Teaching

Below are the courses I have designed and offered at Boston University’s Questrom School of Business.

Courses I have Designed

MS770: Data Visualization (MSMS)

The ability to translate data into visuals can often make the difference between success and failure. The goal of this course is to enable students to use the most common data visualization applications such as Tableau or Microsoft Power BI to communicate data. The course will begin with querying relationship databases, integrating multiple data sources and data validation, followed by choosing the most proper visualization option, creating automated dashboards, and building an overall visual system.

IS823: Analytics for Managers (MBA)

This non-programming-based analytics course examines how the abundance of data has transformed decision making in organizations and the strategic implications of this transformation. We explore how data are being used, ranging from the core principles of properly identifying data sources to the actual analytical methods being used to solve a wide range of business problems. Students will have some hands-on work with Tableau, Orange as well as SQL and NoSQL databases. Neo4j is used to compare and contrast SQL and NoSQL databases in an analytics context. At the end of this course, students will have gained a big-picture perspective on business analytics as well as hands-on experience with commonly-used business analytics software.

IS834: Business Analytics with Python (MBA)

This course was designed for analytically-minded managers. The course covers both a hands-on introduction to python via common business analytics tasks. This course covers variables, data types and data structures, DataFrames, conditionals, loops, and functions. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting.

BA760/BA765: Introduction to Programming for Data Science (MSBA)

This course will cover the fundamentals of programming for data science using R/Python, the command line, and version control. These skills will be reinforced via lectures and hands-on exercises focused on elevating common programming challenges and highlight best practices. The aim of this course is to provide the pathway to fluency in the tools required to analyze data and fully manage data science projects both as an individual contributor as well as in team settings.

BA820: Unsupervised Machine Learning and Text Mining (MSBA)

Through a series of lectures and hands-on exercises, students will examine the techniques to unlock insights from data that appear to lack a known outcome or are considered “unstructured”. The aim of this course is to compare and contrast the application of various methods being applied today and provide the foundation to develop impactful insights using unsupervised machine learning and applied NLP.

BA882: Deploying Analytics Pipelines (MSBA)

This course will equip students with the essential skills for transitioning data analysis and machine learning tasks to the cloud, supporting production workloads. It covers the creation and deployment of data and ML pipelines, including those for generative AI applications, with a focus on data integration strategies, cloud data warehousing, BI, and ML-Ops. Leveraging prior coursework in data management and machine learning, students will learn to implement ETL/ELT processes, monitor data quality, and deploy models as APIs using cloud services.

Additional Courses Taught

IS841: Advanced Analytics for Managers - Data Mining (MBA)

I updated this course to use RapidMiner, as this offering is intentionally not a programming course. In addition, modules were added to include Deep Learning.

IS465: Managing Data Resources (UG)

This course starts with designing database applications, and then moves into data warehousing and pathways to extract value from the data (post-ETL).

IS843: Big Data Analytics for Business (MBA/MSBA)

This is a Python course focusing on analyzing data using cloud resources.