Foundations Of Programming Object-oriented Design Torrents

This course takes you, step by step, through the principles and practices of object-oriented programming (OOP). The course provides you with the firm foundation in OOP that you need to progress to intermediate-level C# courses.

This course takes you through the principles and practices of object-oriented programming (OOP). The course provides you with the firm foundation in OOP that you need to progress to intermediate-level C# courses. It begins by showing you how to turn a set of words into a set of well-defined and related classes. Through demonstrations, it teaches you key object-oriented concepts such as abstraction, encapsulation, inheritance, polymorphism, and interfaces.

The 4 basics of OOP are encapsulation, abstraction, inheritance, and polymorphism. We will go over these in detail in the course, but for now, just know that these are what differentiates object-oriented programming from other types of programming.

This course is for anyone who wants to learn the fundamentals of object-oriented programming (OOP). Anyone who wants to better leverage the features of C# or other OOP languages should take this course.

Catalog Description: Self-paced introduction to the constructs provided in the C++ programming language for procedural and object-oriented programming, aimed at students who already know how to program. Units: 2

Catalog Description: Introduction to the constructs provided in the Python programming language, aimed at students who already know how to program. Flow of control; strings, tuples, lists, and dictionaries; CGI programming; file input and output; object-oriented programming; GUI elements. Units: 2

Catalog Description: An introductory course for students with minimal prior exposure to computer science. Prepares students for future computer science courses and empowers them to utilize programming to solve problems in their field of study. Presents an overview of the history, great principles, and transformative applications of computer science, as well as a comprehensive introduction to programming. Topics include abstraction, recursion, algorithmic complexity, higher-order functions, concurrency, social implications of computing (privacy, education, algorithmic bias), and engaging research areas (data science, AI, HCI). Students will program in Snap! (a friendly graphical language) and Python, and will design and implement two projects of their choice. Units: 4

Catalog Description: Implementation of generic operations. Streams and iterators. Implementation techniques for supporting functional, object-oriented, and constraint-based programming in the Scheme programming language. Together with 9D, 47A constitutes an abbreviated, self-paced version of 61A for students who have already taken a course equivalent to 61B. Units: 1

Catalog Description: An introduction to programming and computer science focused on abstraction techniques as means to manage program complexity. Techniques include procedural abstraction; control abstraction using recursion, higher-order functions, generators, and streams; data abstraction using interfaces, objects, classes, and generic operators; and language abstraction using interpreters and macros. The course exposes students to programming paradigms, including functional, object-oriented, and declarative approaches. It includes an introduction to asymptotic analysis of algorithms. There are several significant programming projects. Units: 4

Catalog Description: Introductory programming and computer science. Abstraction as means to control program complexity. Programming paradigms: functional, object-oriented, client/server, and declarative (logic). Control abstraction: recursion and higher order functions. Introduction to asymptotic analysis of algorithms. Data abstraction: abstract data types, type-tagged data, first class data types, sequences implemented as lists and as arrays, generic operators implemented with data-directed programming and with message passing. Implementation of object-oriented programming with closures over dispatch procedures. Introduction to interpreters and compilers. There are several significant programming projects. Course may be completed in one or two semesters. Students must complete a mimimum of two units during their first semester of 61AS. Units: 1-4

Catalog Description: Development of Computer Science topics appearing in Foundations of Data Science (C8); expands computational concepts and techniques of abstraction. Understanding the structures that underlie the programs, algorithms, and languages used in data science and elsewhere. Mastery of a particular programming language while studying general techniques for managing program complexity, e.g., functional, object-oriented, and declarative programming. Provides practical experience with composing larger systems through several significant programming projects. Units: 3

Catalog Description: Survey of programming languages. The design of modern programming languages. Principles and techniques of scanning, parsing, semantic analysis, and code generation. Implementation of compilers, interpreters, and assemblers. Overview of run-time organization and error handling. Units: 4

Catalog Description: Ideas and techniques for designing, developing, and modifying large software systems. Function-oriented and object-oriented modular design techniques, designing for re-use and maintainability. Specification and documentation. Verification and validation. Cost and quality metrics and estimation. Project team organization and management. Students will work in teams on a substantial programming project. Units: 4

Catalog Description: This course presents ideas and techniques for designing, developing, and modifying large software systems using Agile techniques and tools. Topics include: function-oriented and object-oriented modular design techniques, designing for re-use and maintainability including proper use of design patterns, behavior-driven design, test-driven development, user stories for requirements elicitation & documentation, verification and validation, cost and quality metrics and estimation, project team organization and management, analyzing and refactoring legacy code. Units: 3

Catalog Description: Cryptography or cryptology is the science of designing algorithms and protocols for enabling parties to communicate and compute securely in an untrusted environment (e.g. secure communication, digital signature, etc.) Over the last four decades, cryptography has transformed from an ad hoc collection of mysterious tricks into a rigorous science based on firm complexity-theoretic foundations. This modern complexity-theoretic approach to cryptography will be the focus. E.g., in the context of encryption we will begin by giving a precise mathematical definition for what it means to be a secure encryption scheme and then give a construction (realizing this security notion) assuming various computational hardness assumptions (e.g. factoring). Units: 4

Catalog Description: Access methods and file systems to facilitate data access. Hierarchical, network, relational, and object-oriented data models. Query languages for models. Embedding query languages in programming languages. Database services including protection, integrity control, and alternative views of data. High-level interfaces including application generators, browsers, and report writers. Introduction to transaction processing. Database system implementation to be done as term project. Units: 4

Catalog Description: Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression and classication (linear models, trees, neural networks, ensemble methods, instance-based methods); generative and discriminative probabilistic models; Bayesian parametric learning; density estimation and clustering; Bayesian networks; time series models; dimensionality reduction; programming projects covering a variety of real-world applications. Units: 4

Catalog Description: Software Development Methodologies, emphasizing the basic ideas and discipline of software engineering and their comparative evaluation. Rapid Prototyping, Software Reuse and Automated Generation of Software. Software Design Methods. Object-oriented design and programming. Testing and validation. Software Reliability theory. Software Metrics and models. Sofware Tools and their issues. Software maintenance. Application of AI techniques. Problem solving using rule-based inference techniques. Design of Intelligent Software Development Environment (ISDE). Distributed Software Engineering. Distributed Planning, cooperation among knowledge bases, Intelligent Planning, the Coop Project. Term project demos and discussions. Units: 3 2b1af7f3a8