Data Analytics

Introduction to Computer Science and Problem Solving
Course Outline
Credits: 3
Provides an overview of computer science topics with an emphasis on problem-solving and algorithm development. This course is geared for students with no computer science or programming background and can serve as a solid foundation for further study in computer science. Algorithm development will be taught using pseudocode and diagrams. Computer programs will be written utilizing one or more computer languages. Topics to be included are computer architecture, networks, Boolean logic, and computer ethics.

Prerequisites:

• Please go to e-Services to see Pre-requisites for this course

Corequisites: None
Future Offering:

• Spring 2024

Computer Programming with Java
Course Outline
Credits: 4
Focuses on the use of the Java language to provide a comprehensive introduction to fundamental programming concepts for students interested in exploring computer programming. Program logic, algorithm design, object-oriented programming, and fundamental programming structures are emphasized. Course activities focus on the use of Java to design, code, debug, and test programs of moderate complexity. Gaining knowledge of these concepts and techniques will prepare the student to develop programs to solve real-life problems.

Prerequisites:

• MATH 1118 College Algebra I

Corequisites: None
Future Offering:

• Spring 2024

Course Outline
Credits: 4
Focuses on the use of the Python language to provide a comprehensive introduction to fundamental programming concepts for students interested in exploring computer programming. Program logic, algorithm design, object-oriented programming, and fundamental programming structures are emphasized. Course activities focus on the use of Python to design, code, debug, and test programs of moderate complexity. Gaining knowledge of these concepts and techniques will prepare the student to develop programs to solve real-life problems.

Prerequisites:

• Please go to e-Services to see Pre-requisites for this course

Corequisites: None
Future Offering:

• Spring 2024

Course Outline
Credits: 4
MNTC Goal Areas: 02, 04
Presents basic statistics which includes descriptive and graphical statistics, basic probability, probability distributions, sampling distributions, confidence intervals and hypotheses testing for one or two populations, linear regression, chi-square tests, and ANOVA. Professional statistical software, such as Minitab, will be integrated throughout the class. Graphing calculator required for the course. Recommendation based on the results of the Inver Hills Assessment Test or grade of "C" or higher in MATH 0820 or 0840 within the last 2 years.

Prerequisites:

• Please go to e-Services to see Pre-requisites for this course

Corequisites:

• MATH 0103 Statistics Support

Future Offering:

• Spring 2024
• Summer 2024

Course Outline
Credits: 4
Introduces software applications designed to increase personal and organizational productivity. Applications include Microsoft Office, including Word, Excel, and PowerPoint. Other topics include a survey of open-source content management systems, relational databases, web analytic tools, computer security, safety, ethics, and privacy concerns.

Prerequisites: None
Corequisites: None
Future Offering:

• Spring 2024
• Summer 2024

Course Outline
Credits: 4
Learn the technical and creative skills used by Business Analytics professionals. Develop the technical skills needed through hands-on experience and industry-leading, self-service business intelligence applications such as Alteryx and Tableau and understand and perform technical processes such as ETL (extract, transform, load). Students will complete a data visualization project.

Prerequisites:

• BUS 1100 Introduction to Business Applications and Computing

Corequisites: None
Future Offering:

• Spring 2024

Course Outline
Credits: 4
Builds upon BUS 2400 - Business Analytics I - to include advanced features of Tableau and Alteryx, with a focus on predictive models used to make more effective business decisions. Topics include classification, clustering, and time-series forecasting models, A/B testing, and visualizing public data sets. Final project will include a presentation of discoveries learned throughout the course.

Prerequisites:

• BUS 1100 Introduction to Business Applications and Computing
• BUS 2400 Business Analytics I

Corequisites: None
Future Offering:

• Summer 2024