# Data Analytics (AS) - 60 Credits

### Why Choose Data Analytics?

The demand for professionals in Data Analytics is on the rise while the supply remains low. This creates great job opportunities for individuals within this field. As the demand steadily increases and the supply remains low, data analytics professionals are being paid more and more. 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.

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:*

Code | Title | Credits |
---|---|---|

CSCI 1111 | Introduction to Programming in C | 4 |

CSCI 2001 | Computer Programming Concepts | 4 |

CSCI 2002 | Algorithms and Data Structures | 4 |

COMT 1181 | Database Management Systems | 3 |

DSCI 2000 | Introduction to Data Science | 3 |

MATH 2080 | Statistical Modeling | 3 |

### Complete one of the following courses:

Code | Title | Credits |
---|---|---|

MATH 1080 | Introduction to Statistics | 4 |

MATH 1090 | STATWAY Statistics 2 | 4 |

### Complete two of the following MATH courses grouped as follows:

Code | Title | Credits |
---|---|---|

MATH 1100 and | College Algebra and Probability | 4 |

MATH 1400 | Survey of Calculus | 4 |

or MATH 1500 | Pre-Calculus | 5 |

and MATH 1510 | Calculus 1 | 5 |

### Additional Required Courses - 25-27 credits

Code | Title | Credits |
---|---|---|

ENGC 1101 | Freshman Composition | 4 |

COMM 1100 | Introduction to Human Communication | 3 |

or COMM 1101 | Fundamentals of Public Speaking | 3 |

or COMM 1111 | Interpersonal Communication | 3 |

ECON 2201 | Principles of Microeconomics | 3 |

Completed a minimum of six additional credits from at least two of the following MnTC Goals: 3, 6, 7, 8 or 10.

Complete additional courses to reach 60 college-level credits total. Suggested courses fordomain specialization areas are listed below. (9-11 credits_

### Other Degree Requirements

- Complete additional courses to reach 60 credits total. Suggested courses for domain specialization areas are listed below.
- 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 A.S. 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 1501, CHEM 1020, PHIL 1180, ENGC 2102

**Finance**:

ACCT 2251, ACCT 2254, ECON 2202, PHIL 1170, ENGC 2102

**Law Enforcement/Government**:

PSYC 1110, SOC 1106, SOC 2130, POLS 1195, ENGC 2102, CIM 1141

**Marketing**:

BUSN 2254, BUSN 2400, ECON 2202, PHIL 1170, ENGC 2102, CIM 1141

**Mathematics: **

GEOG 1050, PHIL 1140, GEOG 1104, MATH 1520, MATH 2400

**Others: **

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