Course Description
Data Structures and Programming Methodology, COMPSCI 61BL
The same material as in 61B, but in a laboratory-based format.
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:
Unit Credit
UC Davis:
Unit Credit
UC Irvine:
Unit Credit
UC Los Angeles:
Unit Credit
UC Merced:
Unit Credit (see your Academic Advisor)
UC Riverside:
General Education: CS Elective Units
UC San Diego:
Course Equivalence: UCSD CSE 12
General Education: Seventh - 1 course towards Alternatives - Quantitative Reasoning; ERC 1 course formal skills; Muir: may petition as one course in a matching GE sequence in natural sciences; TMC 1 course toward lower division disciplinary breadth if noncontiguous to major;
UC San Francisco:
Unit Credit
UC Santa Barbara:
Unit Credit
UC Santa Cruz:
Unit Credit
Course Creators
John DeNero
John DeNero is an assistant teaching professor in the UC Berkeley EECS department. He joined the Cal faculty in 2014 to focus on undergraduate education in computer science and data science. He teaches and co-develops two of the largest courses on campus: introductory computer science for majors and introductory data science. He is the author of Composing Programs and co-author of Computational and Inferential Thinking, two online textbooks. He has received the Distinguished Teaching Award, the inaugural Giancarlo Teaching Fellowship, the Jim and Donna Gray Faculty Award for Undergraduate Teaching, and the Diane McEntyre Award for Excellence in Teaching. His research focuses both on natural language processing and computer science education. He received his Masters in Philosophy from Stanford University and his PhD in Electrical Engineering and Computer Science from UC Berkeley in 2010. Prior to becoming a professor, John was a senior research scientist at Google working primarily on Google Translate and natural language processing.
John DeNero is an assistant teaching professor in the UC Berkeley EECS department. He joined the Cal faculty in 2014 to focus on undergraduate education in computer science and data science. He teaches and co-develops two of the largest courses on campus: introductory computer science for majors and introductory data science. He is the author of Composing Programs and co-author of ...
John DeNero is an assistant teaching professor in the UC Berkeley EECS department. He joined the Cal faculty in 2014 to focus on undergraduate education in computer science and data science. He teaches and co-develops two of the largest courses on campus: introductory computer science for majors and introductory data science. He is the author of Composing Programs and co-author of Computational and Inferential Thinking, two online textbooks. He has received the Distinguished Teaching Award, the inaugural Giancarlo Teaching Fellowship, the Jim and Donna Gray Faculty Award for Undergraduate Teaching, and the Diane McEntyre Award for Excellence in Teaching. His research focuses both on natural language processing and computer science education. He received his Masters in Philosophy from Stanford University and his PhD in Electrical Engineering and Computer Science from UC Berkeley in 2010. Prior to becoming a professor, John was a senior research scientist at Google working primarily on Google Translate and natural language processing.
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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