Applied Informatics Minor

Overview for Applied Informatics Minor

Informatics studies the collection, storage, analysis, and presentation of digital information. Students analyze, integrate, and present information in ways that are meaningful to specific audiences. Skills developed in this minor include programming, statistical and other forms of data analysis, management and use of different types of data collections such as databases and XML files, and the application of mash-up tools to combine and present data in novel ways. The minor is for students outside the information technology major who wish to apply the tools of informatics to manage, process, and analyze data associated with their field of study or found in another domain.

The plan code for Applied Informatics Minor is APPINFO-MN.

Curriculum for 2023-2024 for Applied Informatics Minor

Current Students: See Curriculum Requirements

Required Courses
Introduction to Informatics
This course introduces students to the world of Informatics and provides them with tools to begin working as an informatician. Students learn the breadth of informatics and the roles informaticians play. Tools for working with XML and spreadsheets are presented. The course utilizes extensive hands-on computing, but no programming experience is necessary. (This class is restricted to non-computing majors. Students in GCCIS are not eligible to take this course.) Lec/Lab 2 (Fall).
Computational Problem Solving I
A first course in using the object-oriented approach to solve problems in the information domain. Students will learn to design software solutions using the object-oriented approach, to visually model systems using UML, to implement software solutions using a contemporary programming language, and to test these software solutions. Additional topics include thinking in object-oriented terms, and problem definition. Programming projects will be required. Lec/Lab 6 (Fall, Spring).
Introduction to Statistics I
This course introduces statistical methods of extracting meaning from data, and basic inferential statistics. Topics covered include data and data integrity, exploratory data analysis, data visualization, numeric summary measures, the normal distribution, sampling distributions, confidence intervals, and hypothesis testing. The emphasis of the course is on statistical thinking rather than computation. Statistical software is used. (Prerequisites: Any 100 level MATH course, or NMTH-260 or NMTH-272 or NMTH-275 or (NMTH-250 with a C- or better) or a Math Placement Exam score of at least 35.) Lecture 3 (Fall, Spring, Summer).
Introduction to Database and Data Modeling
A presentation of the fundamental concepts and theories used in organizing and structuring data. Coverage includes the data modeling process, basic relational model, normalization theory, relational algebra, and mapping a data model into a database schema. Structured Query Language is used to illustrate the translation of a data model to physical data organization. Modeling and programming assignments will be required. Note: students should have one course in object-oriented programming. (Prerequisites: ISTE-120 or ISTE-200 or IGME-101 or IGME-105 or CSCI-140 or CSCI-142 or NACA-161 or NMAD-180 or BIOL-135 or GCIS-123 or GCIS-127 or equivalent course.) Lec/Lab 3 (Fall, Spring).
Data Exploration and Knowledge Discovery
Rapidly expanding volumes of data from all areas of society are becoming available in digital form. High value information and knowledge is embedded in many of these data volumes. Unlocking this information can provide many benefits, and may also raise ethical questions in certain circumstances. This course provides students with a gentle, hands-on introduction to how interactive data exploration and data mining software can be used for data-driven knowledge discovery. Students will use statistical, visual, and data/text mining software systems to explore data collections from several different domains such as business, environmental management, healthcare, finance, and transportation. (Prerequisites: STAT-145 or equivalent course.) Lec/Lab 3 (Fall, Spring).
Integration in Informatics
This course is the capstone for the applied informatics minor. Students will use mashup tools along with their programming and database skills to develop a project, based on their major’s domain, which demonstrates the work of an informatician. The course utilizes extensive hands-on computing, including programming and database work. (This class is restricted to non-computing majors. Students in GCCIS are not eligible to take this course.) Lec/Lab 2 (Spring).