This course is intended to cover information retrieval and other information processing activities, from an applied perspective. There will be numerous programming projects and quizzes. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.

This course is intended to cover information retrieval and other information processing activities, from an applied perspective. There will be numerous programming projects and quizzes. Topics will include: search engine construction (document acquisition, processing, indexing, and querying); learning to rank; information retrieval system performance evaluation; classification and clustering; other machine learning information processing tasks; and many more.

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering with a focus on real-world applications in a variety of computing contexts (desktop/cluster/cloud). Requires the use of Python.

Introduction to core machine learning models and algorithms for classification, regression, dimensionality reduction and clustering with a focus on real-world applications in a variety of computing contexts (desktop/cluster/cloud). Requires the use of Python.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, maps, graphs, stacks, queues, searching, and sorting. (Gen Ed R2)

Prerequisites: COMPSCI 121 (or equivalent experience) and Basic Math Skills (R1). This course is not a substitute for COMPSCI 187. If unsure of whether this course or COMPSCI 187 is more appropriate, contact instructor.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, maps, graphs, stacks, queues, searching, and sorting. (Gen Ed R2)

Prerequisites: COMPSCI 121 (or equivalent experience) and Basic Math Skills (R1). This course is not a substitute for COMPSCI 187. If unsure of whether this course or COMPSCI 187 is more appropriate, contact instructor.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, maps, graphs, stacks, queues, searching, and sorting. (Gen Ed R2)

Prerequisites: COMPSCI 121 (or equivalent experience) and Basic Math Skills (R1). This course is not a substitute for COMPSCI 187. If unsure of whether this course or COMPSCI 187 is more appropriate, contact instructor.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, maps, graphs, stacks, queues, searching, and sorting. (Gen Ed R2)

Prerequisites: COMPSCI 121 (or equivalent experience) and Basic Math Skills (R1). This course is not a substitute for COMPSCI 187. If unsure of whether this course or COMPSCI 187 is more appropriate, contact instructor.

This course introduces foundational abstract data types and algorithms. The main focus is on the use of data structures in designing and developing programs to solve problems in a variety of domains. Specific topics include lists, sets, maps, graphs, stacks, queues, searching, and sorting. (Gen Ed R2)

Prerequisites: COMPSCI 121 (or equivalent experience) and Basic Math Skills (R1). This course is not a substitute for COMPSCI 187. If unsure of whether this course or COMPSCI 187 is more appropriate, contact instructor.

An introductory course in problem solving, using the programming language Java. Focuses on the fundamental concepts of problem solving and on computer implementation. Intended for computer science majors or those applying for the major. Satisfactory completion is a prerequisite for all higher-level computer science courses. Use of a laptop computer required. Prerequisite: high school algebra and basic math skills (R1). (Gen.Ed. R2)