Course DescriptionsCourse DescriptionsCourse Descriptions

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.

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

Tools and Concepts

An analysis of relational and non-relational databases and their corresponding database management system architectures. Learn to build complex database objects to support a variety of needs from big data and traditional perspectives. Data systems performance, scalability, security.

Learning Objectives

Tools and Concepts

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.

General overview of industry standard machine learning techniques and algorithms. Focus on machine learning model building and optimization, real-world applications, and future directions in the field. Hands-on experience with modern data science packages.

Learning Objectives

Tools and Concepts

Most librarians find themselves in management roles early in their careers. Some manage volunteer or student staff, some manage paraprofessional staff, and others manage other librarians. Management roles require librarians to have a special ability set including planning, organizational, decision-making, leadership, interpersonal, budgetary, and other skills. This course seeks to provide students with knowledge and experiences that will prepare them to apply these skills in a variety of library contexts.

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

Tools and Concepts

In an ever-evolving digital workplace, cloud computing has become the backbone of business operations. This course will provide students with an understanding of the cloud computing industry and economy while exploring how companies strategically plan to adopt, migrate and manage secure cloud applications.

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.

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

Tools and Concepts

Watch the Data Administration Concepts and Database Management Course Overview.

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

Tools and Concepts

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.

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Tools and Concepts

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

Tools and Concepts

Watch the Information Management and Technology Course Overview.

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

Tools and Concepts

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

Tools and Concepts

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

Tools and Concepts

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

Tools and Concepts

Watch the Introduction to Data Science Course Overview.

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

Tools and Concepts

Librarianship is a rapidly evolving field. This course introduces established structures and practices and directions in which we are moving. Survey of the professional, social, ethical, and legal issues affecting information service professionals and organizations and prepares students to deal with these issues and work with a diverse community.

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

Tools and Concepts

Watch the Information Resources: Organization and Access Course Overview.

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

Tools and Concepts

Watch the Information Systems Analysis Course Overview.

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.

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.

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.

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

Tools and Concepts

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.

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

Tools and Concepts

Increase the agility of a data science project by improving the process a team uses to execute their project. Explore data science life cycles (e.g., CRISP-DM, TDSP) and collaboration frameworks (e.g., Kanban, Scrum).

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

Tools and Concepts

Watch the Managing Information Systems Projects Course Overview.

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.

Students complete distributed ledger labs before developing, implementing, and ‘demo or die’ sharktanking their own new blockchain project. Blockchain concepts such as decentralization, smart contracts, trust and consensus governance are discussed.

Blockchain or distributed ledger technology is disrupting currency, property, financial, healthcare, energy, and other markets–or will likely do so over the coming decades. Information professionals, university faculty, student researchers, entrepreneurs, coders, software engineers, cloud managers, and architects are avidly engaging in emerging opportunities. Distributed ledger technology innovation, trust establishment and maintenance, iterative consensus development, and autonomy in use resulting from the prior conditions being fulfilled and maintained will all be explored.

This course introduces students to a variety of approaches that can be taken in research studies and the appropriate selection and application of methods, including quantitative, qualitative, critical, historical, and design-based approaches, from research formulation to communication of results.

Students will develop a research proposal through various phases including literature review, method outline, and expected outcomes/conclusions. After taking this course, the students will be able to:

The IS Research Capstone trains students for inquiry into the complexities of enterprise digital transformation. Students will complete a research project under faculty supervision to fulfill the exit requirement in the Information Systems graduate program. PREREQ: IST 614, IST 617, and the completion of 24 credits.

The IS Research Capstone course will serve as the vehicle to organize the student research experience and closely track student progress in order to ensure a successful and instructive learning experience. Research ethics and compliance with institutional review procedures will be emphasized throughout and will serve as bases for criteria in both formative and summative assessment of the student in this course. Digital transformation of the modern enterprise is a complex and multi-faceted phenomenon. Computer technology drives it, but digital transformation is a product of multiple elements and factors interacting in unprecedented ways. Organizational leaders must continually rethink the nature and organization of work and structuring of work relations as the digital economy itself evolves continually to confront strategists with new challenges. Effective leadership in dynamic environments calls for new ways of thinking about competition, markets and stakeholders, and about governance, policy and regulation. The IS Capstone Research experience is meant for the student who wishes formally to inquire into the complexities of digital transformation – be it in corporate, not-for-profit, or municipal milieux, in public libraries and schools or technology start-ups – by completing a well-defined research project under faculty guidance. The research undertaken could be applied or theory-driven, quantitative or qualitative, positivist or naturalistic. Research ethics and compliance with institutional review procedures will be highlighted throughout and will serve as bases for criteria in both formative and summative assessment of the student in this course.

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

Tools and Concepts

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

Tools and Concepts

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

Tools and Concepts

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

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

Tools and Concepts

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.

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

Tools and Concepts

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

Concepts and Tools

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

Tools and Concepts

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.

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

Tools and Concepts

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

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

Tools and Concepts

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

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.

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

Tools and Concepts

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