSC 215 or CYOP 200. A hands-on study of best practices and strategies for building secure Python desktop and web applications. The objective is to design and build Python applications that are resistant to common security threats. Topics include syntax, data structures, style guides, data munging, web application frameworks, and the use of secure coding tools and processes to guard against application vulnerabilities. Students may receive credit for only one of the following courses: CYOP 300 or SDEV 300.
23841 7382 12 Mar 2025-06 May 2025 Open Online
Faculty: Boswell, Justin L. Syllabus Course Materials
CYOP 310 Reverse Engineering and Malware Analysis (3)
A lab-intensive study of reverse engineering and malware analysis techniques. The objective is to recognize, dissect, and remediate infections caused by malicious code and malware using modern tools and methodologies. Topics include malware analysis, reverse engineering, common malware patterns, assembly language, debuggers and obfuscation, and packing techniques.
Start date has passed. Please register for the next start date.
26175 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Phillips, Nicholas A Syllabus Course Materials
CYOP 310 Reverse Engineering and Malware Analysis (3)
A lab-intensive study of reverse engineering and malware analysis techniques. The objective is to recognize, dissect, and remediate infections caused by malicious code and malware using modern tools and methodologies. Topics include malware analysis, reverse engineering, common malware patterns, assembly language, debuggers and obfuscation, and packing techniques.
26176 7380 12 Mar 2025-06 May 2025 Closed Online
Faculty: Aus, Alex D Syllabus Course Materials
CYOP 310 Reverse Engineering and Malware Analysis (3)
A lab-intensive study of reverse engineering and malware analysis techniques. The objective is to recognize, dissect, and remediate infections caused by malicious code and malware using modern tools and methodologies. Topics include malware analysis, reverse engineering, common malware patterns, assembly language, debuggers and obfuscation, and packing techniques.
Start date has passed. Please register for the next start date.
27136 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Aus, Alex D Syllabus Course Materials
CYOP 310 Reverse Engineering and Malware Analysis (3)
A lab-intensive study of reverse engineering and malware analysis techniques. The objective is to recognize, dissect, and remediate infections caused by malicious code and malware using modern tools and methodologies. Topics include malware analysis, reverse engineering, common malware patterns, assembly language, debuggers and obfuscation, and packing techniques.
27304 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Smith, Benjamin M Syllabus Course Materials
CYOP 325 Detecting Software Vulnerabilities (3)
(Formerly SDEV 325.) Prerequisite: CYOP 300 or SDEV 300. An in-depth, practical application of techniques and tools for detecting and documenting software vulnerabilities and risks. The goal is to research, select, and use software to analyze code and isolate and prioritize application code and processes that could lead to failure or compromise data integrity or privacy. Topics include the top 25 software vulnerabilities, secure coding guidelines, static code analysis, and software assurance metrics. Students may receive credit for only one of the following courses: CYOP 325 or SDEV 325.
Start date has passed. Please register for the next start date.
21341 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Fair, Zachary Syllabus Course Materials
CYOP 325 Detecting Software Vulnerabilities (3)
(Formerly SDEV 325.) Prerequisite: CYOP 300 or SDEV 300. An in-depth, practical application of techniques and tools for detecting and documenting software vulnerabilities and risks. The goal is to research, select, and use software to analyze code and isolate and prioritize application code and processes that could lead to failure or compromise data integrity or privacy. Topics include the top 25 software vulnerabilities, secure coding guidelines, static code analysis, and software assurance metrics. Students may receive credit for only one of the following courses: CYOP 325 or SDEV 325.
23843 7380 12 Mar 2025-06 May 2025 Closed Online
Faculty: Khan, Muhammad A Syllabus Course Materials
CYOP 325 Detecting Software Vulnerabilities (3)
(Formerly SDEV 325.) Prerequisite: CYOP 300 or SDEV 300. An in-depth, practical application of techniques and tools for detecting and documenting software vulnerabilities and risks. The goal is to research, select, and use software to analyze code and isolate and prioritize application code and processes that could lead to failure or compromise data integrity or privacy. Topics include the top 25 software vulnerabilities, secure coding guidelines, static code analysis, and software assurance metrics. Students may receive credit for only one of the following courses: CYOP 325 or SDEV 325.
24741 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Fair, Zachary Syllabus Course Materials
CYOP 325 Detecting Software Vulnerabilities (3)
(Formerly SDEV 325.) Prerequisite: CYOP 300 or SDEV 300. An in-depth, practical application of techniques and tools for detecting and documenting software vulnerabilities and risks. The goal is to research, select, and use software to analyze code and isolate and prioritize application code and processes that could lead to failure or compromise data integrity or privacy. Topics include the top 25 software vulnerabilities, secure coding guidelines, static code analysis, and software assurance metrics. Students may receive credit for only one of the following courses: CYOP 325 or SDEV 325.
25377 7650 12 Mar 2025-06 May 2025 M 6:30P-9:30P Open Dorsey Station (Hybrid)
Faculty: Royal, Brandon R Syllabus Course Materials
Note: Dorsey Station: Classroom assignments are subject to change. Please view the electronic board in the hallway for your classroom assignment.
CYOP 325 Detecting Software Vulnerabilities (3)
(Formerly SDEV 325.) Prerequisite: CYOP 300 or SDEV 300. An in-depth, practical application of techniques and tools for detecting and documenting software vulnerabilities and risks. The goal is to research, select, and use software to analyze code and isolate and prioritize application code and processes that could lead to failure or compromise data integrity or privacy. Topics include the top 25 software vulnerabilities, secure coding guidelines, static code analysis, and software assurance metrics. Students may receive credit for only one of the following courses: CYOP 325 or SDEV 325.
Start date has passed. Please register for the next start date.
27199 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Donoho, Lucas M. Syllabus Course Materials
CYOP 350 Database Security (3)
(Formerly SDEV 350.) Prerequisite: CMSC 320 or CYOP 200. A study of processes and techniques for securing databases. The objective is to design, build, and maintain databases to minimize risks and security attacks. Topics include privileges and roles, user accounts, encryption, authentication methods, and auditing. Students may receive credit for only one of the following courses: CYOP 350 or SDEV 350.
Start date has passed. Please register for the next start date.
21350 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Haseltine, Reginald Yagel Syllabus Course Materials
CYOP 350 Database Security (3)
(Formerly SDEV 350.) Prerequisite: CMSC 320 or CYOP 200. A study of processes and techniques for securing databases. The objective is to design, build, and maintain databases to minimize risks and security attacks. Topics include privileges and roles, user accounts, encryption, authentication methods, and auditing. Students may receive credit for only one of the following courses: CYOP 350 or SDEV 350.
Start date has passed. Please register for the next start date.
22290 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: De Los Santos, Ivan A. Syllabus Course Materials
CYOP 350 Database Security (3)
(Formerly SDEV 350.) Prerequisite: CMSC 320 or CYOP 200. A study of processes and techniques for securing databases. The objective is to design, build, and maintain databases to minimize risks and security attacks. Topics include privileges and roles, user accounts, encryption, authentication methods, and auditing. Students may receive credit for only one of the following courses: CYOP 350 or SDEV 350.
23844 7380 12 Mar 2025-06 May 2025 Closed Online
Faculty: Haseltine, Reginald Yagel Syllabus Course Materials
CYOP 350 Database Security (3)
(Formerly SDEV 350.) Prerequisite: CMSC 320 or CYOP 200. A study of processes and techniques for securing databases. The objective is to design, build, and maintain databases to minimize risks and security attacks. Topics include privileges and roles, user accounts, encryption, authentication methods, and auditing. Students may receive credit for only one of the following courses: CYOP 350 or SDEV 350.
24519 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Syllabus Course Materials
CYOP 360 Secure Software Engineering (3)
(Formerly SDEV 360.) Prerequisite: CMSC 215 or CYOP 200. An in-depth study of the processes, standards, and regulations associated with secure software engineering. The objective is to plan, manage, document, and communicate all phases of a secure software development cycle. Topics include security requirements, secure software life cycle development, threat modeling, and Security Technical Implementation Guides (STIGs). Students may receive credit for only one of the following courses: CYOP 360 or SDEV 360.
Start date has passed. Please register for the next start date.
21633 6380 08 Jan 2025-04 Mar 2025 Closed Online
Faculty: Gabello, David P Syllabus Course Materials
CYOP 360 Secure Software Engineering (3)
(Formerly SDEV 360.) Prerequisite: CMSC 215 or CYOP 200. An in-depth study of the processes, standards, and regulations associated with secure software engineering. The objective is to plan, manage, document, and communicate all phases of a secure software development cycle. Topics include security requirements, secure software life cycle development, threat modeling, and Security Technical Implementation Guides (STIGs). Students may receive credit for only one of the following courses: CYOP 360 or SDEV 360.
Start date has passed. Please register for the next start date.
22553 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Woodson, Kevin T Syllabus Course Materials
CYOP 360 Secure Software Engineering (3)
(Formerly SDEV 360.) Prerequisite: CMSC 215 or CYOP 200. An in-depth study of the processes, standards, and regulations associated with secure software engineering. The objective is to plan, manage, document, and communicate all phases of a secure software development cycle. Topics include security requirements, secure software life cycle development, threat modeling, and Security Technical Implementation Guides (STIGs). Students may receive credit for only one of the following courses: CYOP 360 or SDEV 360.
23847 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Eyler, Carl W Syllabus Course Materials
CYOP 400 Secure Programming in the Cloud (3)
(Formerly SDEV 400.) Prerequisite: CYOP 300 or SDEV 300. A hands-on study of programming secure applications in the cloud. The goal is to design and build applications in the cloud while implementing appropriate security policies. Topics include cloud computing models, risks and security challenges of programming in the cloud, and data security. Students may receive credit for only one of the following courses: CYOP 400 or SDEV 400.
Start date has passed. Please register for the next start date.
21701 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Poma, Craig A Syllabus Course Materials
CYOP 400 Secure Programming in the Cloud (3)
(Formerly SDEV 400.) Prerequisite: CYOP 300 or SDEV 300. A hands-on study of programming secure applications in the cloud. The goal is to design and build applications in the cloud while implementing appropriate security policies. Topics include cloud computing models, risks and security challenges of programming in the cloud, and data security. Students may receive credit for only one of the following courses: CYOP 400 or SDEV 400.
23848 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Poma, Craig A Syllabus Course Materials
CYOP 425 Mitigating Software Vulnerabilities (3)
(Formerly SDEV 425.) Prerequisites: CYOP 325 (or SDEV 325) and CYOP 360 (or SDEV 360). An in-depth analysis and evaluation of the mitigation of software vulnerabilities. The aim is to detect and mitigate software vulnerabilities by evaluating code. Topics include language-specific software vulnerabilities, mitigation, and input validation. Students may receive credit for only one of the following courses: CYOP 425 or SDEV 425.
Start date has passed. Please register for the next start date.
21664 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Nebhnani, Puran C Syllabus Course Materials
CYOP 425 Mitigating Software Vulnerabilities (3)
(Formerly SDEV 425.) Prerequisites: CYOP 325 (or SDEV 325) and CYOP 360 (or SDEV 360). An in-depth analysis and evaluation of the mitigation of software vulnerabilities. The aim is to detect and mitigate software vulnerabilities by evaluating code. Topics include language-specific software vulnerabilities, mitigation, and input validation. Students may receive credit for only one of the following courses: CYOP 425 or SDEV 425.
24821 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Waithe, Errol S. Syllabus Course Materials
CYOP 460 Software Security Testing (3)
(Formerly SDEV 460.) Prerequisite: SDEV 425. A hands-on study of exploits, attacks, and techniques used to penetrate application security defenses and strategies for mitigating such attacks. The objective is to apply appropriate methodologies for software penetration testing to identify application weaknesses and logic flaws and to test and create scripts for exploitation and discovery. Topics include web architecture, application infrastructure, reconnaissance, discovery, mapping, and exploitation. Students may receive credit for only one of the following courses: CYOP 460 or SDEV 460.
Start date has passed. Please register for the next start date.
21702 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Eyler, Carl W Syllabus Course Materials
CYOP 460 Software Security Testing (3)
(Formerly SDEV 460.) Prerequisite: SDEV 425. A hands-on study of exploits, attacks, and techniques used to penetrate application security defenses and strategies for mitigating such attacks. The objective is to apply appropriate methodologies for software penetration testing to identify application weaknesses and logic flaws and to test and create scripts for exploitation and discovery. Topics include web architecture, application infrastructure, reconnaissance, discovery, mapping, and exploitation. Students may receive credit for only one of the following courses: CYOP 460 or SDEV 460.
24822 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Johnson, Kyle L Syllabus Course Materials
CYOP 495 Cyber Operations Capstone (3)
Prerequisite: 27 credits of Cyber Operations major coursework. A comprehensive project-driven study of cyber operations, network collection tactics, techniques, and procedures and reverse engineering and malware analysis with an emphasis on the proactive response to triggers or unusual activity. The objective is to use appropriate tools and techniques to monitor cyber operations. Topics include wireless and virtual networks, cryptography, network monitoring and intrusion analysis, threat hunting, and secure software engineering.
Start date has passed. Please register for the next start date.
26177 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Klein, Jamy D Syllabus Course Materials
CYOP 495 Cyber Operations Capstone (3)
Prerequisite: 27 credits of Cyber Operations major coursework. A comprehensive project-driven study of cyber operations, network collection tactics, techniques, and procedures and reverse engineering and malware analysis with an emphasis on the proactive response to triggers or unusual activity. The objective is to use appropriate tools and techniques to monitor cyber operations. Topics include wireless and virtual networks, cryptography, network monitoring and intrusion analysis, threat hunting, and secure software engineering.
26178 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Klein, Jamy 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.
22160 6380 08 Jan 2025-04 Mar 2025 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.
22271 6381 08 Jan 2025-04 Mar 2025 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.
22278 6382 08 Jan 2025-04 Mar 2025 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.
Start date has passed. Please register for the next start date.
22296 6383 08 Jan 2025-04 Mar 2025 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.
22366 6384 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Ezzati, Parinaz 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.
22589 6385 08 Jan 2025-04 Mar 2025 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.
22700 6386 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Pearson, Christy Lynn 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.
23215 6980 12 Feb 2025-08 Apr 2025 Closed Online
Faculty: Quintieri, Michael 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.
23236 6981 12 Feb 2025-08 Apr 2025 Closed Online
Faculty: Larson, Deanne 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.
23316 6982 12 Feb 2025-08 Apr 2025 Open Online
Faculty: Momtaz, Maliha 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.
24704 7380 12 Mar 2025-06 May 2025 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.
24847 7381 12 Mar 2025-06 May 2025 Closed Online
Faculty: Zimmer, Janet 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.
24877 7382 12 Mar 2025-06 May 2025 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.
24927 7383 12 Mar 2025-06 May 2025 Open Online
Faculty: Mintz, Renae 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.
27416 6387 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Green, Toni 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.
22472 6380 08 Jan 2025-04 Mar 2025 Open 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.
22544 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Wong, Sze Wing 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.
25002 7380 12 Mar 2025-06 May 2025 Closed 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.
25033 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Moustafa, Rida E 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.
22252 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Burkhardt, Michael H 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.
22273 6381 08 Jan 2025-04 Mar 2025 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.
22570 6382 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Cook, John 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.
24705 7380 12 Mar 2025-06 May 2025 Open 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.
24843 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Zeleke, Abebaw 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.
24869 7382 12 Mar 2025-06 May 2025 Open Online
Faculty: 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.
27320 6383 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Crombie, George W 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.
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22244 6380 08 Jan 2025-04 Mar 2025 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.
22245 6381 08 Jan 2025-04 Mar 2025 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.
23232 6980 12 Feb 2025-08 Apr 2025 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.
24817 7380 12 Mar 2025-06 May 2025 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.
24853 7381 12 Mar 2025-06 May 2025 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.
25057 7382 12 Mar 2025-06 May 2025 Open Online
Faculty: Alkaabi, Mahfood H 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.
27139 6382 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Clay, Christopher 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.
26234 5460 12 Mar 2025-06 May 2025 W 6:30P-9:30P Open Laurel (Hybrid)
Faculty: Bryant, Richoun Denise 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.
26235 6380 08 Jan 2025-04 Mar 2025 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.
26236 6381 08 Jan 2025-04 Mar 2025 Open 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.
26237 6382 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Thomas, Sunela 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.
26238 6383 08 Jan 2025-04 Mar 2025 Open 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.
26240 7380 12 Mar 2025-06 May 2025 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.
26241 7381 12 Mar 2025-06 May 2025 Closed 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.
26242 7382 12 Mar 2025-06 May 2025 Open Online
Faculty: Heuermann, Lewis Edward 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.
26243 7383 12 Mar 2025-06 May 2025 Open Online
Faculty: 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.
22251 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Duncan, Jessica 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.
22480 6381 08 Jan 2025-04 Mar 2025 Closed Online
Faculty: Heuermann, Lewis Edward 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.
24706 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: King, Brandon I 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.
24852 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: 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.
27392 6382 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Leon Rodriguez, Javier Eduardo 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.
27521 7382 12 Mar 2025-06 May 2025 Open Online
Faculty: 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.
22250 6380 08 Jan 2025-04 Mar 2025 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.
Start date has passed. Please register for the next start date.
22642 6381 08 Jan 2025-04 Mar 2025 Open 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.
24707 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Chesney, Steve L 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.
25017 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Jemberie, Chalachew T Syllabus Course Materials
DATA 440 Advanced Machine Learning (3)
Prerequisites: DATA 230 and DATA 430. A project-based study of advanced concepts and applications in machine learning (ML) such as neural networks, support vector machines (SVM), ensemble models, deep learning, and reinforced learning. Emphasis is on building predictive models for practical business and social problems, developing complex and explainable predictive models, assessing classifiers, and comparing their performance. All stages of the machine learning life cycles are developed, following industry best practices for selecting methods and tools to build ML models, including Auto ML.
Start date has passed. Please register for the next start date.
22237 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Rai, Paritosh Syllabus Course Materials
DATA 440 Advanced Machine Learning (3)
Prerequisites: DATA 230 and DATA 430. A project-based study of advanced concepts and applications in machine learning (ML) such as neural networks, support vector machines (SVM), ensemble models, deep learning, and reinforced learning. Emphasis is on building predictive models for practical business and social problems, developing complex and explainable predictive models, assessing classifiers, and comparing their performance. All stages of the machine learning life cycles are developed, following industry best practices for selecting methods and tools to build ML models, including Auto ML.
24812 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Paul, Rahul Syllabus Course Materials
DATA 440 Advanced Machine Learning (3)
Prerequisites: DATA 230 and DATA 430. A project-based study of advanced concepts and applications in machine learning (ML) such as neural networks, support vector machines (SVM), ensemble models, deep learning, and reinforced learning. Emphasis is on building predictive models for practical business and social problems, developing complex and explainable predictive models, assessing classifiers, and comparing their performance. All stages of the machine learning life cycles are developed, following industry best practices for selecting methods and tools to build ML models, including Auto ML.
Start date has passed. Please register for the next start date.
27185 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Menon Gopalakrishna, Prahlad Syllabus Course Materials
DATA 440 Advanced Machine Learning (3)
Prerequisites: DATA 230 and DATA 430. A project-based study of advanced concepts and applications in machine learning (ML) such as neural networks, support vector machines (SVM), ensemble models, deep learning, and reinforced learning. Emphasis is on building predictive models for practical business and social problems, developing complex and explainable predictive models, assessing classifiers, and comparing their performance. All stages of the machine learning life cycles are developed, following industry best practices for selecting methods and tools to build ML models, including Auto ML.
27626 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: 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.
22238 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Bean, Brandon 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.
24813 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: 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.
26975 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Dave, Linesh Ramesh Syllabus Course Materials
DATA 450 Data Ethics (3)
Prerequisite: DATA 430. A study of ethics within the context of data science, machine learning, and artificial intelligence. Emphasis is on examining data and model bias; building explainable, fair, trustable, and accurate predictive modeling systems; and reporting responsible results. Topics include the technology implications of human-centered machine learning and artificial intelligence on decision making in organizations and government and the broader impact on society, including multinational and global effects.
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22239 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Duan, Chaojie Syllabus Course Materials
DATA 450 Data Ethics (3)
Prerequisite: DATA 430. A study of ethics within the context of data science, machine learning, and artificial intelligence. Emphasis is on examining data and model bias; building explainable, fair, trustable, and accurate predictive modeling systems; and reporting responsible results. Topics include the technology implications of human-centered machine learning and artificial intelligence on decision making in organizations and government and the broader impact on society, including multinational and global effects.
24814 7380 12 Mar 2025-06 May 2025 Open Online
Faculty: Menon Gopalakrishna, Prahlad Syllabus Course Materials
DATA 450 Data Ethics (3)
Prerequisite: DATA 430. A study of ethics within the context of data science, machine learning, and artificial intelligence. Emphasis is on examining data and model bias; building explainable, fair, trustable, and accurate predictive modeling systems; and reporting responsible results. Topics include the technology implications of human-centered machine learning and artificial intelligence on decision making in organizations and government and the broader impact on society, including multinational and global effects.
Start date has passed. Please register for the next start date.
26767 6381 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Elchouemi, Amr Syllabus Course Materials
DATA 450 Data Ethics (3)
Prerequisite: DATA 430. A study of ethics within the context of data science, machine learning, and artificial intelligence. Emphasis is on examining data and model bias; building explainable, fair, trustable, and accurate predictive modeling systems; and reporting responsible results. Topics include the technology implications of human-centered machine learning and artificial intelligence on decision making in organizations and government and the broader impact on society, including multinational and global effects.
27087 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Knode, Charles S Syllabus Course Materials
DATA 460 Artificial Intelligence Solutions (3)
(Designed to help prepare for the AWS Certified Machine Learning or Microsoft Designing and Implementing an Azure AI Solution exam.) Prerequisite: DATA 430. A hands-on, project-based study of artificial intelligence and machine learning solutions to complex problems. Topics include natural language processing, computer vision, and speech recognition.
Start date has passed. Please register for the next start date.
22473 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Skog, Jeremy Owen Syllabus Course Materials
DATA 460 Artificial Intelligence Solutions (3)
(Designed to help prepare for the AWS Certified Machine Learning or Microsoft Designing and Implementing an Azure AI Solution exam.) Prerequisite: DATA 430. A hands-on, project-based study of artificial intelligence and machine learning solutions to complex problems. Topics include natural language processing, computer vision, and speech recognition.
25003 7380 12 Mar 2025-06 May 2025 Closed Online
Faculty: Jha, Manoj K Syllabus Course Materials
DATA 460 Artificial Intelligence Solutions (3)
(Designed to help prepare for the AWS Certified Machine Learning or Microsoft Designing and Implementing an Azure AI Solution exam.) Prerequisite: DATA 430. A hands-on, project-based study of artificial intelligence and machine learning solutions to complex problems. Topics include natural language processing, computer vision, and speech recognition.
25025 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: DATA 440, DATA 445, and DATA 450. A project based, practical application of the knowledge, technical skills, and critical thinking skills acquired during previous study designed to showcase the student's data science expertise. individually selected projects include all phases of machine learning life cycles 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.
22474 6380 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Chesney, Steve L Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: DATA 440, DATA 445, and DATA 450. A project based, practical application of the knowledge, technical skills, and critical thinking skills acquired during previous study designed to showcase the student's data science expertise. individually selected projects include all phases of machine learning life cycles 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.
25004 7380 12 Mar 2025-06 May 2025 Closed Online
Faculty: Rai, Paritosh Syllabus Course Materials
DATA 495 Data Science Capstone (3)
Prerequisites: DATA 440, DATA 445, and DATA 450. A project based, practical application of the knowledge, technical skills, and critical thinking skills acquired during previous study designed to showcase the student's data science expertise. individually selected projects include all phases of machine learning life cycles 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.
25013 7381 12 Mar 2025-06 May 2025 Open Online
Faculty: Cook, John A Syllabus Course Materials
ECON 103 Economics in the Information Age (3)
A survey of basic concepts and principles in micro- and macroeconomics and how the economy has been affected by technology. The aim is to define and explain the key terms and concepts in economics and determine how technology has affected consumers, producers, and markets, as well as economic growth and policy. Topics include how innovation affects labor markets, the value of information, and the role of technological change in the economy.
Start date has passed. Please register for the next start date.
21153 6380 08 Jan 2025-04 Mar 2025 Closed Online
Faculty: Asif, Salma Syllabus Course Materials
ECON 103 Economics in the Information Age (3)
A survey of basic concepts and principles in micro- and macroeconomics and how the economy has been affected by technology. The aim is to define and explain the key terms and concepts in economics and determine how technology has affected consumers, producers, and markets, as well as economic growth and policy. Topics include how innovation affects labor markets, the value of information, and the role of technological change in the economy.
Start date has passed. Please register for the next start date.
21154 6381 08 Jan 2025-04 Mar 2025 Closed Online
Faculty: Rice, Richard E Syllabus Course Materials
ECON 103 Economics in the Information Age (3)
A survey of basic concepts and principles in micro- and macroeconomics and how the economy has been affected by technology. The aim is to define and explain the key terms and concepts in economics and determine how technology has affected consumers, producers, and markets, as well as economic growth and policy. Topics include how innovation affects labor markets, the value of information, and the role of technological change in the economy.
Start date has passed. Please register for the next start date.
21155 6382 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Light, Joel Norman Syllabus Course Materials
ECON 103 Economics in the Information Age (3)
A survey of basic concepts and principles in micro- and macroeconomics and how the economy has been affected by technology. The aim is to define and explain the key terms and concepts in economics and determine how technology has affected consumers, producers, and markets, as well as economic growth and policy. Topics include how innovation affects labor markets, the value of information, and the role of technological change in the economy.
Start date has passed. Please register for the next start date.
21994 6383 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Greenfield, Stuart J Syllabus Course Materials
ECON 103 Economics in the Information Age (3)
A survey of basic concepts and principles in micro- and macroeconomics and how the economy has been affected by technology. The aim is to define and explain the key terms and concepts in economics and determine how technology has affected consumers, producers, and markets, as well as economic growth and policy. Topics include how innovation affects labor markets, the value of information, and the role of technological change in the economy.
Start date has passed. Please register for the next start date.
22111 6384 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Light, Joel Norman Syllabus Course Materials
ECON 103 Economics in the Information Age (3)
A survey of basic concepts and principles in micro- and macroeconomics and how the economy has been affected by technology. The aim is to define and explain the key terms and concepts in economics and determine how technology has affected consumers, producers, and markets, as well as economic growth and policy. Topics include how innovation affects labor markets, the value of information, and the role of technological change in the economy.
Start date has passed. Please register for the next start date.
22193 6385 08 Jan 2025-04 Mar 2025 Open Online
Faculty: Almoguera, Pedro A Syllabus Course Materials
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