Computer Information Systems: Beginning
10 courses · Mt. San Antonio College · 2026-2027 Catalog
Classes: Fall 2026 · Winter 2027
CISB 10 Office Skills
- Units
- 3
- Hours
- Lecture: 54
Skills necessary to work in an office setting including: alpha and numeric keyboarding, email etiquette and standards, electronic calendaring, ten-key, composing, formatting and storing business documents, and telephone techniques.
CISB 11 Computer Information Systems
- Units
- 3.5
- Hours
- Lecture: 54, Lab: 27
- Transfers to
- CSU, UC (credit limitation)
- C-ID
- BUS 140, ITIS 120
Overview of computer information systems including computer hardware, software, networking, programming, databases, Internet, security, systems analysis, ethics, and problem solving using business applications.
CISB 15 Microcomputer Applications
- Units
- 3.5
- Hours
- Lecture: 54, Lab: 27
- Transfers to
- CSU, UC
Windows operating system (OS) and applications, simple business examples using up-to-date browser, word processing, spreadsheet, database management and presentation software, and integration of software applications.
CISB 16 Macintosh Applications
- Units
- 2
- Hours
- Lecture: 27, Lab: 27
- Transfers to
- CSU
Macintosh operating system and related tools; creating files using office applications; storing and sharing files using iCloud.
CISB 21 Microsoft Excel
- Units
- 3
- Hours
- Lecture: 54
- Transfers to
- CSU
Spreadsheet concepts using Microsoft Excel including formatting, formulas and functions, charts, linked worksheets, pivot tables, business intelligence, macros, and Visual Basic for Applications (VBA) code.
CISB 31 Microsoft Word
- Units
- 3
- Hours
- Lecture: 54
Word processing with Microsoft Word and its editing, formatting, and language tools to create, edit, and format business and publication documents. Includes creating flyers, newsletters, and other publication documents using advanced formatting techniques and tools.
CISB 51 Microsoft PowerPoint
- Units
- 3
- Hours
- Lecture: 54
- Transfers to
- CSU
Using PowerPoint to plan, design, and produce effective presentations. Includes creating charts, diagrams, and storyboards; developing appropriate text content; and adding sound, animation, and movies.
CISB 60 Machine and Deep Learning in Business
- Units
- 3.5
- Hours
- Lecture: 54, Lab: 27
- Prerequisite
- CISD 41
- Advisory
- CISP 71
A broad introduction to machine learning and deep learning algorithms and their implementation to solve real-world business problems. Includes end-to-end process of investigating data through a machine learning lens and discuss how to extract and identify useful features that best represent your data and evaluate the performance of different machine learning algorithms. Topics include: supervised learning (linear regression, logistic regression, support vector machines, k-nearest neighbors, decision trees, random forest, and gradient boosted tree); unsupervised learning (clustering, dimensionality reduction, kernel methods). Covers building deep learning prediction models of different complexities, from simple linear logistic regression to major categories of neural networks including convolutional neural networks (CNNs). Is structured around special coding blueprint approaches no mathematical complexities. The major goal of the course is to gain an immense amount of valuable hands-on experience with real-world business challenges.
CISB 63 Generative Artificial Intelligence, Large Language Models, & Natural Language Processing in Business
- Units
- 3.5
- Hours
- Lecture: 54, Lab: 27
- Prerequisite
- CISD 41
This course is to unlock the power of generative AI (Artificial Intelligence) and transform your business strategy with our comprehensive course. Dive into essential principles and practical techniques for leveraging Large Language Models (LLMs) and Natural Language Processing (NLP) in a business context. This course provides a thorough exploration of: Text Processing Techniques (Master essential methods such as regular expressions, tokenization, text normalization, parts-of-speech tagging, and grammar parsing). Named Entity Recognition and Feature Engineering (Learn to extract key entities and engineer features using count vectors and TF-IDF (Term Frequency-Inverse Document Frequency). Text Analysis (Gain expertise in text cleaning, semantics, and sentiment analysis). Generative AI (Artificial Intelligence) Tools and Applications (Explore the latest advancements in generative AI, including creating AI-powered applications and chatbots using Python and relevant frameworks).
CISB 81 Work Experience in Office Technology
- Units
- 1-4
- Prerequisite
- Instructor approval and Compliance with Work Experience regulations as designated in the College Catalog.
Provides students with actual on-the-job experience in an approved worksite, which is related to classroom-based learning. A minimum of 54 clock hours per semester of supervised work is required for each one unit of credit. It is recommended that the hours per week be equally distributed throughout the semester. Work experience placement is not guaranteed, but assistance is provided.