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1 - 10 of 31 results for: CS 106B

BIOE 214: Representations and Algorithms for Computational Molecular Biology (BIOMEDIN 214, CS 274, GENE 214)

Topics: introduction to bioinformatics and computational biology, algorithms for alignment of biological sequences and structures, computing with strings, phylogenetic tree construction, hidden Markov models, basic structural computations on proteins, protein structure prediction, protein threading techniques, homology modeling, molecular dynamics and energy minimization, statistical analysis of 3D biological data, integration of data sources, knowledge representation and controlled terminologies for molecular biology, microarray analysis, machine learning (clustering and classification), and natural language text processing. Prerequisite: CS 106B; recommended: CS161; consent of instructor for 3 units.
Terms: Aut | Units: 3-4 | Grading: Medical Option (Med-Ltr-CR/NC)

BIOMEDIN 214: Representations and Algorithms for Computational Molecular Biology (BIOE 214, CS 274, GENE 214)

Topics: introduction to bioinformatics and computational biology, algorithms for alignment of biological sequences and structures, computing with strings, phylogenetic tree construction, hidden Markov models, basic structural computations on proteins, protein structure prediction, protein threading techniques, homology modeling, molecular dynamics and energy minimization, statistical analysis of 3D biological data, integration of data sources, knowledge representation and controlled terminologies for molecular biology, microarray analysis, machine learning (clustering and classification), and natural language text processing. Prerequisite: CS 106B; recommended: CS161; consent of instructor for 3 units.
Terms: Aut | Units: 3-4 | Grading: Medical Option (Med-Ltr-CR/NC)

COMM 113: Computational Methods in the Civic Sphere (COMM 213)

The widespread availability of public data provides a rich opportunity for those who can efficiently filter, interpret, and visualize information. Course develops necessary technical skills for data collection, analysis, and publication, including data mining and web visualization, with a focus on civic affairs and government accountability. Open to all majors and a range of technical skill levels. Involves tackling new tools and technical concepts in the pursuit of engaging, public-facing projects. (Graduate students enroll in 213). Prerequisite COMM 273D, CS 106A, or CS 106B.
Terms: Win | Units: 4-5 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)

COMM 213: Computational Methods in the Civic Sphere (COMM 113)

The widespread availability of public data provides a rich opportunity for those who can efficiently filter, interpret, and visualize information. Course develops necessary technical skills for data collection, analysis, and publication, including data mining and web visualization, with a focus on civic affairs and government accountability. Open to all majors and a range of technical skill levels. Involves tackling new tools and technical concepts in the pursuit of engaging, public-facing projects. (Graduate students enroll in 213). Prerequisite COMM 273D, CS 106A, or CS 106B.
Terms: Win | Units: 4-5 | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)

CS 9: Problem-Solving for the CS Technical Interview

This course will prepare students to interview for software engineering and related internships and full-time positions in industry. Drawing on multiple sources of actual interview questions, students will learn key problem-solving strategies specific to the technical/coding interview. Students will be encouraged to synthesize information they have learned across different courses in the major. Emphasis will be on the oral and combination written-oral modes of communication common in coding interviews, but which are unfamiliar settings for problem solving for many students. Prerequisites: CS 106B or X.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit

CS 41: Hap.py Code: The Python Programming Language

The fundamentals and contemporary usage of the Python programming language. Primary focus on developing best practices in writing Python and exploring the extensible and unique parts of Python that make it such a powerful language. Topics include: data structures (e.g. lists and dictionaries) and characteristic pythonic conventions such as anonymous functions, iterables, and powerful built-ins (e.g. map, filter, zip). We will also cover object-oriented design, the standard library, and common third-party packages (e.g. requests, pillow). Time permitting, we will explore modern Python-based web frameworks and project distribution. Prerequisite: 106B/X or equivalent. Application required.
Terms: not given this year | Units: 2 | Grading: Satisfactory/No Credit

CS 50: Using Tech for Good

Students in the class will work in small teams to implement high-impact projects for partner organizations. Taught by the CS+Social Good team, the aim of the class is to empower you to leverage technology for social good by inspiring action, facilitating collaboration, and forging pathways towards global change. Recommended: CS 106B, CS 42 or 142. Class is open to students of all years. May be repeated for credit. Cardinal Course certified by the Haas Center.
Terms: Aut, Spr | Units: 2 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: Cain, J. (PI)

CS 106B: Programming Abstractions (ENGR 70B)

Abstraction and its relation to programming. Software engineering principles of data abstraction and modularity. Object-oriented programming, fundamental data structures (such as stacks, queues, sets) and data-directed design. Recursion and recursive data structures (linked lists, trees, graphs). Introduction to time and space complexity analysis. Uses the programming language C++ covering its basic facilities. Prerequisite: 106A or equivalent. Summer quarter enrollment is limited.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR | Grading: Letter or Credit/No Credit

CS 106L: Standard C++ Programming Laboratory

Supplemental lab to 106B and 106X. Additional features of standard C++ programming practice. Possible topics include advanced C++ language features, standard libraries, STL containers and algorithms, object memory management, operator overloading, and inheritance. Prerequisite: consent of instructor. Corequisite: 106B or 106X.
Terms: Win | Units: 1 | Grading: Satisfactory/No Credit

CS 106S: Programming Abstractions and Social Good

Supplemental lab to CS 106B and CS 106X. Students will apply fundamental computer science concepts learned in 106B/X to problems in the social good space (such as health, government, education, and environment). Course consists of in-class activities designed by local tech companies and nonprofits. Corequisite: 106B or 106X.
Terms: Win | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Cain, J. (PI)
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