Computer Science
10 courses · Chaffey College · 2026-2027 Catalog
Classes: Summer 2026 · Fall 2026 · Spring 2027
COMPSCI 1 Programming Concepts and Methodology I (C++)
- Units
- 3
- Hours
- 48-54 Lecture
- Transfers to
- CSU, UC
- C-ID
- COMP 122
Introduces the discipline of computer science using a high level language, utilizing programming and practical hands-on problem solving. Topics include: hardware, software, computer architecture, memory and registers, input-output data operations, storage, information control, problem solving, and Object Oriented Programming. First course in a sequence of courses that is compliant with the standards of the Association for Computing Machinery (ACM). This course qualifies for the Computer Science & Cyber Security Pathways.
COMPSCI 2 Programming Concepts and Methodology II (C++)
- Units
- 3
- Hours
- 48-54 Lecture
- Prerequisite
- Completion with a C or better in: COMPSCI 1
- Transfers to
- CSU, UC
- C-ID
- COMP 132
Application of software engineering techniques to the design and development of large programs; data abstraction and structures and associated algorithms
COMPSCI 3 Computer Architecture and Organization
- Units
- 3
- Hours
- 48-54 Lecture
- Prerequisite
- Completion with a C or better in: COMPSCI 1 or COMPSCI 5 or ITIS 30
- Transfers to
- CSU, UC
- C-ID
- COMP 142
The organization and behavior of real computer systems at the assembly-language level. The mapping of statements and constructs in a high-level language onto sequences of machine instructions is studied, as well as the internal representation of simple data types and structures. Numerical computation is examined, noting the various data representation errors and potential procedural errors.
COMPSCI 4 Discrete Structures
- Units
- 3
- Hours
- 48-54 Lecture
- Prerequisite
- Completion with a C or better in: COMPSCI 1 or COMPSCI 5 or ITIS 30
- Transfers to
- CSU, UC
- C-ID
- COMP 152; MATH 160
Fundamental topics for Computer Science, such as logic, proof techniques, set theory, introduction to computer programming, basic counting rules, relations, functions and recursion, graphs and probability trees.
COMPSCI 5 Programming Concepts and Methodology I (Python)
- Units
- 3
- Hours
- 48-54 Lecture
- Transfers to
- CSU, UC
Beginning computer application design and construction concepts using Python programming language. Course includes fundamental concepts of control structures, data structures, and object-oriented programming.
COMPSCI 6 Programming Concepts and Methodology II (Python)
- Units
- 3
- Hours
- 48-54 Lecture
- Prerequisite
- Completion with a C or better in: COMPSCI 5
- Transfers to
- CSU, UC
- C-ID
- COMP 132
Application of software engineering techniques to the design and development of large programs; data abstraction and structures and associated algorithms using Python.
COMPSCI 10 Introduction to Data Science
- Units
- 3
- Hours
- 48-54 Lecture
- Transfers to
- CSU
Introduction to data science for students with little to no experience in the subject. Topics include foundational programming concepts, problem-solving strategies and code design, and data science concepts such as table operations, exploratory data analysis, and basic probability. Students explore the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction, and decision-making. The course focus is on transforming and analyzing data; machine learning methods, including regression, classification, and clustering; principles behind data visualizations; concepts of measurement error and prediction; and techniques for scalable data processing.
COMPSCI 11 Python Data Analytics
- Units
- 3
- Hours
- 48-54 Lecture
- Prerequisite
- Completion with a C or better in: COMPSCI 5
- Transfers to
- CSU
This course provides students with experience in using Python as a tool to import, explore, condition, and analyze data. Students will develop ways to find meaning in data using Python tools and modules such as NumPy, Matplotlib, and Pandas. Topics include: production of plots and models for decision-making, import and manipulation of databases, data visualization, selection and application of statistical analyses, machine learning, and predictive modeling.
COMPSCI 20 Big Data Analytics
- Units
- 3
- Hours
- 48-54 Lecture
- Prerequisite
- Completion with a C or better in: ITIS 80
Big data analytics describes the process of uncovering trends, patterns, and correlations in large amounts of raw data to help make data-informed decisions. It involves handling massive datasets and processes including data sourcing, storage, querying, analysis, visualization, and updating. Big data systems rely on data mining, distributed storage, resource management, query processing, and fault tolerance. Analytics techniques, including clustering and regression, help uncover patterns and correlations, driving data-informed decision-making.
COMPSCI 401 Introduction to Virtual and Augmented Reality
- Units
- 3
- Hours
- 48-54 Lecture
This course introduces students to Virtual Reality (VR) and Augmented Reality (AR). Included is a basic introduction to this technology through an overview and introduction of all types of extended reality (XR), history and development, uses and applications in business, education, healthcare, and other industries, the challenges of the medium, and the basic application development tools and hardware components necessary to build virtual environments. This course is designed for people who are new to VR as a medium.