Teaching
Courses at the University of Michigan School of Information.
Courses
SI 608 — Networks
Covers topics in network analysis, from social networks to applications in information networks such as the internet. We introduce basic concepts in network theory, discuss metrics and models, use software analysis tools to experiment with a wide variety of real-world network data, and study applications to areas such as information retrieval.
Fall 2017, 2018, 2019, 2020, 2021, 2022, 2024, 2025 · Winter 2016, 2017
SI 650 — Information Retrieval
Students learn the underlying technologies of search engines, recommendation systems, and other powerful tools for connecting people with information. Topics include the basic principles and algorithms for information retrieval, along with hands-on experience building search engines and improving search accuracy.
Fall 2024, 2025
SI 618 — Data Manipulation and Analysis
Helps students get started with data harvesting, processing, aggregation, and analysis. Topics include using APIs to collect data, SQL, and Spark via Python. Earlier iterations used R for exploratory data analysis; later versions use Python for those tasks as well.
Fall 2017, 2019, 2020, 2021, 2022 · Winter 2017
SI 699 — Big Data Analytics
Students demonstrate mastery of data collection, processing, analysis, retrieval, mining, visualization, and prediction. The course synthesizes methods from information retrieval, statistical data analysis, data mining, machine learning, and other big-data fields. Students work on semester-long projects with industry-scale data sets solving real-world problems.
Winter 2019, 2020, 2021, 2025
SIADS 699 — Capstone
A project-based course in which students propose and build end-to-end data science projects in their domains of interest. Students demonstrate mastery of data science concepts from their MADS training and produce a creative, original, and technically rigorous portfolio piece. Projects are supervised by instructors with regular peer review.
Winter 2023