Data Science I: Machine Learning Essentials

PhD in organizational leadership, Saint Mary’s University of Minnesota; MBA and Master of Information Technology, University of Texas; Master of Health Informatics, University of Minnesota; BS in engineering, NED Engineering University of Pakistan

Dr. Saeed’s background is a blend of engineering, information technology, and education, with more than 15 years of related experience at Westinghouse, General Nanosystems, General Dynamics C4 Systems, Samsung, and others in managing and delivering various IT projects. Her experience includes leadership roles in application and web development, database design, IT infrastructure system modifications, process and product development, and operational improvements. She has worked as a program director of information technology and assistant adjunct professor of ITIS at the Saint Mary’s University of Minnesota, where she designed and managed three degree programs in areas such as information technology, business administration, and accounting.

• INET 4007 – Security II: Cloud Security and Strategy
• INET 4041 – Networking II: Emerging Technologies
• INET 4061 – Data Science I: Machine Learning Essentials
• INET 4165 – Security I: Cybersecurity Essentials

MS, business analytics and BISyE, industrial and systems engineering, University of Minnesota

Kyle Stahl is a senior data science supervisor at Cargill Inc, where he leads a team of data science specialists in solving complex machine learning and optimization problems across the agriculture industry. He has applied advanced analytics techniques to various industry groups within Cargill, including global supply chain, animal growth modeling, biochemistry, sales, agronomy, and production scheduling. Kyle works across the entire machine learning process, from defining the problem and collecting data to integrating mathematical models into software and helping people adapt their business processes to new technology.

• INET 4061 – Data Science I: Machine Learning Essentials
• INET 4062 – Data Science II: Advanced Analytics and AI

BASc, Information Technology Infrastructure, University of Minnesota

Ian-Mathew's work focuses on the development of resilient big data infrastructure, large-scale data engineering, and its application in data science. His expertise includes infrastructure, software engineering, and risk management in the finance and retail sectors. He has also served as an enterprise technical manager of open-source software and platforms used for data science and analysis. Ian-Mathew values building effective engineering cultures in teams and foregrounding ethical considerations in the development and deployment of technology. He also has more than a decade of small-team leadership experience as a veteran of the US Army and is an active contributor to initiatives to make tech more inclusive and accessible for all.

• INET 2001 – Fundamentals of IT
• INET 4061 – Data Science I: Machine Learning Essentials