2019 - 2020 Course Catalog

Data Analytics (AS)

60 Credits

This degree provides an introduction to data science by combining the tools of basic statistics, computer programming, and mathematical analysis with foundational concepts from a specific domain area. It will give students sufficient knowledge to enter the job market and to transfer credits to a baccalaureate program at a four-year institution.

Core Courses – 33-35 Credits

Completion of this degree is dependent upon a grade of C or higher in each of the following courses:

CSCI 1111Introduction to Programming in C

(4 cr)

CSCI 2001Computer Programming Concepts

(4 cr)

CSCI 2002Algorithms and Data Structures

(4 cr)

COMT 1181Database Management Systems

(3 cr)

DSCI 2000Introduction to Date Science

(3 cr)

Complete one of the following two courses:

MATH 1080Introduction to Statistics

(4 cr)

MATH 1090STATWAY Statistics 2

(4 cr)

Required

MATH 2080Statistical Modeling

(3 cr)

Complete two of the following Math courses grouped as follows:

MATH 1100College Algebra and Probability

(4 cr)

MATH 1400Survey of Calculus

(4 cr)

Or

MATH 1500Pre-Calculus

(5 cr)

MATH 1510Calculus 1

(5 cr)

Additional Required Courses – 25-27 Credits

ENGC 1101Freshman Composition

(4 cr)

Complete one of the following three courses:

COMM 1100Introduction to Human Communication

(3 cr)

COMM 1101Fundamentals of Public Speaking

(3 cr)

COMM 1111Interpersonal Communication

(3 cr)

Required

ECON 2201Principles of Microeconomics

(3 cr)

 

Complete a minimum of six additional credits from at least two of the following MnTC Goals: (6 Credits)

3, 6, 7, 8 or 10.

Complete additional courses to reach 60 college-level credits total (9-11 Credits)

Suggested courses for specialization areas are listed below.

Other Degree Requirements

  • Earn a minimum cumulative grade point average (GPA) of 2.0 for college-level coursework (courses numbered 1000 and above) completed at Normandale.
  • Earn a minimum of 20 college-level credits at Normandale.

Coursework in this degree program satisfies a portion of the Minnesota Transfer Curriculum (MnTC). Please see MnTC Degree Audit Report.

Sample Domain Specialization Areas for the AS in Data Analytics

Four-year data science programs and employers want students to be prepared to specialize in a chosen domain area. The domain specialties below represent a few possible areas of interest. Students should consult with faculty and advisors, including those at possible transfer institutions, for further information.

Bioinformatics:

BIOL 1501Principles of Biology I

(5 cr)

CHEM 1020Introductory Chemistry

(4 cr)

PHIL 1180Biomedical Ethics

(3 cr)

ENGC 2102Business and Technical Writing

(3 cr)

Finance:

ACCT 2251Financial Accounting

(4 cr)

ACCT 2254Introduction to Management Information Systems

(4 cr)

ECON 2202Principles of Macroeconomics

(3 cr)

PHIL 1170Business Ethics

(3 cr)

ENGC 2102Business and Technical Writing

(3 cr)

Law Enforcement/Government:

PSYC 1110Introduction to Psychology

(4 cr)

SOC 1106Social Problems in a Changing World

(3 cr)

SOC 2130Introduction to Criminal Justice

(3 cr)

POLS 1195Conflict and Negotiation

(3 cr)

ENGC 2102Business and Technical Writing

(3 cr)

CIM 1141Presentation Graphics 1

(1 cr)

Marketing:

BUSN 2254Introduction to Management Information Systems

(4 cr)

BUSN 2400Principles of Marketing

(3 cr)

ECON 2202Principles of Macroeconomics

(3 cr)

PHIL 1170Business Ethics

(3 cr)

ENGC 2102Business and Technical Writing

(3 cr)

CIM 1141Presentation Graphics 1

(1 cr)

Mathematics:

GEOG 1050Introduction to Maps and Places

(3 cr)

PHIL 1140Environmental Ethics

(3 cr)

Or

GEOG 1104Resources, Society and Environment

(3 cr)

MATH 1520Calculus 2

(5 cr)

MATH 2400Probability and Statistics with Calculus

(4 cr)

Others:

Students can also develop other domain specialization areas in consultation with their advisor and faculty.

Data Analytics