InfoSci at College Park - Curriculum, Courses, Syllabi
The InfoSci degree requires a total of 120 credits, including 40 credits in General Education and 45 credits in the Information Science major. In addition to the ten core courses, 15 credits (five courses) of upper level major electives are required to complete the Information Science degree.
Enrolled Students: be sure to consult the Undergraduate Academic Policies, Forms, & Handbooks.
Benchmark courses are "indicator courses" that help advisors chart your progress in the major. Completing the benchmark courses on time, and with good grades, means you are making satisfactory progress through the major.
Failure to complete the benchmark courses with a C- or better within two attempts, will require you to change out of the the major. If you are having challenges in the benchmark courses it may be a sign that the major is not a good fit, and you should speak to an advisor.
Benchmark I (Must be completed within the first 30 credits after declaring the major).
- MATH 115 (or higher) - Precalculus (3 credits)
- PSYC 100 - Introduction to Psychology (3 credits)
Benchmark II (Must be completed within the first 60 credits after declaring the major).
- STAT 100 - Elementary Statistics and Probability (3 credits)
- INST 126 - Intro to Programming for Information Science (3 credits)
- INST 201 - Introduction to Information Science: Heroes and Villains in the Age of Information (3 credits)
The program requires ten courses of Core and five courses of upper level (300-400 level) Major Electives.
INST Core Courses
- INST 201 Introduction to Information Science: Heroes and Villains in the Age of Information
Examining the effects of new information technologies on how we conduct business, interact with friends, and go through our daily lives. Understanding how technical and social factors have influenced the evolution of information society. Evaluating the transformative power of information in education, policy, and entertainment, and the dark side of these changes..
- INST 311 Information Organization
Examines the theories, concepts, and principles of information, information representation and organization, record structures, description, and classification. Topics to be covered in this course include the methods and strategies to develop systems for storage, organization, and retrieval of information in a variety of organizational and institutional settings, as well as policy, ethical, and social implications of these systems.
- INST 314 Statistics for Information Science
Basic concepts in statistics including measure construction, data exploration, hypothesis development, hypothesis testing, pattern identification, and statistical analysis. The course also provides an overview of commonly used data manipulation and analytic tools. Through homework assignments, projects, and in-class activities, you will practice working with these techniques and tools to create information resources that can be used in individual and organizational decision-making and problem-solving.
- INST 326 Object-Oriented Programming for Information Science
An introduction to programming, emphasizing understanding and implementation of applications using object-oriented techniques. Topics to be covered include program design and testing as well as implementation of programs.
- INST 327 Database Design and Modeling
Introduction to databases, the relational model, entity-relationship diagrams, user-oriented database design and normalization, and Structured Query Language (SQL). Through labs, tests, and a project, students develop both theoretical and practical knowledge of relational database systems.
- INST 335 Teams and Organizations
Team development and the principles, methods and types of leadership will be a focus with an emphasis on goal setting, motivation, problem solving, and conflict resolution. This course examines the principles of managing team projects in organizations through planning and execution including estimating costs, managing risks, scheduling, staff and resource allocation, communication, tracking, and control.
- INST 346 Technologies, Infrastructures and Architecture
Examines the basic concepts of local and wide-area computer networking including an overview of services provided by networks, network topologies and hardware, packet switching, client/server architectures, network protocols, and network servers and applications. The principles and techniques of information organization and architecture for the Web environment will be covered along with such topics as management, security, authentication, and policy issues associated with distributed systems.
- INST 352 Information User Needs and Assessment
Focuses on use of information by individuals, including the theories, concepts, and principles of information, information behavior and mental models. Methods for determining information behavior and user needs, including accessibility issues will be examined and strategies for using information technology to support individual users and their specific needs will be explored.
- INST 362 User-Centered Design
Introduction to human-computer interaction (HCI), with a focus on how HCI connects psychology, information systems, computer science, and human factors. User-centered design and user interface implementation methods discussed include identifying user needs, understanding user behaviors, envisioning interfaces, and utilizing prototyping tools, with an emphasis on incorporating people in the design process from initial field observations to summative usability testing.
- INST 490 Integrative Capstone
The capstone provides a platform for Information Science students where they can apply a subset of the concepts, methods, and tools they learn as part of the Information Science program to addressing an information problem or fulfilling an information need.
Apply your Major Elective courses to the Cybersecurity and Privacy Specialization.
Students equip themselves with human-centered cybersecurity skills and perspectives, and prepare to launch careers in the cybersecurity field with particular emphasis on management, policy, and governance-related functions. (Beginning Fall 2019)
- Course information coming soon!
Apply your Major Elective courses to the Data Science Specialization. iFocus courses compliment this specialization.
Students develop understanding and skills for managing, manipulating, and mobilizing data to develop insight, create value, and achieve organizational goals in a wide range of sectors.
- INST 354 Decision-Making for Information Science
Examines the use of information in organizational and individual decision-making, including the roles of information professionals and information systems in informed decision-making through techniques such as data analysis and regression, optimization, sensitivity analysis, decision trees, risk analysis and business simulation models.
- INST 377 Dynamic Web Applications
An exploration of the basic methods and tools for developing dynamic, database-driven websites, including acquiring, installing, and running web servers, database servers, and connectability applications.
- INST 414 Advanced Data Science
An exploration of how to extract insights from large-scale datasets. The course will cover the complete analytical funnel from data extraction and cleaning to data analysis and insights interpretation and visualization. The data analysis component will focus on techniques in both supervised and unsupervised learning to extract information from datasets. Topics will include clustering, classification, and regression techniques. Through homework assignments, a project, exams and in-class activities, students will practice working with these techniques and tools to extract relevant information from structured and unstructured data.
- INST 447 Data Sources and Manipulation
Examines approaches to locating, acquiring, manipulating, and disseminating data. Imperfection, biases, and other problems in data are examined, and methods for identifying and correcting such problems are introduced. The course covers other topics such as automated collection of large data sets, and extracting, transforming, and reformatting a variety of data and file types.
- INST 462 Introduction to Data Visualization
Exploration of the theories, methods, and techniques of visualization of information, including the effects of human perception, the aesthetics of information design, the mechanics of visual display, and the semiotics of iconography.
iFocus areas complement the Data Science Specialization.
Apply your Major Elective courses to the Digital Curation Specialization.
With this specialization, students can launch careers in which they collect, digitize, appraise, curate, and disseminate information assets effectively and efficiently. (Beginning Fall 2019)
- Course information coming soon!
View the full iSchool undergraduate course catalog for detailed course descriptions, course and section numbers, instructors, and syllabi.
Recommended Python focus topics, books, and tutorials
Essential Python Topics
- Statements, variables, basic data types & operators
- Conditional statements
- Lists, dictionaries, tuples
- Input and output
- Reading and writing files
- Functions, libraries, modules
- Testing & debugging
- Python for Everybody - $10 print, free online
- Python Crash Course - $40 print, $32 ebook
- CS Principles: Big Ideas in Programming - free, with interactive examples
Online Python Courses and Tutorials
- Codecademy Python - free
- The Python Guru - free
- DataCamp Python Programming courses - Intro course free; others charged by the month
- Coursera - These can be audited for free. If you pay, you can get feedback and "grades":
Every student in the Information Science major must follow the policies of the program and college. If you have questions about a policy, please contact your advisor.
- Required Number of Credits:
InfoSci students are required to take 45 credits within the major. 30 credits of which must be approved major coursework with the INST prefix. Students must take 15 credits of approved upper-level [300-400 level] electives.
- Benchmark and Major courses:
Students who have declared InfoSci as their major, must take benchmark and InfoSci core courses at UMD.
- Benchmark Courses Taken Concurrently with Major Courses:
InfoSci students must successfully (C- or higher) complete all benchmark courses before taking InfoSci Core coursework. The College will allow InfoSci students to start taking InfoSci core courses in their last semester of benchmark coursework.
- Major Electives:
In order to apply non-INST UMD courses towards the InfoSci major elective requirements, students must take courses that are approved by the InfoSci program after declaring InfoSci as their major. Students must obtain approval for non-INST courses before enrolling in them in order for them to be counted as major electives.
- Declared InfoSci Students:
Students that declare InfoSci as their major must complete all benchmark courses prior to enrolling in major electives.
- Advanced Placement Credits:
Advanced Placement (AP) credits that have been accepted and transferred to UMD successfully may be used to satisfy corresponding InfoSci benchmark requirements.