Updated: 5/26/2021

CSE 190 - Topics in Computer Science and Engineering

Units: 4

Course Description:  Topics of special interest in Computer Science and Engineering. Topics may vary from quarter to quarter.

Prerequisites: Prerequisites vary per course per instructor. Department stamp required.

Offered: Every quarter as staffing allows

- May be repeated for credit max 3 times (maximum of 12 units; assuming courses taken for a different topic)

- A maximum of ONE CSE 190 may enrolled/waitlisted per quarter


Fall 2021


CSE 190 A00: TBA with Nuno Bandiera

Course information pending instructor confirmation


CSE 190 B00: Post-Relational Data Models with Professor Alin Deutsch

Prerequisites: CSE 132A or approved equivalent

To enroll: Submit course clearance request via Enrollment Authorization System (EASy)

Description: The course surveys a wide range of post-relational data models and high-level query languages that have achieved prominence with the advent of the Big Data era. These include graph database models and query languages in their various incarnations, such as XML and its standard query languages XPath and XQuery;  JSON and its query languages SparkSQL, AQL, MongoDB's query language, etc.;  RDF and Semantic Web data (SparQL); graph databases (neo4j's graph data model and the Cypher query language, the Gremlin query language, the upcoming GQL standard, etc.). The course emphasizes the common ideas across these models and languages, connecting them to their common roots in object-oriented and SQL databases. Attendants will be prepared to face any new model by learning how to classify its primitive along model-transcendent dimensions. They will also acquire practical data modeling and query programming skills required by today's data scientists.


CSE 190 C00: Human-AI Interaction with Kristen Vaccaro

Prerequisite(s): No course prerequisites, but all assignments will be in Python (students are expected to be proficient in Python if enrolling in this course)

To enroll: Submit course clearance request via Enrollment Authorization System (EASy)

Description: This course provides an introduction to harnessing the power of AI so that it benefits people and communities. Topics will include: agency and initiative, fairness and bias, transparency and explainability, confidence and errors, and privacy, ethics, and trust. Students will build a number of interactive technologies powered by AI, gain practical experience with what makes them more or less usable, and learn to evaluate their impact on individuals and communities. Students will learn to think critically (but also optimistically) about what AI systems can do and how they should be integrated into society.