SC&I Courses

Learning Objectives

Upon successful completion of this course, students will be able to:

• Use models and structures to depict large data sets within a data analytics environment.
• Apply statistical models to data using SPSS and related software programs.
• Explain, determine, debate, compare and contrast: predictive analytic issues, language issues, algorithms, analytic methods, curation issues, and applications to social networks.
• Create a tutorial guide to assist others in data analytic endeavors to include structuring data sets, using software to analyze data, and depositing and making accessible big data sets.
• Assess how different statistical models might be used to extract meaning from particular data sets.
• Understand how clustering and other statistical models can be used to extract meaning from data sets which will then lead to decision models on particular sub-groups.
• Specify how to manage and curate large sets within a particular application area.
• Address storage, security, and privacy issues as they apply to different types of large data sets.
• Implement appropriate frameworks to identify the overall model for a big data set, how such data might be analyzed, curated, placed in a repository to provide appropriate access points for data set retrieval.

Learning Objectives

Upon successful completion of this course, students will be able to:

• Apply programming languages and tools such as UNIX commands, MySQL, Python, and R to collect, clean, process, and analyze data.
• Exhibit familiarity with data science methods by learning and experiencing essential algorithms and approaches.
• Use statistical methods and visualization techniques to explore and analyze data, and visualize and present the results.
• Identify data-driven analytics problems and design solutions and applications to solve them.

Learning Objectives

Upon successful completion of this course, students will be able to:

• Exhibit familiarity with Machine Learning methods by learning and experiencing essential algorithms and approaches as they relate to data problems and information processing strategies;
• Use Machine Learning techniques to explore and analyze data, and derive decision-making insights;
• Identify data-driven analytics problems as they relate to organizational or individual information needs;
• Design innovative solutions and applications to solve problems using Machine Learning techniques and strategies.

Learning Objectives

Upon successful completion of this course, students will be able to:

• Describe the history and current state of digital archives/museums;
• Investigate the major questions that affect how an institution should gather and organize digital materials;
• Design a new digital curation program including its principles for selection of content, the kinds of tools that might be used for a variety of materials, an organization of the library that is appropriate, and relevant legal issues;
• Identify possible funding sources and sustainability.

Learning Objectives

Upon successful completion of this course, students will be able to:

• Articulate the importance of information security to organizations and individuals and learn how information security can be incorporated in any system;
• Evaluate information assets in order to define the level of security needed, information security strategy, model and architecture to suit organizational security needs;
• Identify possible threats to assets, and possible countermeasures to reduce vulnerabilities and avert risks and their suitability for implementation;
• Practice best practices concerning information security behavior to help protect information assets;
• Utilize standard processes and procedures to analyze security requirements and design and document information security plans. 

Learning Objectives

Upon successful completion of this course, students will be able to:

• Write a grant proposal focused on digital preservation and digitization of collections
• Assess copyright of cultural heritage materials for public digital access
• Compare and contrast controlled digital lending practices across an array of institutions
• Evaluate digitization best practices and advanced imaging techniques in cultural heritage institutions
• Use frameworks such as Open Archival Information System (OAIS) and National Digital Stewardship Alliance (NDSA) levels to assess digital preservation strategies
• Utilize time management techniques to understand the intertwined nature of digital preservation and project management
• Develop a personal digital collection while ensuring its long term accessibility and digital preservation status

Learning Objectives

Upon successful completion of this course, students will be able to:

• Examine, evaluate, and apply contemporary management concepts, theories, and functions.
• Demonstrate an understanding of the applications of managerial functions including planning, organizing, and leading.
• Explore existing information organizations and critically analyze the ways in which management activities and functions are carried out in those environments.
• Analyze and evaluate key organizational concepts and issues.
• Develop and apply problem-solving skills in a managerial situation.
• Contribute to collaborative projects and initiatives that are relevant in today's interactive and technologically mediated work environments.

Learning Objectives

Upon successful completion of this course, students will be able to:

• Critically analyze and evaluate key leadership theories, models, and perspectives and apply them in a library context.
• Integrate library core values, competencies, transformative leadership approaches, and attributes of library leaders in diverse library settings.
• Formulate a library leadership philosophy and development plan to adopt in professional endeavors based on a self-assessment of one's leadership traits, competencies, styles, strengths, and areas for future growth.
• Adopt principles and models of transformational leadership in practical library contexts as a result of knowledge gained though inquiry, discovery, discussion, observation, and self-introspection throughout the course.
• Work effectively in interactions and communications with others such as in teams and other collaborative endeavors, planning and decision making, coaching/mentoring, dealing with challenges, and promoting diversity in the community in which they serve.

Learning Objectives

• Students will investigate the range of evaluative methods used in library and information science to assess institutional, system and service performance. Value issues and external validity issues will be highlighted during this review. Emphasis throughout the course will be on the impact of systems and services to end-users.
• Measurement issues will be explored as they relate to evaluation goals and objectives. Students will simulate the design of an evaluation program for targeted users and will analyze the results obtained using quantitative and qualitative research methods. Effective methods for graphing data results will be emphasized for this objective. Computer packages will be used to demonstrate data analysis and the creation of graphic displays. Computer laboratory sessions will be held as needed to supplement the course topics.
• Alternative methods to evaluate services and systems will be explored with a concomitant analysis of the advantages and disadvantages of each approach. Specific references will be made to the appropriateness of different evaluative methodologies and criteria.