Al for Document Extraction &
Data Structuring

    • 68 learners

      Enrolled

    • Level 2

      Intermediate

    • Self-paced

      Course duration

    • 1 Ebook

      Free of charge
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    Course overview
    This course equips learners with practical skills to use AI for document extraction and data structuring, helping technical teams transform dense documents into structured, usable outputs such as tables, schemas, and extraction-ready data.

    Participants will learn how to apply schema-first extraction, design output formats before prompting, extract key values from scientific papers, CoA, regulatory documents, and technical reports, and validate AI-extracted data before formal use. By the end of this course, learners will be able to process complex documents faster while maintaining consistency, traceability, and human review.
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    What We Offer

    What's included in this online course?

    A step-by-step guide

    Learn how to move from complex documents to structured outputs through schema design, extraction, validation, and review.

    Study at your own pace

    Access the course anytime and practice with document extraction examples based on technical, scientific, quality, and regulatory use cases.

    Practical extraction experience

    Use CO-STAR prompts to extract biomedical values, CoA parameters, regulatory requirements, and structured data from documents.
    What you'll be able to do
     Design extraction schemas before writing AI prompts
      Extract structured data from scientific, quality, and regulatory documents
      Generate tables or CSV-ready outputs from complex document content
      Apply self-validation and Four-Eyes review before using extracted data formally
    Certification included
    Complete this course to strengthen your AI literacy in document extraction and data structuring. You will learn how to use AI responsibly to extract data, structure outputs, validate results, and maintain traceability to source documents.

    This certificate shows that you understand how to apply AI tools for schema-first extraction, technical document processing, and validated data preparation in structured workflows.

    Meet the People Behind AI Literacy

    AI Literacy is developed through the collaboration of cross-functional contributors who support the planning, content development, technical implementation, and learning experience of the program. Together, the team helps bring practical AI knowledge, real-world use cases, and responsible AI guidance to employees across the organization.

    Edwin Simjaya

    Head of AI and Software Center

    Tamaria Artpinkan

    Product Innovation Lead

    Selvianingrum

    AI Engineer

    Reyhan Phillies W.

    Project Manager

    Pradipa Arya Nugraha

    UI/UX Designer

    Runi Dwi Jiasta

    Project Manager

    Bernadus Ignasio

    AI Engineer

    Mary Priscilla

    AI Engineer

    Renata Rusli

    UI/UX Designer

    Alfredo Anthony S.

    UI/UX Designer

    Shalomita Sharon P.

    UI/UX Designer

    Terence Lee

    UI/UX Designer