Course Description

Data Structures (Online), COMPSCI W61B

Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

Key Information

Credit: 6 quarter units / 4 semester units credit
UC Berkeley, Electrical Eng & Computer Sci

Course Credit:

Upon successful completion, all online courses offered through cross-enrollment provide UC unit credit. Some courses are approved for GE, major preparation and/or, major credit or can be used as a substitute for a course at your campus.
 
If "unit credit" is listed by your campus, consult your department, academic adviser or Student Affairs division to inquire about the petition process for more than unit credit for the course.

UC Berkeley:
Major Requirement: fulfills lower division requirement for CS & EECS Majors

UC Davis:
Unit Credit

UC Irvine:
Unit Credit

UC Los Angeles:
Unit Credit

UC Merced:
Course Equivalence: CS W61B at Berkeley is equivalent to CSE 030 at UC Merced

UC Riverside:
Course Equivalence: UCR CS 014 - Introduction to Data Structures and Algorithms

UC San Diego:
Course Equivalence: UCSD CSE 12
General Education: TMC 1 course toward lower division disciplinary breadth if noncontiguous to major; Warren - May be counted depending on major/PofC, Seventh - 1 course towards Alternatives - Quantitative Reasoning; ERC - 1 course formal skills 

UC San Francisco:
Unit Credit

UC Santa Barbara:
Unit Credit

UC Santa Cruz:
Unit Credit

More About The Course

Relevant Website

Course Creator

Joshua Hug
Josh Hug, Assistant Teaching Professor at UC Berkeley. Prior to that he was a lecturer at Princeton, where he taught data structures, introductory programming, and information security. He completed his PhD in EECS at UC Berkeley in 2011, and his work focused on reverse engineering of bacterial signal processing systems and bacterial decision making. During his foray into the strange world of computational biology, he discovered that teaching is the best possible job, and he is pleased to have returned to his computer science roots to teach. Before UC Berkeley, he was born, raised, and went to college in Texas where his emphasis was in computer architecture. Prior to his time in Texas he was a dispersion of random molecules, unassembled into any greater being.  Josh Hug, Assistant Teaching Professor at UC Berkeley. Prior to that he was a lecturer at Princeton, where he taught data structures, introductory programming, and information security. He completed his PhD in EECS at UC Berkeley in 2011, and his work focused on reverse engineering of bacterial signal processing systems and bacterial decision making. During his foray into the strange world of ...

Josh Hug, Assistant Teaching Professor at UC Berkeley. Prior to that he was a lecturer at Princeton, where he taught data structures, introductory programming, and information security. He completed his PhD in EECS at UC Berkeley in 2011, and his work focused on reverse engineering of bacterial signal processing systems and bacterial decision making. During his foray into the strange world of computational biology, he discovered that teaching is the best possible job, and he is pleased to have returned to his computer science roots to teach. Before UC Berkeley, he was born, raised, and went to college in Texas where his emphasis was in computer architecture. Prior to his time in Texas he was a dispersion of random molecules, unassembled into any greater being. 

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