This category explores the dynamic field of Library and Information Science, emphasizing both traditional knowledge organization and emerging digital innovations. Learners gain practical skills in managing, preserving, and providing access to information resources in the modern knowledge society.

It integrates current trends such as artificial intelligence (AI) and machine learning in the digitization of library materials, reflecting the idea that “the library is a growing organism” — constantly evolving with technology. Learners will also develop competence in using reference management software and digital tools that enhance research, information retrieval, and scholarly communication.

Archives Management

This course introduces learners to the basic principles and practices of managing archives. It covers how archives are created, organized, preserved, and accessed for future use. Learners will gain practical skills in handling both physical and digital archives to support institutional memory and accountability.

Records Management

This course provides trainees with the knowledge and skills required to create, manage, store, protect, and dispose of records in an organization. It covers both manual and electronic records systems, emphasizing best practices in classification, retrieval, retention, preservation, and legal compliance. Learners will gain practical competencies in organizing records, circulating records for action, applying security measures, and supporting efficient decision-making through proper records management.

Digitization and Artificial Intelligence in Libraries

Course Description: Digitization and Artificial Intelligence in Libraries

This course explores the integration of digitization technologies and artificial intelligence (AI) in the modernization of library and information services. It equips learners with the knowledge and practical skills to convert physical materials into digital formats, manage electronic collections, and apply intelligent systems for improved access, retrieval, and preservation of information.

Learners will examine how machine learning, optical character recognition (OCR), and metadata automation are transforming library workflows. The course also introduces reference management software, digital curation practices, and ethical considerations in AI-driven libraries.

Learning Outcomes:
By the end of this course, learners will be able to:

  1. Explain the concepts and importance of digitization in libraries.

  2. Apply AI and machine learning tools in digital resource management.

  3. Perform basic digitization processes, including scanning and OCR.

  4. Use reference management tools for digital scholarship.

  5. Evaluate the ethical and professional issues in AI-enhanced library services.