This course introduces and develops methods for designing and implementing abstract data types using the Java programming language. The main focus is on how to build and encapsulate data objects and their associated operations. Specific topics include linked structures, recursive structures and algorithms, binary trees, balanced trees, and hash tables. These topics are fundamental to programming and are essential to other courses in computer science. The course involves weekly programming assignments, in-class quizzes, discussion section exercises, and multiple exams.

This course introduces and develops methods for designing and implementing abstract data types using the Java programming language. The main focus is on how to build and encapsulate data objects and their associated operations. Specific topics include linked structures, recursive structures and algorithms, binary trees, balanced trees, and hash tables. These topics are fundamental to programming and are essential to other courses in computer science. The course involves weekly programming assignments, in-class quizzes, discussion section exercises, and multiple exams.

This course introduces and develops methods for designing and implementing abstract data types using the Java programming language. The main focus is on how to build and encapsulate data objects and their associated operations. Specific topics include linked structures, recursive structures and algorithms, binary trees, balanced trees, and hash tables. These topics are fundamental to programming and are essential to other courses in computer science. The course involves weekly programming assignments, in-class quizzes, discussion section exercises, and multiple exams.

Mathematical and algorithmic foundations of big data processing. Study of methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning. This course counts as a CS Elective for the CS Major (BS or BA).

Mathematical and algorithmic foundations of big data processing. Study of methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning. This course counts as a CS Elective for the CS Major (BS or BA).

Programming languages are fundamental to computer science and everyday programming. This course is an in-depth introduction to the formal, logical foundations of programming languages.

Introduces students to the principal activities involved in developing high-quality software systems, including recent state-of-the-art advances. Topics include: requirements analysis, formal specification methods, software design, testing, program analysis, and automated software engineering.

Introduces students to the principal activities involved in developing high-quality software systems, including recent state-of-the-art advances. Topics include: requirements analysis, formal specification methods, software design, testing, program analysis, and automated software engineering.

How computers work, including digital logic, arithmetic, data path, and memory. Students build circuits with prototyping boards; program microcontrollers in assembly language and C to work with various I/O devices.

Satisfies the Junior Year Writing requirement. The impact of computers on modern society.