Image of hands on a computer keyboard 

Available starting January 1, 2020 

​Data scientists require knowledge in a variety of information technology sub-fields, including algorithms, data structures, programming languages and statistical methods.  While the field of Data Science is computer science centric, statistical and domain expertise is required.  Accordingly, the data scientist may specialize in various fields, including business, physics, biology, finance and economics.

The Data Science AS gives students the skills to analyze, procure, store and process large amounts of data.  The study of Data Science will have students dealing with data that comes from disparate sources in the modern context of the Internet, in various unstructured forms and across academic disciplines. 

The Data Science AS Degree will Transfer/Articulate to:

Metropolitan State University for a Data Science BS Degree, which can be completed through NHCC's University Center.


 

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2021 - 2022

  • Curriculum

    Program Courses
    CoursesTitlesCourse OutlinesGoal AreasCredits
    Course Subject: CSCI         Course Number:1040
    Course Title:Fundamentals of Structured Query Language (SQL)      Goal Areas:n/a      Credits:3

    Course Description:The goal of this course is to teach students how to design, build and use databases utilizing Microsoft SQL Server. The students will also learn to enter and retrieve information. They will learn SQL commands and query creation, including complex multi-table joins, and display and analyze query results. Students will design their own databases and deploy them on Microsoft SQL Server.Possessing skills in performing common Windows tasks working with applications, or taking CSci 1000, is highly recommended.
    		Fundamentals of Structured Query Language (SQL) andView-CSCI 1040n/a3
    Course Subject: CSCI         Course Number:1130
    Course Title:Introduction to Programming in Java (CS0)      Goal Areas:n/a      Credits:4

    Course Description:This course provides an introduction to the Java programming language and its foundational topics. In this course students will explore fundamental programming and computing concepts with a focus on problem solving, algorithm development and implementation. Topics included are: data types and memory concepts, arithmetic operators and mathematical expressions, conditional statements, repetition, arrays, methods and the basics of object-orientation.
    		Introduction to Programming in Java (CS0) andView-CSCI 1130n/a4
    Course Subject: CSCI         Course Number:2001
    Course Title:Object Oriented Programming (CS1)      Goal Areas:n/a      Credits:4

    Course Description:Students will learn object-oriented programming while creating algorithms.The basic principles of software engineering are emphasized. By doing their own Java projects, students will developproblem-solving skills and gain experience in detecting and correcting software errors.Procedures, recursion, and iteration will be presented in the development of algorithms. Inheritance and polymorphism are studied. The use of abstraction will be emphasized throughout the course.
    		Object Oriented Programming (CS1) andView-CSCI 2001n/a4
    Course Subject: CSCI         Course Number:2011
    Course Title:Programming in Python      Goal Areas:n/a      Credits:1

    Course Description:The course will introduce the Python Programming language in terms familiar to students experienced with writing simple, yet complete, programs in other languages. Additionally, the course will focus on utilities and features considered strengths in Python. This includes interfaces to specialized libraries and databases. Prerequisites: CSCI 1120 or CSCI 1130 or CSCI 1150 or CSCI 2001 or CSCI 2400
    		Programming in Python andView-CSCI 2011n/a1
    Course Subject: CSCI         Course Number:2030
    Course Title:Database Modeling and Design      Goal Areas:n/a      Credits:4

    Course Description:This course covers relational databases from conceptual design to implementation. The course will include logical and physical design, normalization, as well as the definition of tables and indexes. The use of Structured Query Language (SQL) for data retrieval and manipulation will be emphasized. Prerequisite: CSci 1040 and CSci 1120 or CSci 1130 or CSci 1150PLEASE NOTE: Students enrolled in CSCI 1040 can register for CSCI 2030 in anticipation of successful completion of CSCI 1040. Please contact Registration.
    		Database Modeling and Design andView-CSCI 2030n/a4
    Course Subject: DSCI         Course Number:2001
    Course Title:Data Science I      Goal Areas:n/a      Credits:4

    Course Description:This course introduces students to the rapidly growing field of Data Science. Students will learn the concepts and tools used to analyze data sets and make informed business and/or research decisions. Students will use various software, including databases, to gather, organize and visualize data for analysis.
    		Data Science I andView-DSCI 2001n/a4
    Course Subject: DSCI         Course Number:2002
    Course Title:Data Science II      Goal Areas:n/a      Credits:4

    Course Description:Provide students further exposure to the growing field of Data Science. Building upon the topics in Data Science I, students will learn about machine learning techniques, ways to deal with networked systems and extremely large data sets, and methods for improving the performance of computerized statistical models.
    		Data Science IIView-DSCI 2002n/a4
    and
    Course Subject: DSCI         Course Number:2009
    Course Title:Interdisciplinary Applications in Data Science      Goal Areas:n/a      Credits:2

    Course Description:This course provides a flexible in-depth review of interdisciplinary applications in Data Science. The curriculum has students independently explore and apply methods of Data Science in a real-world context related to their career interests.
    		Interdisciplinary Applications in Data ScienceView-DSCI 2009n/a2
     
    Program Electives
    CoursesTitlesCourse OutlinesGoal AreasCredits

    ​Program Electives - 4 Credits (1 course)

    Course Subject: CSCI         Course Number:1150
    Course Title:Programming in C# for .NET      Goal Areas:n/a      Credits:4

    Course Description:This course provides an introduction to object-oriented programming using the C# programming language. The majority of the course will be on the semantics of the C# language, a major component of Microsoft .NET development environment. Topics include: Visual Studio .NET integrated development environment, selected value and reference types, control structures, operators and expressions, methods, classes, and inheritance. Completion of this class will prepare the student for advanced topics in C#. Prerequisite: Math 1150 with a grade of C or better
    		Programming in C# for .NET orView-CSCI 1150n/a4
    Course Subject: CSCI         Course Number:1180
    Course Title:Introduction to Linux Operating System      Goal Areas:n/a      Credits:4

    Course Description:This course introduces Linux, a popular open-source operating system and a variety of Unix. Topics include installing and using Linux, the architecture of Linux, using the command-line shell, the file system, common utilities (including text editors), and the basics of shell scripting. Hands-on work with Linux is a central part of this class. Some experience in computer programming is recommended.
    		Introduction to Linux Operating System orView-CSCI 1180n/a4
    Course Subject: CSCI         Course Number:2002
    Course Title:Data Structures and Algorithms (CS2)      Goal Areas:n/a      Credits:4

    Course Description:This course continues using abstract data types and the concepts presented in CSci 2001 and introduces stacks, queues, linked lists, and trees. This course also covers advanced programming topics of recursion, sorting methods, and complexity measures. This is an object-oriented programming course.
    		Data Structures and Algorithms (CS2) orView-CSCI 2002n/a4
    Course Subject: CSCI         Course Number:2010
    Course Title:Discrete Mathematical Structures      Goal Areas:n/a      Credits:4

    Course Description:The course covers mathematical topics essential for work in computer science. Topics include: number bases, mathematical induction, sets, relations, functions, congruence, recursion, combinations and permutations, probability, graphs, trees, logic, Boolean algebra, and proof techniques. Computing related problems and examples are integrated throughout the course. Prerequisites: MATH 1150 College Algebra (Minimum grade: 1.67 GPA Equivalent) Or A score of 79 or higher on the College Level Math (0167) placement test Or An ACT math score of 26 or higher.Recommended: Any CSCI course numbered 1030 or above (Minimum grade: 1.67 GPA Equivalent)
    		Discrete Mathematical Structures orView-CSCI 2010n/a4
    Course Subject: MATH         Course Number:2000
    Course Title:Discrete Mathematical Structures      Goal Areas:n/a      Credits:4

    Course Description:The course covers mathematical topics essential for work in computer science. Topics include: number bases, mathematical induction, sets, relations, functions, congruence, recursion, combinations and permutations, probability, graphs, trees, logic, Boolean algebra, and proof techniques. Computing related problems and examples are integrated throughout the course. Prerequisites: MATH 1150 College Algebra (Minimum grade: 1.67 GPA Equivalent) Or A score of 79 or higher on the College Level Math (0167) placement test Or An ACT math score of 26 or higher
    		Discrete Mathematical StructuresView-MATH 2000n/a4
     
    General Education Courses
    CoursesTitlesCourse OutlinesGoal AreasCredits
    Course Subject: ENGL         Course Number:1200
    Course Title:Gateway College Writing      Goal Areas:n/a      Credits:4

    Course Description:This class provides extended practice in critical reading, writing, and thinking skills. Students will develop an effective writing process and work to achieve college-level competence in reading and responding to texts, visuals, events, and ideas in a variety of written formats, with an emphasis on the academic essay. Audience awareness, interpretation and analysis, logical reasoning, and persuasive and argumentative skills will be developed. MLA style documentation of primary sources will be included.
    		Gateway College Writing orView-ENGL 1200n/a4
    Course Subject: ENGL         Course Number:1201
    Course Title:College Writing I      Goal Areas:n/a      Credits:4

    Course Description:This class provides extended practice in critical reading, writing, and thinking skills. Students will develop an effective writing process and work to achieve college-level competence in reading and responding to texts, visuals, events, and ideas in a variety of written formats, with an emphasis on the academic essay. Audience awareness, interpretation and analysis, logical reasoning, and persuasive and argumentative skills will be developed. MLA style documentation of primary sources will be included.
    		College Writing I andView-ENGL 1201n/a4
    Course Subject: ENGL         Course Number:1202
    Course Title:College Writing II      Goal Areas:n/a      Credits:2

    Course Description:This class focuses on the research process, textual analysis of primary and secondary sources, rhetorical strategies for argument and persuasion, and successful integration of sources into a longer academic paper utilizing MLA (or other, as appropriate) documentation format. The class may be disciplinary, interdisciplinary, or topical in content, as noted on the class registration site.
    		College Writing II andView-ENGL 1202n/a2
    Course Subject: COMM         Course Number:1010
    Course Title:Fundamentals of Public Speaking      Goal Areas:n/a      Credits:3

    Course Description:This course provides instruction and practical experience in the basics of public speaking. This course has a performance component: students are expected to create and deliver informative, persuasive and other types of speeches.
    		Fundamentals of Public Speaking andView-COMM 1010n/a3
    Course Subject: ECON         Course Number:1060
    Course Title:Principles of Macroeconomics       Goal Areas:n/a      Credits:3

    Course Description:This course covers mainstream theories, the economy's recent performance, national income and output levels, money and the banking system, inflation and unemployment, fiscal and monetary policies, economic growth, and international trade.
    		Principles of Macroeconomics orView-ECON 1060n/a3
    Course Subject: ECON         Course Number:1070
    Course Title:Principles of Microeconomics      Goal Areas:n/a      Credits:3

    Course Description:This course covers theories of consumer and producer behavior as well as market structure, the role of government in the economy, distribution of income, externalities, and taxes.
    		Principles of Microeconomics andView-ECON 1070n/a3
    Course Subject: MATH         Course Number:1150
    Course Title:College Algebra      Goal Areas:n/a      Credits:3

    Course Description:This college-level course continues the study of algebra conducted in the developmental algebra courses. Topics include polynomial, rational, inverse, exponential, and logarithmic functions and their applications. Additional topics include systems of non-linear equations, systems of linear equations, and matrices. Prerequisites: College math placement level or successful completion of Math 0970 or 0980 with grade of C or better
    		College Algebra andView-MATH 1150n/a3
    Course Subject: MATH         Course Number:1210
    Course Title:Applied Statistics      Goal Areas:n/a      Credits:4

    Course Description:This course provides students with practical statistical tools for analyzing a variety of data. Students will learn how to choose which statistical test to implement, how to apply computer software to conduct tests, and how to interpret the statistical results. Topics include discussion of frequency distributions, measures of central tendency and variation, exploratory data analysis, probability, hypothesis testing and inferences about proportions and means (one and two populations), analysis of variance, correlation, linear regression, and nonparametric statistics. Prerequisites: College math placement above Math 1150 or successful completion of Math 1150 or higher with grade of C or better.
    		Applied StatisticsView-MATH 1210n/a4
     
    Natural Science - 1 lab course, 4 credits
    CoursesTitlesCourse OutlinesGoal AreasCredits

    ​ANTH1020(3), BIOL1000(4), BIOL1001(4), BIOL1002(4), BIOL1030(4), BIOL1101(4), BIOL1102(4), BIOL1120(3), BIOL1130(4), BIOL1140(4), BIOL1160(4), BIOL1200(4), BIOL1350(3), BIOL1360(4), BIOL1610(1), BIOL1650(1), BIOL2020(4), BIOL2030(4), BIOL2100(4), BIOL2111(4), BIOL2112(4), BIOL2360(4), CHEM1000(4), CHEM1010(4), CHEM1030(4), CHEM1061(4), CHEM1062(4), GEOG1010(3), GEOL1010(2), GEOL1020(2), GEOL1030(2), GEOL1040(2), GEOL1110(4), GEOL1120(4), GEOL1130(4), GEOL1150(4), GEOL1160(4), GEOL1850(3), GEOL1851(1), NSCI1000(4), NSCI1010(1), NSCI1020(1), NSCI1030(1), NSCI1050(4), NSCI1060(3), NSCI1061(1), NSCI1070(3), NSCI1071(1), NSCI1110(4), NSCI1120(4), PHYS1000(4), PHYS1030(4), PHYS1050(4), PHYS1060(3), PHYS1061(1), PHYS1070(3), PHYS1071(1), PHYS1120(4), PHYS1140(3), PHYS1201(5), PHYS1202(5), PHYS1231(4), PHYS1232(4), PHYS1400(3), PHYS1410(1), PHYS1450(3), PHYS1460(1), PHYS1601(5), PHYS1602(5)

     
    MnTC Electives
    CoursesTitlesCourse OutlinesGoal AreasCredits
    Electives from Goal Areas 6-10 (7 credits)
     
                                   Total Credits Required60

  • Program Outcomes

    ​Program outcomes:

    After successfully completing this program, a student will be able to:

    1. Empirically support business decisions and scientific research.
    2. Properly interpret and communicate statistical measures.
    3. Select relevant data for system development and analysis.
    4. Apply general analytical models to specialized areas in other disciplines.
    5. Derive meaning from data in relevant contexts.
    6. Properly assess and apply systems of algorithms, databases and third party
    software.
    7. Understand the role of networked systems and their topologies for data analysis.
    8. Determine appropriate resource allocations for solving data oriented problems.
    9. Explain how data is procured, stored and analyzed.
    10. Apply methods of data preparation such as parsing and normalization.
    11. Interpret statistical parameters for understanding data in context.
    12. Evaluate models of data analysis.
    13. Develop algorithmic solutions using appropriate programming structures.


  • Career Opportunities

    ​Information on careers, including salary and employment outlook data, is available on the iseek and Bureau of Labor Statistics websites: www.iseek.org and www.bls.gov.

  • Transfer Information

    ​If you are planning on transferring to another institution, follow the guidelines available on our transfer resources web page to help you plan the process: Transfer Information

  • Degree Information

    ​

    The Associate of Science (A.S.) degree is intended for students whose primary goal is to complete the credentials for a specific career and/or prepare for transfer to complete a bachelorandrsquo;s degree at a college or university with whom North Hennepin Community College has an articulation agreement. The A.S. degree provides a balance of general education courses and the required scientific, professional or technical courses in the degree program.

    A student shall:

    • Earn a minimum of 60 semester credits as required in the program, with a grade point average of 2.00 (C) or above in courses taken at North Hennepin Community College. Specific programs may have additional requirements or a higher minimum grade point average.
    • Earn a minimum of 15 semester credits at North Hennepin Community College. A student must complete at least 50% of career specific courses at North Hennepin Community College.
    • Earn 30 credits in at least 6 Minnesota Transfer Curriculum (MnTC) goal areas.
    • Earn 30 professional/technical credits.
    • Have four years to complete the graduation requirements as published in the catalog in effect at the time of their initial enrollment. Students taking more than four years to complete their graduation requirements may follow any catalog published during the fouryear period preceding their graduation.

    Completion of an A.S. degree fulfills the Goal Area 2 requirement of the Minnesota Transfer Curriculum (MnTC).

    Developmental Courses Some students may need preparatory course(s) in Math and/or English. Courses numbered below 1000 will not apply toward a degree.

    Equal Opportunity Employer and Disability Access Information North Hennepin Community College is a member of Minnesota State Colleges and Universities system and an equal opportunity employer and educator. This document is available in alternative formats to individuals with disabilities by calling 7634930555 or through the Minnesota Relay Service at 18006273529.


  • Accreditation

    North Hennepin Community College is accredited by the:
    Higher Learning Commission of the North Central Association of Colleges and Schools
    30 N. LaSalle Street, Suite 2400
    Chicago, IL 60602-2504
    1-800-621-7440