BUS 386
Business Analytics

Course Description

This course will explore the basics of analyzing data sets for business decision-making. Students will learn to interpret data and make recommendations for several business categories. Topics such as data visualization, forecasting, trend analysis, pricing, and data clustering will be included.

Class Details

CRN Course Section Days Times Instructor Loc
28681 BUS 386 62Z Seats open No set days TBA-TBA John Francis ONLINE
No set days TBA-TBA TBA TBA
No set days TBA-TBA TBA

Class Dates: This class runs from 2026-09-21 to 2026-12-11.
Footnote:
BUS-386.-62Z: Fully ONLINE. This class mirrors the for-credit class of the same number (BUS 386 mirrors BUS 86), so the course description is the same. Non-credit courses are intended for students who want to gain general knowledge, learn a new skill, upgrade existing skills, or enrich their understanding of a wide range of topics. Non-credit courses cannot be used to earn an associate degree nor any college transcriptable certificates. They can, however, be used to earn non-transcriptable certificates of completion. This is an online class that does not have scheduled meetings and can be completed independently each week on the student's own time. Students must have access to a computer, the internet and an individual email address. Most De Anza classes will use the Canvas course management system. We recommend a laptop or desktop computer to successfully complete the course; a tablet or phone may not be adequate for all assignments and tests. Information about Canvas and Online Education Orientation can be found in Canvas on the Student Resources page: https://deanza.instructure.com/courses/3382. The Student Online Resources hub with extensive information and tips can be found at deanza.edu/online-ed/students/remotelearning.

Class Materials

View textbook and/or other materials at the Bookstore

Course Details

Units
0 Units
Hours
  • Weekly Lecture Hours: 5
  • Weekly Lab Hours: 0
Program Status
Program Applicable
Credit
Non-credit Class
Grading Method
  • Letter Grade
  • Pass/No Pass

Requisite and Advisory

Advisory
  • ESL 272 and ESL 273, or ESL 472 and ESL 473, or eligibility for ENGL C1000 or ENGL C1000H or ESL 5
  • Elementary algebra or equivalent (or higher), or appropriate placement beyond elementary algebra

Limitations on Enrollment and Entrance Skills

(No limit on student re-enrollment for 0 unit courses.)
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