Data Science in Enterprise Computing Graduate Academic Certificate

Course Description:
This graduate-level course provides an in-depth exploration of enterprise computing with a focus on mainframe technologies in modern business operations. Students will learn about mainframe security, data compliance, automation, performance optimization, and emerging trends like quantum computing threats, AIOps, and API-driven integration. Hands-on labs and real-world projects reinforce key concepts, while guest lectures highlight career paths in system administration, application development, security, and business analysis. By the end of the course, students will be equipped to design, manage, and optimize mainframe solutions in hybrid cloud and enterprise environments.

 Course Objectives:
By completing this course, students will be able to:

• Explain the role of mainframes in hybrid cloud environments and enterprise computing.
• Identify mainframe security models (RACF, TSS, ACF2), data compliance regulations, and post-quantum cryptography strategies.
• Implement automation techniques for job scheduling, system management, and resource optimization using mainframe tools.
• Utilize key metrics and monitoring tools to optimize mainframe workloads and ensure system reliability.
• Discuss advancements such as AIOps, API integration, telemetry, and mainframe support for modern programming languages.
• Manage data storage, databases, and real-time processing with industry-standard tools and technologies.
• identify key roles and their major responsibilities in mainframe world.

 Course Format:
This course is designed to be highly interactive and experiential. Students will learn through a combination of guest lectures, group discussions, and direct engagement with industry professionals. Guest speakers—including mainframe experts from leading companies—will provide real-world insights into mainframe roles, technologies, and career pathways. Students will have opportunities to interact with professionals in the field through panel sessions, Q&A events, and networking activities, gaining firsthand perspectives on the current and future landscape of mainframe computing.

Course Description: 
This course introduces students to the fundamentals of software design, development, and testing using common business tools and languages such as COBOL in a mainframe environment. Covers the language syntax as well as a variety of data and file structures. In addition, the course explores issues related to data validation and reporting as it relates to business problems.  Students gain experience working in both a batch and interactive environment using a variety of computing hardware including mainframe computers.

Course Objectives:
By completing this course, students will be able to: 

• Understand how to design, develop, and test computer software needed to address common business problems.
• Develop expertise across a variety of computing platforms, including mainframe computers.
• Develop expertise using commonly used programming environments and languages such as COBOL.
• Develop expertise with ASCII and EBCDIC data formatting
• Develop expertise using Job Control Language (JCL) and mainframe utilities
• Develop expertise with File Transfer Protocol (FTP)
• Develop critical thinking skills by analyzing mainframe-related business products

Course Format: 
This class meets each week. This course is a heavily hands-on course working with software and systems commonly found in business environments.  Student progress will be measured using a combination of assignments, exams, and a final project.

Course Description: 
This course focuses on concepts related to advanced COBOL programming such as computer utilization, advanced business applications, structures, debugging techniques and tools. Students explore advanced techniques related to software design on interactive systems using a variety of software development tools.  Other topics include advanced file processing, utilities, batch and interactive JCL, report writer and other advanced features of COBOL.

Course Objectives:
By completing this course, students will be able to: 

• Gain mastery of how to design, develop, and test computer software needed to address common business problems.
• Gain mastery of working on mainframe computers using both batch and interactive JCL.
• Gain an understanding of how to use advanced features of the COBOL programming language, which include VSAM file handling, tables, and internal sorting.
• Gain a mastery of data formats and data handling.
• Develop a proficiency in hexadecimal math to analyze core dumps.
• Develop critical thinking skills by analyzing mainframe-related business decisions

Course Format: 
This class meets each week. This is a heavily hands-on course that involves working with software and systems commonly found in enterprise computing environments. The course is structured to provide a blend of theoretical understanding of programming languages and tools with associated hands-on assignments and real-world projects, ensuring students gain both conceptual knowledge and practical experience.

Note: 
BCIS 5550 requires completion of BCIS 5540.

Course Description:
This course explores the integration of Data Science and Artificial Intelligence (AI) within mainframe systems, highlighting their role in enterprise data processing and analytics. Students will learn how mainframes handle big data, secure data storage, machine learning, and deep learning applications at scale. Key topics include data collection, preprocessing, exploratory analysis, model deployment, and high-performance computing using mainframe technologies like Db2, VSAM, z/OS, and AI accelerators. The curriculum also covers data security, privacy, compliance, and industry use cases in finance, healthcare, and retail. Hands-on labs and real-world projects prepare students to design and deploy AI-driven solutions on mainframe platforms.

Course Objectives:

• Explain the architecture and capabilities of mainframes for large-scale data processing and AI applications.
• Implement secure data handling, encryption, and privacy-compliant practices in mainframe environments.
• Utilize mainframe tools like Db2, VSAM, and AI accelerators for efficient data storage and processing.
• Extract, integrate, and prepare structured and unstructured data for analysis on mainframes.
• Conduct exploratory data analysis and statistical visualization using R and Python in mainframe systems.
• Implement supervised, unsupervised, and deep learning algorithms for real-world applications on mainframes.
• Leverage mainframe-specific accelerators (IBM Telum II, Spyre) for deep learning optimization.
• Analyze real-world applications of AI in finance, healthcare, and retail, and understand future trends in mainframe AI.
• Apply best practices for deploying AI and machine learning models on z/OS and mainframe platforms.

Course Format:
This hands-on course works with software and systems commonly found in enterprise computing environments. Students are required to attend the associated learning labs and complete other course requirements including assignments, projects and exams.