My Courses
Information Security & Risk Management
ISM 6328
Fall 2026
This course builds a practical foundation in assessing IT risk and implementing information security controls across an organization. We'll study the major categories of information security threats, from malware and phishing to unauthorized access and network vulnerabilities, alongside the common controls used to mitigate them. The curriculum covers access controls, security operations and administration, auditing, testing, and monitoring, as well as cryptography and its role in protecting data. We'll examine the Internet of Things as an expanding attack surface and study malicious code and activity within the context of enterprise networks and telecommunications. Significant emphasis is placed on the legal and regulatory landscape, including U.S. compliance laws and the standard methodologies organizations use to meet them, alongside recognized information security standards and professional certifications (CEH, CISM, Security+, CISSP, GSEC) that define the field. Topics also include risk response and recovery planning, giving a full lifecycle view from threat identification through incident remediation. The course is built around chapter-based readings and aligned quizzes, providing structured exposure to the terminology, frameworks, and technical vocabulary used by cybersecurity professionals. This course complements my other systems and data coursework by focusing specifically on how organizations identify, evaluate, and control information security risk at an enterprise scale.
Text Analytics
ISM 6564
Fall 2026
This course provides a thorough foundation in transforming unstructured text into working, production-grade AI systems. We'll study the fundamentals of text analytics, including tokenization schemes, vector representations of documents, and the distance and similarity metrics used to judge textual relatedness, before applying predictive modeling techniques to encoded text. The curriculum traces the evolution of language modeling from recurrent networks and the attention mechanism through the transformer architecture, covering how large and small language models are built, deployed locally, and accessed through commercial APIs. We'll compare adaptation strategies including prompting, retrieval, and parameter-efficient fine-tuning, learning the trade-offs and appropriate use cases for each. Significant emphasis is placed on grounding models in organizational data through retrieval-augmented generation and context engineering, as well as governed tool use through the Model Context Protocol and multi-agent coordination under least-privilege permissions. Topics also include red-teaming, evaluation harnesses, and the governance practices needed to move an AI system from demonstration to defensible production release. The hands-on components involve weekly notebook assignments, documented AI-assisted development, and a capstone project designing, building, and defending a working multi-agent system. This course complements my other data and analytics coursework by focusing specifically on how to build, secure, and govern language-model-based systems for enterprise use.
Enterprise Information Systems Management
ISM 6155
Fall 2026
This course examines how enterprises align IT strategy with business goals while navigating the growing role of AI in organizational decision-making. We'll study foundational strategy frameworks, including the IS Strategy Triangle and Porter's Competitive Advantage, and apply them to real business problems involving fragmented data systems and operational inefficiencies. The curriculum covers organizing and governing enterprise IS resources, leading IS initiatives through change management, and structuring IT architecture, control, and security. We'll examine how AI capabilities are reshaping enterprise systems, including autonomous decision-making in areas like hiring, lending, and supply chain logistics, and the corresponding risks of algorithmic bias and operational failure. Significant emphasis is placed on ethical, legal, and governance frameworks for AI (such as HEVIDS and the AEGIS Analysis Method), alongside global IS considerations and cross-cultural management. Topics also include policy development, compliance structures, and advanced analytics as tools for enterprise decision-making. The hands-on components involve case study analyses of real business challenges, an ongoing analysis portfolio connecting concepts to career goals, and a capstone group project building a C-suite-ready AI implementation strategy complete with ROI calculations and risk mitigations, defended in a live executive pitch. This course complements my other analytics and systems coursework by focusing specifically on how to lead, govern, and justify enterprise technology decisions at a strategic level.
Big Data for Business Applications
ISM 6562
Spring 2026
This is an intensive, hands-on course focused on managing and analyzing massive datasets using modern big data technologies. The course starts with PostgreSQL fundamentals and distributed SQL, then progresses to NoSQL databases like Cassandra and MongoDB, teaching us when to apply relational versus non-relational approaches. The second half covers big data processing frameworks, Hadoop, MapReduce, and Apache Spark, where we'll build distributed data processing pipelines using PySpark and implement machine learning at scale with SparkML. Everything is containerized using Docker, and we'll work extensively with Git for version control and Linux command line tools. The assessment structure includes two major team projects instead of traditional exams: a midterm comparing different database architectures and a final project building an end-to-end analytics pipeline. We'll also explore stream processing with Kafka and modern cloud data platforms like Databricks. The course emphasizes practical implementation, weekly labs, DataCamp modules, and real-world applications. It bridges the gap between theoretical understanding and the technical skills companies actually need for working with big data in production environments, covering everything from CAP theorem implications to query optimization strategies.
Advanced Systems Analysis and Design
ISM 6124
Spring 2026
This is a concentrated eight week online course that covers the complete systems development life cycle, from initial project selection through implementation planning. We'll work through structured and object-oriented methodologies, learning to create comprehensive system models including use cases, process models, data models, and architectural designs. Each week focuses on a different SDLC phase, building toward an integrated understanding of how information systems are conceived, analyzed, designed, and implemented in organizational contexts. The course explores both traditional waterfall and agile development approaches, teaching us when each methodology is most appropriate. Assessment includes weekly reflection assignments connecting concepts to industry applications, regular quizzes, and a group project where we'll develop a complete system proposal. We'll also compile an annotated bibliography examining the evolution of agile methodologies in systems development. The emphasis is on both technical rigor and professional communication, learning to translate business requirements into system specifications and present solutions effectively to stakeholders. This course is designed to prepare us for roles as systems analysts, business analysts, or IT consultants who bridge the gap between business needs and technical implementation.
Data Warehousing
ISM 6208
Spring 2026
This course provides a thorough foundation in designing and implementing enterprise data warehouses for business intelligence and analytics. We'll study fundamental architectures including star schemas, snowflake schemas, and dimensional modeling techniques that optimize data warehouses for analytical queries. The curriculum covers designing fact and dimension tables, managing slowly changing dimensions, and building ETL (Extract, Transform, Load) processes to integrate data from multiple source systems. We'll compare traditional data warehouse approaches with modern data lake architectures, learning the trade-offs and appropriate use cases for each. Significant emphasis is placed on data quality, governance, and metadata management, the foundational work that makes data warehouses valuable for decision-making. Topics also include OLAP cubes, data marts, and performance optimization for complex analytical workloads. The hands-on components involve actually designing warehouse schemas and implementing dimensional models, providing practical experience with the tools and techniques used in production environments. This course complements my other database and analytics coursework by focusing specifically on how to structure and manage data for business intelligence, reporting, and analytical applications at enterprise scale.
Application Development for Analytics
ISM 6225
Spring 2026
This course focuses on the operational and technical responsibilities of managing production database systems. We'll cover essential DBA tasks including installation and configuration, backup and recovery strategies, security and access control, performance monitoring and tuning, and capacity planning. The curriculum teaches advanced SQL query writing and optimization, index management for performance, implementation of database security through users, roles, and permissions, and development of comprehensive disaster recovery plans. We'll work with both SQL Server and PostgreSQL, learning platform-specific administration tools while understanding universal DBA principles that apply across database systems. Key skills include reading execution plans, identifying performance bottlenecks, and tuning queries to improve application responsiveness. The course also addresses contemporary concerns such as cloud database services, automated backup solutions, and monitoring tools. Hands-on lab exercises provide practical experience performing common DBA tasks in simulated production environments. This course is designed to prepare us for database administrator roles where we'd be responsible for ensuring that critical business data systems remain secure, available, performant, and properly maintained, skills that are fundamental to supporting any organization's data infrastructure.
Data Visualization for Storytelling
ISM 6419
Summer 2026
This course provides a hands-on foundation in the principles and practice of data and information visualization for communicating insights effectively. We'll study what separates truthful visualizations from misleading ones, examining the design choices and statistical framing that shape how a chart is interpreted. The curriculum covers the full arc of visual storytelling: identifying a research area and formulating research questions, sourcing relevant data, and building visualizations that clearly and compellingly support a narrative. Significant emphasis is placed on Tableau, where we work through data preparation, combining visualizations, animations, and parameters to build increasingly sophisticated dashboards. We also explore data visualization in Python, comparing code-based approaches with drag-and-drop BI tools. Additional topics include accessibility considerations for visualizations, such as designing for visual impairment, and the broader question of how to responsibly use data to tell a story without distorting it. The course culminates in a final project requiring a comparative essay, a full project report with visualizations, a project presentation, and a reflective essay, giving practical experience presenting analytical findings the way they'd be delivered in a professional setting. This course complements my other analytics coursework by focusing specifically on the communication layer of data work: how to turn analysis into a visual narrative that drives decision-making.
Foundations of Business Statistics
QMB 6304
Fall 2025
This course provided the statistical foundation I needed for data analysis and business decision-making. We covered descriptive statistics, probability theory, hypothesis testing, confidence intervals, regression analysis, and ANOVA. I learned how to analyze datasets, test hypotheses about business problems, and interpret statistical results to make recommendations. The course emphasized practical application, we used statistical software to work with real business data and learned how to communicate our findings effectively. This class was essential for understanding the mathematical reasoning behind many data analytics and machine learning techniques. It taught me how to think critically about data, recognize patterns, understand variability, and make decisions based on evidence rather than intuition.
Advanced Database Management
ISM 6218
Fall 2025
This was probably my favorite course, it went deep into database design and management. We started with the fundamentals of relational databases and entity-relationship modeling, then moved into advanced SQL for complex queries, triggers, and views. I learned about database normalization to eliminate redundancy, indexing strategies to improve performance, and transaction management to ensure data integrity. We covered both traditional SQL databases and newer NoSQL alternatives, discussing when each approach makes sense. The course also introduced OLAP systems for business intelligence and data warehousing concepts. The hands-on labs were great, I got to design complete database systems from scratch, implement them in SQL Server, and optimize their performance. This course gave me the skills to not just use databases, but to design and manage them effectively.
Machine Learning
ISM 6251
Fall 2025
This was an intensive, hands-on course in machine learning that really challenged me. We covered a wide range of ML algorithms like, decision trees, random forests, regression models, neural networks, support vector machines, k-nearest neighbors, and clustering techniques. The course emphasized practical implementation using Python with libraries like scikit-learn, PyTorch, and TensorFlow. Every week we had coding assignments where we applied these algorithms to real datasets, learning how to preprocess data, engineer features, train models, and evaluate their performance. We worked in groups on larger projects that required us to tackle real-world prediction problems from start to finish. The course taught me not just how the algorithms work mathematically, but how to choose the right approach for different problems and interpret what the models are telling us. It was demanding but incredibly rewarding, I came out of it confident in my ability to apply machine learning to business problems.
Managing Information Resources
ISM 4300
Spring 2025
This course was all about understanding how organizations manage their IT resources strategically. We covered IT governance, basically how companies make decisions about technology investments and align them with business goals. We discussed information security management, data governance strategies, and how to structure enterprise architecture. The course emphasized the business side of IT, looking at how technology can drive competitive advantage and support organizational strategy. I learned how to think about IT not just as a technical function, but as a strategic asset that needs careful management and planning.
Project Management for Business Majors
ISM 4314
Spring 2025
This course gave me a solid foundation in project management principles and practices. We learned about the Project Management Body of Knowledge (PMBOK) and covered the complete project lifecycle from initiation and planning through execution, monitoring, and closeout. The course taught both traditional Waterfall methodology and Agile approaches like Scrum and Kanban, helping me understand when to use each approach. We worked on real project plans using Microsoft Project, created work breakdown structures, managed schedules and budgets, and learned how to handle risks and stakeholder communications. The group projects gave me practical experience working on teams and dealing with the challenges that come up in real project environments. This course was incredibly practical and directly applicable to any role where you need to manage initiatives or work on cross-functional teams.
Business Data Communications
ISM 4220
Fall 2024
In this course, I learned about the network infrastructure and data communication technologies that businesses rely on every day. We covered how data moves across networks from local area networks (LANs) in offices to wide area networks (WANs) connecting different locations. The course explained network protocols like TCP/IP, wireless networking, cloud computing infrastructure, and network security concepts. I gained an understanding of how organizations design and manage their network architecture to support business operations reliably and securely. This course helped me appreciate the technical foundation that makes all our business applications and data systems work seamlessly.
Database Administration and Design
ISM 4212
Fall 2024
Introduction to database design and administration covering data modeling, ERD/EERD creation, normalization, relational schema design, and SQL implementation. Focus on creating normalized database designs, implementing physical databases with proper constraints and referential integrity, and developing SQL queries and programmable objects for real-world applications.