Course Descriptions

Online Courses From the iSchool

Courses from the iSchool’s online programs are designed by our expert faculty with years of experience in the information and technology fields. All iSchool course descriptions are listed below along with business courses offered through the Martin J. Whitman School of Management.


IST 564: Accessible Library and Information Services

Preservice librarians will gain understanding of the various strategies for planning library programs and services inclusive of the informative needs of pre-K–12th-grade students with disabilities. The course offers context, awareness and strategies to develop programs and services, provide facilities and select resources and technologies that meet diverse needs and abilities of all patrons.

Learning Objectives

  • Use disability history and the social model of disability to advocate for and recommend change.
  • Use laws and standards to evaluate the accessibility of—and select resources for—library programs, policies and services.
  • Apply a social justice lens to designing and presenting a model library program, policy, service or resource.
  • Use the Universal Design for Learning (UDL) framework to create a model library program, policy, service or resource for diverse patrons.
  • Interact and communicate effectively with patrons regardless of their abilities.

Tools and Concepts

  • Library observation
  • Disability history
  • Social model
  • Assistive Technology (AT) recommendations
  • Library accessibility evaluations

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IST 769: Advanced Database Administration Concepts and Database Management (3 Credits)

This course provides an in-depth analysis of database management system architecture, building complex objects and applications using database forms and reports. Students learn about data warehousing, establishing and implementing database security, and tuning databases for optimum performance.

Upon completion of this course, students will achieve a deep technical knowledge and comprehension of database management systems, management of solution development and management of information technology. Oracle 10g and Developer Suite 10g will be used for assignments, lab exercises and course projects.

Learning Objectives

  • Achieve deep technical knowledge of database management systems.
  • Develop the ability to solve information problems at the individual and organizational levels.
  • Comprehend the disciplines used in the development of information system solutions.
  • Apply these disciplines to the solution of organizational and business problems.
  • Integrate the technical and solution development concepts with the principles of IT governance, strategic alignment, user behavior and financial analysis.
  • Apply these concepts to the analysis of complex management case studies and problems.
  • Analyze, compare, evaluate and clearly articulate the relative value of IT alternatives.

Tools and Concepts

  • Oracle 10g / Developer Suite 10g
  • Database management system architecture
  • Database security and optimization
  • Data storage on electromagnetic devices
  • Building applications using forms and reports
  • Building objects: abstract data types, functions, procedures, sequences, triggers and views

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IST 704: Applied Information Security

Applications of information security including hands-on experience. Students who successfully complete this course will understand how information security technology is applied to real systems.

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IST 718: Big Data Analytics

This course offers a broad introduction to analytical processing tools and techniques for information professionals. Students develop a portfolio of resources, demonstrations, recipes and examples of various analytical techniques while growing their specialization in one or more areas of interest.

Students will learn to obtain, screen, clean, link, manipulate, analyze and display data while creating summaries, overviews, models, analyses and basic tables, histograms, trees and scattergrams. They will use Python and Apache Spark to explore classic and modern machine learning techniques (such as deep learning) within a big data context, including sentiment analysis via supervised learning, recommendation systems via unsupervised learning and predicting credit scoring via random forest machine learning.

Learning Objectives

  • Understand complex data structures, transformation of data structures and manipulation of data elements.
  • Understand essential analysis techniques, including descriptive statistics, summarization and elementary modeling.
  • Understand scripting methods, including debugging methodologies, for handling data in R and other tools.
  • Appreciate the range of applicability of information analytics to real problems in areas such as business, science and engineering.
  • Develop ability to match available analytical methodologies to the information needs of clients and users and present results in a meaningful way.

Tools and Concepts

  • Machine learning
  • Python (Apache Spark, Hadoop 2.0, Spark ML, Pandas, Matplotlib)
  • Describing and modeling data sets
  • Volume and velocity of data
  • Data analytics and inferencing
  • Efficient debugging and problem solving

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IST 635: Collection Development and Access

Advanced investigation of collection building, acquisition and maintenance in libraries and information centers; user and collection analysis; collection development policies and guidelines, budgeting and licensing; evaluation and usage statistics; consortial collaboration; preservation; and ethical issues.

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IST 659: Data Administration Concepts and Database Administration

This course provides a foundation for database administration, exploring the fundamental models of database management systems. It covers the definition, development and management of databases for information systems.

Students learn data analysis techniques, data modeling, schema design, query languages and search specifications, including Structured Query Language (SQL), data structures, file organizations, principles of data management systems, and hierarchical, network and relational data models. Students gain hands-on experience using Microsoft’s Access and SQL Server database management systems (DBMS) as implementation vehicles.

This course provides hands-on experience in database design and implementation through assignments, lab exercises and course projects. This course also introduces advanced database concepts such as transaction management and concurrency control, distributed databases, multitier client/server architectures, web-based database applications, data warehousing and NoSQL.

Learning Objectives

  • Understand fundamental data and database concepts.
  • Explain and use the database development life cycle.
  • Solve problems by constructing database queries using SQL.
  • Design databases using data modeling and data normalization techniques.
  • Develop insights into future data management tools and technique trends.
  • Recommend and justify strategies for managing data security, privacy, audit/control, fraud detection, backup and recovery.
  • Critique the effectiveness of DBMS in computer information systems.

Tools and Concepts

  • SQL
  • Microsoft SQL Server
  • Microsoft Access
  • Visio
  • NoSQL
  • Data warehousing
  • Database design, management and implementation
  • Network and hierarchical data models
  • Multitier client/server architectures
  • Web-based database applications

Watch the Data Administration Concepts and Database Management Course Overview.

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IST 707: Data Analytics

This course introduces data mining techniques, real-world applications of those techniques and their challenges. Students learn popular data mining methods to gain insight from data and solve complex issues across industries.

Students also acquire hands-on experience using current software to develop data mining solutions to scientific and business problems. Topics include the key tasks of data mining. Through the exploration of the concepts and techniques of data mining and practical exercises, students will develop skills that can be applied to business, science or other organizational problems. Additionally, students will use R and other open source tools to perform machine learning across a range of situations when working with structured data (including clustering, classification, decision tree and association rules).

Learning Objectives

  • Document, analyze and translate data mining needs into technical designs and solutions.
  • Apply data mining concepts, algorithms and evaluation methods to real-world problems.
  • Employ data storytelling and dive into the data, find useful patterns, and articulate what patterns have been found, how they are found and why they are valuable and trustworthy.

Tools and Concepts

  • Machine learning
  • R and RStudio (arules, RWeka, class label, e1071, caret)
  • Data preparation
  • Concept description
  • Association rule mining
  • Classification and clustering
  • Evaluation and analysis

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IST 722: Data Warehouse

This course introduces the concepts of business intelligence (BI) and the practice/techniques in building a BI solution. Students focus on how to use data warehouses as a BI solution to make better organizational decisions. Topics include concepts, principles and tools for designing, and implementing data warehouses.

Students learn the differences between Ralph Kimball’s and Bill Inmon’s approaches, roles and responsibilities in the design and implementation of a data warehouse, project management guidelines and techniques, and requirements gathering. Coursework also covers dimensional modeling, Extract Transform and Load (ETL) architecture, specification and data loading, and master and reference data management, as well as integration approaches (ETL, EII, EAI), analytical reporting concepts, data governance and recent trends in the data warehouse domain.

Learning Objectives

  • Gain technical knowledge and comprehension about data warehouses.
  • Develop the ability to apply these technologies to solve information problems at the individual and organizational levels.
  • Comprehend the disciplines used in the development of data warehouse solutions.
  • Develop the ability to apply these disciplines in developing solutions for certain organizational and business problems.
  • Integrate technical and solution development concepts with the principles of data governance, strategic alignment and information analysis.
  • Apply these concepts in the analysis of complex management case studies and problems.

Tools and Concepts

  • SQL server tools: DBMS, SQL Server Integration Services (SSIS), SQL Server Analysis Service (SSAS), SQL Server Reporting Services (SSRS)
  • Project management and requirement gathering
  • Dimensional modeling and design
  • Technical architecture
  • ETL development with SSIS
  • Data governance and business intelligence
  • Big data in the data warehouse

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IST 625: Enterprise Risk Management

This course offers students a multidisciplinary perspective of risk assessment, modeling and management. Topics include concepts of personal accountability versus governance and policy, how organizations define and measure risk and loss, and plans for contingencies.

In this course, students look at the entire enterprise risk management (ERM) cycle,

including how we structure to involve the right people, how we identify our risks, how we measure them, and how we mitigate, share or transfer them.  Rather than focusing on standard IT security protocols and technologies or particular software tools, this course aims to highlight frameworks, issues and best practices. The goal is to assist information professionals and other professionals in helping support how their organizations holistically plan, assess, measure and manage enterprise risk.

Learning Objectives

  • Learn and apply the common risk management vocabulary so that you may more effectively participate in discussions about enterprise-wide risk management.
  • Look holistically at risks that could affect the survival and resiliency of the entire organization.
  • Evaluate ERM in context of both upside (positive) and downside (negative) risk.
  • Study and analyze issues at all phases of the multistage enterprise risk process, beginning with the organizational “risk culture” and “risk infrastructure.”

Tools and Concepts

  • Enterprise risk management (ERM) program
  • Contingency planning and disaster recovery (CP/DR) activities
  • Risk categories, measurement and management

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IST 621: Information Management and Technology

This course is designed to help the student become aware of what happens when digital transformation and the organization collide, and how IT managers can create organizational, technological and personal capabilities to succeed in a rapidly changing digital world. Students learn the foundation of general management concepts, information management implementation concerns and strategies, and information life cycle management as it relates to a career in the field.

Learning Objectives

  • Learn a number of models for diagnosing and implementing change situations that should prove valuable in work situations.
  • Communicate how technology and organizations adapt to each other when facing rapid digital transformation.
  • Identify and discuss key concepts and theories relating to information, change and digital transformation.
  • Apply models to diagnose and solve digital transformation problems.
  • Ethically apply skills associated with different types of information and change management.

Tools and Concepts

  • IT-enabled digital transformation
  • Diagnostics/analysis/contextual knowledge
  • Change agents

Watch the Information Management and Technology Course Overview.

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IST 618: Information Policy

Throughout the course, students will explore public policy issues that affect the information, library and telecommunication sectors. Discussion also will include the application of economic, legal and political sciences concepts to policy analysis. This course will widen students’ views of information and communication technologies (ICTs) by adding a new perspective based on the societal and policy factors that influence decisions.

Learning Objectives

  • Analyze and critique basic public policy issues of the digital economy.
  • Apply key concepts from economics, law and political science.
  • Recognize the reasons, circumstances and factors leading to government intervention.
  • Discern and research emerging information policy issues and effects on organizations.
  • Advocate for and implement sensible and ethical information and technology policy.

Tools and Concepts

  • Intellectual property
  • Economic regulation
  • Access and affordability
  • Privacy and security
  • Public-sector information policy
  • Internet governance
  • Sources policy-related information

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IST 719: Information Visualization

This course is a broad introduction to data visualization for information professionals through demonstrations, recipes and examples of various data visualization techniques. Students are introduced to the programming language R, Adobe Illustrator, simple data cleaning techniques, simple design concepts and the ethics of visualizing data. The focus is on developing static data visualizations to visually explore and communicate findings using data from a variety of sources. Conceptual themes are presented alongside technical aspects of data visualization.

Learning Objectives

  • Use R to do basic data cleaning and preparation on a wide range of data sets.
  • Identify stories in data sets through exploration using R to create appropriate rough plots to identify distributions and relationships in the data.
  • Create rich visual artifacts that communicate data stories, including identifying the optimal type of visualization to minimize viewer cognitive overload and maximize image interpretability.
  • Use basic design principles to enhance viewer receptivity and convey meaning, and use Adobe Illustrator to combine R data visualizations.
  • Critically assess visualizations, including interpreting and analyzing the meanings of data visualizations.
  • Identify appropriate audiences, bringing an ethics-based perspective to the development and interpretation of visualizations.

Tools and Concepts

  • R
  • Python / BeautifulSoup, plotrix, igraph, maps, rworldmap, ggplot2, lubridate, wordcloud2, RColorBrewer, png and rgl
  • Adobe Illustrator

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IST 611: Information Technologies in Educational Organizations

In this interdisciplinary survey course, students will study issues related to information technologies used in educational settings, gaining experience with various technologies relevant to educational contexts.

Emphasis is balanced between knowledge regarding information technologies and appropriate use of these technologies for achieving pedagogical goals in a range of settings. Students will be introduced to a variety of technologies used in education and training, as well as opportunities to work both independently and collaboratively.

Learning Objectives

  • Demonstrate knowledge of technological impact on information services and instruction for diverse learning audiences.
  • Increase competence in using a number of existing and emerging technologies for educational use.
  • Generate teaching ideas for promoting digital citizenship, social responsibility and internet safety.
  • Ability to discuss specific legislation and its effect on school libraries and librarians.

Tools and Concepts

  • Information and communications technologies
  • Ethical issues
  • Knowledge management tools
  • Collaborative learning technologies
  • Education databases
  • On-site project fieldwork

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IST 687: Introduction to Data Science

The course provides students a hands-on introduction to data science, with applied examples of data collection, processing, transformation, management and analysis. Students will explore key concepts related to data science, including applied statistics, information visualization, text mining and machine learning. R, the open source statistical analysis and visualization system, will be used throughout the course. R is reckoned by many to be the most popular choice among data analysts worldwide; having knowledge and skill with using it is considered a valuable and marketable job skill for most data scientists.

Students will also learn how to use supervised and unsupervised machine learning techniques. They will focus on structured data, using R (e.g., support vector machines, association rules mining) in conjunction with learning the full life cycle of data science.

Learning Objectives

  • Understand essential concepts and characteristics of data.
  • Perform basic computational scripting using R and other optional tools.
  • Apply scripting/code development for data management using R and RStudio.
  • Comprehend principles and practices in data screening, cleaning and linking.
  • Communicate results to decision makers.

Tools and Concepts

  • Coding with R
  • Applied statistics
  • Data mapping
  • Linear modeling
  • Information visualization
  • Text mining
  • Machine learning

Watch the Introduction to Data Science Course Overview.

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IST 623: Introduction to Information Security

This course is intended to teach fundamental elements in information security and introduce the key areas of security challenges, countermeasures and applications. The course will focus on a comprehensive understanding of information security rather than an in-depth analysis of a particular area.

Topics include security properties, vulnerabilities, cryptography, public key infrastructure (PKI), security policies, authentication, access control, security protocols, network security, cyberattacks and security management. Students will also have research opportunities and hands-on experiences in information security. Students who successfully complete this course have a comprehensive overview of information security with some hands-on experience.

Learning Objectives

  • Explain the fundamental elements in information security.
  • Obtain in-depth security knowledge and skills in the research areas selected.
  • Demonstrate the hands-on ability to analyze security properties using various security services and tools.
  • Develop expertise in a specific area of information security in further study, extending the contents learned from the course.

Tools and Concepts

  • Security policies
  • Security models (access control models, BLP rules, RBAC concepts)
  • Secret and public key cryptography
  • Internet security protocols (SSL/TLS, IP tunneling, IPsec)
  • Security in wireless networks
  • Firewalls

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IST 511: Introduction to the Library and Information Profession

This course provides an introductory look into the principles, values and practices that are the foundation of the profession. Students will explore the rapidly evolving librarianship field and be introduced to established structures and practices as well as future directions of the field. The course also focuses on the professional, social, ethical and legal issues that affect information service professionals and organizations.

Learning Objectives

Apply leadership skills of visioning, entrepreneurship, advocacy, planning and management.

  • Manage information resources and the information life cycle.
  • Apply appropriate pedagogical and learning theories.
  • Design and employ policies essential for information services and resources.
  • Collaborate with a diverse community to advocate for and construct inclusive, meaningful and participatory library services, programs and resources.
  • Perform and assess research-based applied practices.

Tools and Concepts

  • Library catalog, print resources and commercial databases
  • Oral and written communication methods
  • Library and information science vocabulary
  • Process of professional networking
  • Issues and goals of different library types

Watch the Introduction to the Library and Information Profession Course Overview.

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IST 616: Information Resources: Organization and Access

This course is an introductory survey of principles, techniques and standards used in information systems to represent and organize information, especially those implemented in libraries and information centers. Students will explore the fundamental concepts of theory and practice in information organization, storage and retrieval, including an introduction to existing systems and standards. Topics are covered at the introductory level with the expectation that students wishing to pursue any specific areas will assume further coursework.

Learning Objectives

  • Identify how organized information affects information search and retrieval.
  • Organize and describe the concepts, principles, standards and technologies of information organization.
  • Understand the nature of information-based problems and how information systems address these problems.
  • Analyze and interpret the human aspects and trends in information organization.

Tools and Concepts

  • Basic description of information resources
  • Standards for bibliographic/metadata data encoding
  • Knowledge organization structures (LCSH, LCC, and Dewey)
  • Indexing and classifying information
  • Characteristics of presently available systems

Watch the Information Resources: Organization and Access Course Overview.

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IST 654: Information Systems Analysis

This course focuses on automated tools and technologies and methods of systems analysis through decomposition and modeling. Students practice project management and systems analysis techniques as well as structured methodologies.

Students eventually apply what they learn to a final group project. In this course, students will cover the concepts and techniques of information systems analysis and design (SA&D), including analysis skills as well as managerial issues. The course covers techniques used by modern systems analysts and gives extensive practice with structured methodologies and object-oriented techniques.

Learning Objectives

  • Define various systems analysis and design concepts and terminologies.
  • Describe the stages of the system development life cycle model.
  • Describe different methodologies and state-of-the-art developments in SA&D techniques and methods.
  • Compare, use and synthesize different conceptual modeling techniques for systems analysis.
  • Apply logic modeling techniques.
  • Address the managerial issues and model the importance of collaboration/communication involved in SA&D.

Tools and Concepts

  • SA&D
  • Entity relation diagrams (ERDs)
  • Data flow diagrams (DFDs)
  • Unified Modeling Language (UML)

Watch the Information Systems Analysis Course Overview.

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IST 662: Instructional Strategies and Techniques for Information Professionals

Students are introduced to information literacy models for application to instruction in information organizations. This course focuses on strategies and techniques for designing, presenting and evaluating information technology training and training materials for real clients.

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IST 971: Internship — Information Management

Students are required to participate in a fully supervised internship experience. Credits for the internship vary, and students work with an academic advisor to determine the number of credits that apply to an internship. Students can take a maximum of six credits, and waivers are available.

Guidelines for Credit Reductions and Substitutions: Students with one to three years of full-time professional experience in the information technology field may substitute the internship requirement for another three-credit course.

Students with a minimum of three years of full-time professional experience in the information technology field may reduce the credit requirement of the program by three credits, substituted by work experience.

Students with a minimum of six years of full-time professional experience in the information technology field may reduce the credit requirement of the program by six credits, substituted by work experience.

Students with a minimum of six years of full-time professional experience in the information technology field may reduce the credit requirement of the program by six credits, substituted by work experience.

For all credit reductions and substitutions, your resume is required, and we may request joining-leaving letters that may be audited.

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IST 973: Internship – Library and Information Science

Students are required to participate in a fully supervised internship experience. Credits for the internship vary, and students will work with an academic advisor to determine the number of credits an internship entails. Students can take a maximum of six credits (minimum three credits).

Independent Readings and Research

Students who already possess significant professional work experience in libraries or information centers may petition to waive the internship and substitute it with an additional elective.

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IST 613: Library Planning, Marketing, and Assessment

This course is a user-focused approach to planning, marketing and assessing activities that support core library functions, including collection development, systems and public services. Students will focus on how libraries create and deliver value to users and stakeholders, as well as the institutions, organizations or communities of which they are a part.

To provide an effective return on investment, librarians must determine the degree to which their services, expertise and resources contribute to the ability of their institutions, organizations or communities to meet their missions and fulfill their purposes.

This course requires you to work in close collaboration with an approved partner library and librarian. You may select any type of library—school, public, academic, special—providing there is at least one certified librarian who agrees to work with you.

Learning Objectives

  • Apply leadership skills and attitudes of visioning, entrepreneurship, advocacy, planning and management.
  • Possess the skills to respect, engage and collaborate with a diverse community.
  • Perform and assess research-based practices that information literacy, inquiry and research methods.

Tools and Concepts

  • Communication and collaboration
  • Purpose and mission of library communities
  • Assessment of existing library services
  • Increasing value of library services
  • Creation of supporting literature reviews
  • Project management processes, tools and strategies
  • Communication/marketing messages
  • Assessment questions, methods and analysis strategies

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IST 636: Leading Issues in Information Security

This course is intended to cover today’s leading issues and challenges in information security, considering social, ethical, management and global perspectives that are related to current technology trends.

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IST 668: Literacy Through School Libraries

This course focuses on the role that librarians play in the development of literacy in children and young adults. Literacy is defined broadly to encompass all types of literacy, including visual, media, information, digital and technological. Students will learn skills to aid young learners in developing the motivation and skills to confront the unique challenges posed by various formats of literacy.

Learning Objectives

  • Define literacy as a product of motivation and making meaning.
  • Develop literacy lessons to teach crucial skills for making meaning from text.
  • Develop library programs, services and instruction to foster the specialized critical thinking skills necessary for different types of literacy.
  • Considering individual student needs when planning literacy activities and instruction.
  • Plan strategies to empower students’ voices.
  • Develop a plan for schoolwide literacy integration.

Tools and Concepts

  • Ecosystem of literacy
  • Transactional reading
  • Academic vs. independent reading
  • Role of teachers of literacy
  • Literary lesson template
  • Importance of visual literacy

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IST 645: Managing Information Systems Projects

This course is an introduction to roles, activities, methods and tools that are common in information systems projects. Students in this course gain insight into project management as a professional discipline in information and communication technology (ICT). Technical and behavioral aspects of project management are discussed.

Major topics include managing project adoption issues such as selection and approval of projects; cost-benefit analysis and requirements analysis; planning for systems development and estimation; scheduling and implementation issues such as project organization, implementation and control; and project closure.

Learning Objectives

  • Enable students to understand issues in the management or development of real-world information and telecommunications systems.
  • Develop project management skills and experience that will be directly transferable.
  • Explain how project managers are credentialed by professional organizations.
  • Articulate the sequence of activities in a typical ICT project.
  • Explain the nature of the deliverables that are typical outcomes of project activities.
  • Describe stages in the life cycle of an ICT product or service.
  • Use project management methods and tools to deliver written work.
  • Explain how application of the methods and concepts of project management may vary, depending on contextual factors.

Tools and Concepts

  • Project Management Body of Knowledge (as articulated by the Project Management Institute)
  • ICT project
  • Cost-benefit analysis
  • Information systems

Watch the Managing Information Systems Projects Course Overview.

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IST 614: Management Principles for Information Professionals

Students are introduced to the profession and practice of information field management. The course is designed to illustrate common management themes in organizational contexts, lending a better understanding to issues, principles and techniques of practicing managers. Students will become prepared to understand and apply both the basic theoretical principles of organization theory and practical managerial techniques.

Learning Objectives

  • Explain the four functions of management.
  • Describe the roles and responsibilities of different types of managers.
  • Understand the historic development of management theories.

Tools and Concepts

  • Effective leadership communication
  • Sustainable competitive advantage
  • Corporate-, industry-, and organization-level strategies
  • SWOT and five-forces analyses
  • Financial implications of strategic alternatives
  • Rational scoring models
  • Structural design of organizations
  • Management practices of global and organizational cultures
  • Recruitment, selection and retention techniques

Watch the Management Principles for Information Professionals Course Overview.

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IST 661: Managing a School Library

This course prepares information professionals for work in school libraries by teaching students to administer school library resources and services; enhance teaching and student achievement; identify services and resources that support the curriculum, teaching and student achievement; and link to the larger learning community and become a visionary leader. Additionally, students will learn to oversee programming that fosters and motivates student inquiry and reading enrichment.

Learning Objectives

  • Apply the skills and attitudes of visioning, entrepreneurship, advocacy, planning and management.
  • Manage information resources and the information life cycle.
  • Apply appropriate legal pedagogical and learning theory principles.
  • Strengthen skills to respect, engage and collaborate with a diverse community.
  • Perform and assess research-based practices.

Tools and Concepts

  • Student-centered school library programs
  • Cultural responsiveness and agency
  • Collection development approaches
  • Grant proposals
  • Independent reading initiatives
  • Curriculum integration and teacher collaboration
  • Library media center management

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IST 663: Motivating 21st-Century Learning

This course focuses on the instructional design and teaching role of the librarian with specific emphasis on the pre-K to 12th-grade educational context—although the concepts, principles and skills are applicable for learners from toddlers to senior citizens. Students will explore the motivation, learning theory, inquiry, assessment, lesson planning and teaching techniques essential to learner success. Assignments are designed to give students authentic experiences in both lesson design and implementation.

Learning Objectives

  • Apply visioning, entrepreneurship, advocacy, planning and management to leadership positions.
  • Manage information resources and the information life cycle through prescribed processes and dissemination.
  • Apply appropriate pedagogical and learning theory principles in the design, development, implementation and assessment of library instruction and learning.
  • Design and employ policies essential for creating and providing information services and resources.
  • Enhance skills in respecting, engaging and collaborating with a diverse community.
  • Perform and assess research-based practices through the application of information literacy, inquiry and research methods.

Tools and Concepts

  • Inquiry-based learning experiences
  • Facilitating student motivation
  • National and state standards
  • Cross-curriculum instruction
  • Instructional leadership and collaboration

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IST 664: Natural Language Processing

This course focuses on the linguistic and computational aspects of natural language processing (NLP) technologies. Students develop an understanding of how NLP can process written text and produce a linguistic analysis that can be used in other applications. Discussions cover the multiple levels of linguistic analysis required for a computer to accept natural language input, interpret it and carry out a particular application. Topics include levels of linguistic analysis with a focus on techniques in application.

Students in this course will explore all the levels of linguistic analysis, going from tokenization, word-level semantics, part-of-speech tagging, syntax and semantics up to the discourse level. They will also use NLP techniques on unstructured data using Python, including information retrieval, question-answering, sentiment analysis, summarization and dialogue systems.

Learning Objectives

  • Demonstrate the levels of linguistic analysis and computational techniques used to understand text at each level and what the challenges are for those techniques.
  • Process text through the language levels using the resources of the Natural Language Toolkit (NLTK) and some rudimentary use of the programming language Python.
  • Describe how NLP is used in real-world applications.

Tools and Concepts

  • Machine learning
  • Python / NLTK
  • Linguistic analysis
  • Tokenization
  • Word-level semantics
  • Part-of-speech tagging, syntax and discourse
  • Sentiment analysis and summarization
  • Dialogue systems

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IST 772: Quantitative Reasoning

Multiple strategies for inferential reasoning about quantitative data. Methods for connecting data provenance to substantive analytical conclusions.

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IST 605: Reference and Information Literacy Services

Reference and information literacy services are core to all forms of librarianship, taking center stage in academic, public, school and special libraries. This course focuses on the use of information resources and provision in libraries, assuming an integrated approach that broadly combines print and electronic resources and services. Students will be introduced to the essential ethics, techniques and tools related to communicating with and teaching users.

The course includes 10 hours of observing/shadowing a librarian (or librarians) with an MLS-equivalent degree or certification, as well as interviewing the librarian(s). Half of these hours will occur at a physical or virtual reference desk, while the remaining hours may include observing instruction sessions or daily tasks.

Learning Objectives

  • Perform and assess research-based practices through the application of information literacy, inquiry and research methods.
  • Appropriately apply pedagogical and learning theory principles in the design, development, implementation and assessment of library instruction and learning.

Tools and Concepts

  • Reference and information literacy services
  • Personal/professional philosophy
  • Professional ethics and communication
  • Standard reference resources
  • User information needs
  • Audience-accessible language for user reference query
  • Information literacy definitions

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IST 652: Scripting for Data Analysis

This course explores scripting for the data science pipeline. Students learn to acquire, access and transform different forms of data, including structured, semi-structured and unstructured data.

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IST 755: Strategic Management of Information Resources

Students integrate and apply the knowledge they have gained to case studies, projects and other high-level assignments, allowing them to draw from their previous courses on critical information resource management areas.

The objective of this course is to apply and expand on what students have learned throughout their master’s program and work experiences to better understand the challenges of strategic management of information resources. We use texts, articles, frameworks, discussions and other online sources to provide material on strategic management concepts, their application to information resources and the national and global contexts in which organizations operate. We also will examine and discuss particularly important current and emerging issues that are critical to the management of information resources in large, complex organizations.

Learning Outcomes

  • Learn how to make strategic decisions on IT resources with limited information.
  • Know how business requirements influence the strategic management of IT.
  • Evaluate global business and technology trends.
  • Use analytic frameworks to understand how information resources can be optimized.
  • Understand the relationship between an organization’s strategy, business activities, technology trends, industry structures and national global environments.

Tools and Concepts

  • Enterprise architecture
  • IT management
  • Cybersecurity and risk management

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IST 736: Text Mining

This course introduces concepts and methods for gaining insight from a large amount of text data. Students learn the application of text mining techniques for business intelligence, digital humanities and social behavior analysis. The main goal of this course is to increase student awareness of the power of a large amount of text data and the computational methods used for finding patterns in large text corpora. It introduces text mining technologies rooted in machine learning, natural language processing and statistics.

It also showcases the applications of text mining technologies in information organization and access, business intelligence, social behavior analysis and digital humanities. Students will also focus on machine learning for unstructured data using a Python-based command line tool called scikit-learn and a range of machine learning techniques, such as Naïve Bayes and support vector machines.

Learning Objectives

  • Describe basic concepts and methods in text mining, such as document representation, information extraction, text classification and clustering, and topic modeling.
  • Use benchmark corpora, commercial and open-source text analysis and visualization tools to explore interesting patterns.
  • Understand conceptually the mechanism of advanced text mining algorithms for information extraction, text classification and clustering, opinion mining and their applications in real-world problems.
  • Choose appropriate technologies for specific text analysis tasks, and evaluate the benefit and challenges of the chosen technical solution.

Concepts and Tools

  • Python / scikit-learn
  • Machine learning
  • Natural language processing (NLP)
  • Reproducible research
  • Corpus statistics
  • Information organization and access
  • Business intelligence
  • Social behavioral analysis
  • Digital humanities

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IST 612: Youth Services in Libraries and Information Centers

This course includes a discussion of collection development—both in schools and in public libraries—that meets the needs of diverse learners. This includes developmentally appropriate literature and library programming, practical applications and use of children’s literature to encourage ongoing literacy, storytelling, digital media literacy and a range of available materials to meet the needs of children across mediums.

Learning Objectives

  • Identify and evaluate children’s and young adult literature genres and literary elements.
  • Evaluate and discuss the aspects of diversity in collection development.
  • Create and assess instructional activities and strategies that promote reading for enjoyment, literacy development and STEM learning.
  • Use knowledge of research and theory to support program decision making.

Tools and Concepts

  • Theories and practices
  • Media, literature and emerging trends in youth services
  • Necessary competencies for youth literacy development

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Business courses offered in collaboration with the Martin J. Whitman School of Management


ACC 652: Accounting Analytics

This course covers accounting analytics including Benford’s Law, current and prior period data, and anomaly detection. Students learn correlation and time series detection, risk assessment and risk scoring, and purchasing card transaction fraud.

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SCM 651: Business Analytics

This course is designed for students who are interested in developing a portfolio of skills in business analytics. Class discussions are based on case studies and articles from business and technical publications. Students perform substantial hands-on work in data collection, analysis and interpretation.

Learning Objectives

  • Use tools to collect and organize data.
  • Identify patterns in data via visualization, statistical analysis and data mining.
  • Develop alternative strategies based on the data.
  • Develop a plan of action to implement business decisions.

Tools and Concepts

  • Machine learning
  • R
  • Statistical summaries and correlations
  • Logit and probit regression modeling
  • Tableau
  • Google Analytics
  • Data structures and query design
  • Power Pivot

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MBC 638: Data Analysis and Decision Making

This course covers the concepts, principles and methods that support the scientific approach to managerial problem solving and process improvement. Students learn basic statistical techniques, how and when to use those techniques and the assumptions associated with their use. Students will be able to perform statistical analyses and interpret results in a meaningful way, and relate results of such analyses to become information-based decision makers.

Learning Objectives

  • Understand the value of data collection and analysis in gaining insight and making decisions in today’s business environment.
  • Identify and apply the appropriate statistical technique for a given set of conditions to answer a particular question.

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FIN 654: Financial Analytics

This course introduces methods and tools useful in decision making in the financial industry, including macroeconomic event studies, analysis of term structures, Morningstar equity data, style analysis, credit card receivables, trading analytics and execution algorithms. Students learn to analyze financial data sets using different analytical methods.

Topics include analytical techniques, nonlinear estimation, portfolio analytics, risk measurement, extreme value analysis, forecasting and predictive techniques and financial modeling. A final project will apply techniques to the construction of an online application.

Learning Objectives

  • Develop ability to apply data analytical concepts to standard finance industry models
  • Develop proficiencies in coding and modeling using R and RStudio
  • Draw insights and verify conclusions based on inferences from model simulations
  • Demonstrate a comprehensive understanding of analytical concepts via final project application

Tools and Concepts

  • R / RStudio / R Markdown
  • Shiny / shinydashboard
  • Data structures
  • Statistical computing
  • Functions, loops and control bootstrapping
  • Empirical characteristics of economic and financial time series
  • Term structure of interest rates
  • Market and credit risk
  • Measuring volatility
  • Risk management analytics

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MBC 639: Leadership in Organizations

Examines leadership on both a knowledge and skill basis. Leadership from a business perspective on three levels: individual, team, and organization.


MAR 653: Marketing Analytics

This course covers marketing analytics techniques including discriminant analysis, logit, cluster analysis, factor analysis and conjoint analysis. Students learn marketing decision support models such as new product diffusion, test-market, price and sales promotion decision models.

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SCM 702: Principles of Management Science

In this course, students learn the concepts and development of analytical model building as used in global supply chain decisions. Topics include modeling for managerial decision making, emphasizing the formulation, solution, interpretation and limitations of linear programs, network models, integer programs, nonlinear programs and simulation, and queuing models for tactical and strategic business decisions related to supply chain management.

To facilitate understanding and communication of the various models discussed in class, the course will make extensive use of spreadsheet-based applications for prescriptive and descriptive mathematical models.

Learning Objectives

  • Improve decision making through the appropriate application of management science principles.
  • Demonstrate knowledge of various modeling and rational data-driven approaches to managerial decision making, including both normative techniques and descriptive models as well as their potential contributions to organizational effectiveness.
  • Design, construct, validate and interpret appropriate spreadsheet-based models for the analysis of individual and recurring managerial decision problems.
  • Utilize post-optimal solution information provided by those models to recommend appropriate actions and to evaluate the sensitivity of those recommendations to changes in environmental assumptions.

Tools and Concepts

  • R1 Excel
  • Prototype LP models
  • Post-optimal sensitivity analysis
  • Multicriteria decision problems
  • Linear, nonlinear and network modeling
  • Descriptive models
  • Mixed integer and quadratic programs
  • Queueing and simulation models

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