About the Course
Organizations today require educational results that are verifiable and reproducible. To achieve this, professionals must master a specific set of capabilities, including data cleaning for educational datasets, applying the CRISP-DM framework to learning contexts, and designing interactive dashboards that track real-time engagement. This course moves beyond theoretical discussion to provide a structured system for educational improvement. You will learn to practice hands-on data visualization using tools like Power BI or Tableau while being introduced to the conceptual foundations of predictive modeling and machine learning in student success initiatives.
What you will learn in this course includes the ability to map learner journeys across multiple platforms, calculate the impact of instructional interventions, and build automated reporting systems for institutional leadership. This course teaches you how to synthesize disparate data points from Learning Management Systems (LMS) and external activities into a unified view of learner progress. We acknowledge the real-world constraints of data silos, varying levels of digital literacy, and the complexities of data privacy regulations. This training is specifically designed for professionals who must deliver high-impact results within these operational realities, providing the tools to build a culture of evidence-based decision-making.
Target Audience
This program is essential for professionals responsible for the design, delivery, and assessment of educational programs in academic and corporate environments.
This course is designed for:
- Instructional Designers optimizing course content through engagement data
- Academic Registrars tracking student progression and retention metrics
- Learning and Development Managers measuring corporate training ROI
- EdTech Product Managers developing data-driven learning features
- School Administrators implementing institutional effectiveness frameworks
- Educational Data Analysts building student performance dashboards
- Curriculum Developers aligning content with learner achievement data
- Student Success Coaches identifying at-risk learners for intervention
- Higher Education Researchers studying learning behavior and outcomes
- Corporate Trainers evaluating the impact of digital learning initiatives
Course Objectives
This course equips you to design, execute, and report learning analytics initiatives that improve student success, ensure data compliance, and support strategic institutional goals.
By the end of this course, you'll be able to:
- Assess institutional data readiness using the Learning Analytics Maturity Model
- Apply xAPI® standards to capture learning experiences outside the LMS
- Build interactive student engagement dashboards using Power BI or Tableau
- Calculate the correlation between specific learning activities and assessment outcomes
- Design a predictive model to identify students at risk of attrition
- Evaluate curriculum effectiveness using the Kirkpatrick Model of evaluation
- Navigate data privacy requirements for educational data governance and ethics
- Synthesize complex learning data into actionable reports for executive leadership
Requirements & Prerequisites
Participants should have a basic understanding of educational delivery or instructional design. Familiarity with spreadsheet software (Microsoft Excel) is required. No prior programming or advanced statistical knowledge is necessary, as the course focuses on operational application and the use of visualization tools.
Professional and Organizational Impact
When you lead learning analytics with credible data and practical strategies, you become a trusted driver of academic excellence and organizational growth.
As a professional, you will benefit by:
- Build technical expertise in educational data mining and visualization
- Gain confidence in making evidence-based pedagogical recommendations
- Strengthen your ability to prove the ROI of learning initiatives
- Enhance your professional profile as a data-literate education leader
- Develop specialized skills in xAPI and LRS implementation
- Position yourself for senior roles in institutional effectiveness
- Expand your capability to lead digital transformation in education
Organizations that embed learning analytics excellence into their operational context reduce attrition, optimize resources, and build lasting competitive advantage.
Your organization will benefit from:
- Improved student retention through early identification of at-risk learners
- Optimized resource allocation based on high-impact learning activities
- Enhanced compliance with international data protection and privacy standards
- Increased accuracy in institutional reporting and accreditation processes
- Strengthened competitive positioning through personalized learning experiences
- Reduced costs by eliminating ineffective curriculum components
- Data-driven evidence for strategic planning and stakeholder investment
Training Methodology
This is a practical, outcome-driven course designed to turn learning analytics aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on calculation of learner engagement metrics using real educational datasets
- Scenario simulation requiring intervention decisions for at-risk student profiles
- Data audit exercise using a standardized educational data governance checklist
- Stakeholder mapping exercise for reporting learning outcomes to academic boards
- Case study analysis from K-12, Higher Education, and Corporate sectors
- Group workshop producing a functional student success dashboard prototype
- Reflection exercise benchmarking current institutional practices against ISO/IEC 20741 standards
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Data Analytics for Education and Learning Analytics Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Skills Relevance
- Master cutting-edge data analytics tools applicable in modern educational environments.
- Transform data into actionable insights for strategic educational improvements.
- Leverage analytics to craft personalized learning experiences and boost engagement.
Expert Delivery
- Learn from leading educators and data scientists with real-world experience.
- Courses curated by experts to maximize your learning in minimal time.
- Interactive, hands-on sessions ensure you can apply concepts immediately.
Career Advancement
- Enhance your resume with highly sought-after data analytics competencies.
- Position yourself as a leader in the merging fields of education and technology.
- Unlock new career opportunities in educational institutions and ed-tech companies.
Industry Tools and Platforms Featured in this Training
The platforms and vendors local teams are running today — taught against real configurations, not generic vendor demos.
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Canvas InstructureLearning management system data can be used to examine learner engagement, course participation, and completion patterns in higher education.
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Tableau SalesforceUsed to build dashboards and visualizations for student performance, retention, and curriculum impact reporting.
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Excel MicrosoftUsed for cleaning, summarizing, and reporting education data before it is pushed into dashboards or models.
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Python Python Software FoundationUsed for data cleaning, analysis, and predictive modeling in student success and learning analytics workflows.
