Advanced Learning Analytics and Skills Intelligence Training Course

Course overview

Learning teams are increasingly expected to prove which interventions build capability, improve mobility, and support business performance—not simply report attendance, completions, and satisfaction scores. This course addresses the gap between routine learning reporting and decision-grade learning intelligence. Participants learn to connect learning data, workforce skills data, performance signals, and operational measures into evidence that helps leaders prioritise investment, identify skill gaps, and intervene before capability risks affect delivery.

The course covers learning analytics strategy, data architecture, metric design, skills taxonomy governance, proficiency assessment, and dashboard development. Participants work with xAPI event data, learning record store outputs, HRIS and performance data structures, Excel Power Query transformations, and Power BI data models. They learn to define measurable learning hypotheses, build leading and lagging indicators, segment learners and populations responsibly, calculate skill-gap and capability-risk measures, and distinguish correlation from defensible causal claims.

Delivery combines instructor-led analysis demonstrations with guided labs, data-quality diagnostics, dashboard critiques, and a multi-day skills intelligence case study. Each participant develops a Learning Analytics and Skills Intelligence Action Pack: a metric dictionary, data-source map, skills measurement model, Power BI dashboard wireframe, and 90-day implementation roadmap. The course is designed for L&D professionals who already manage learning data and need to turn it into structured evidence for workforce and business decisions.

Course objectives

By the end of this course, participants will be able to:

• Design a learning analytics measurement framework linking learning activity, skill acquisition, application, and business indicators
• Create a metric dictionary with definitions, formulas, owners, data sources, refresh frequencies, and decision uses
• Map xAPI, LMS, HRIS, performance, and assessment data into a governed learning-data architecture
• Use Excel Power Query to profile, clean, join, and document learning and skills data sets
• Build a Power BI semantic model and dashboard for participation, proficiency, skill-gap, and capability-risk analysis
• Construct a skills taxonomy and proficiency model aligned to job families, critical roles, and business capabilities
• Apply cohort analysis, segmentation, confidence intervals, and comparison-group logic to evaluate learning impact
• Produce a 90-day learning analytics and skills intelligence implementation roadmap with governance controls

Benefits of attending

Target competencies

Who should attend

• Learning Analytics Managers — who need to convert fragmented learning data into executive-ready workforce insight
• Senior Learning and Development Specialists — who must demonstrate the value and application of major learning programmes
• Talent Management Managers — who connect capability data to succession, mobility, and critical-role planning
• HR Data and People Analytics Analysts — who integrate learning, skills, performance, and workforce data sources
• Learning Technology Managers — who own LMS, LXP, LRS, and xAPI data flows that require stronger reporting design
• Workforce Planning Managers — who need credible skill-gap evidence for reskilling and capacity decisions

Requirements and prerequisites

Participants should have practical experience in L&D, talent, HR analytics, or learning technology and be comfortable interpreting tables, percentages, trends, and basic charts. Familiarity with an LMS or LXP, learner-completion reports, Excel formulas, and the distinction between learning activity and learning outcomes is assumed. Participants should also understand their organisation’s basic job-role or competency structure. Prior Power BI, SQL, Python, statistical modelling, or xAPI implementation experience is not required; the course introduces the relevant functions and concepts through guided exercises. This is not suitable for participants with no exposure to learning data or L&D operations.

Training methodology

The five-day programme alternates short instructor-led sessions with structured data labs using a realistic enterprise reskilling scenario. Participants inspect LMS, xAPI, assessment, skills, and performance extracts; use Excel Power Query to prepare data; and translate stakeholder questions into measures and dashboard views in Power BI. Small groups challenge metric definitions, identify data-governance risks, and test competing explanations for performance changes. Daily outputs build toward an individual Learning Analytics and Skills Intelligence Action Pack, refined through instructor feedback and a final stakeholder presentation.

Course outline

Day 1: Learning analytics strategy and measurement design

• From activity reporting to decision-grade learning intelligence
• Learning value chains and measurable capability hypotheses
• Leading, lagging, input, output, outcome, and impact indicators
• Metric dictionary design and calculation governance
• Stakeholder decision mapping for executives and business leaders
• Learning analytics maturity assessment models
• Ethical use, privacy, fairness, and consent in learner data

Workshop: Participants convert a business capability problem into a measurement framework, stakeholder map, and first draft of a metric dictionary.

Day 2: Learning data architecture and preparation

• LMS, LXP, LRS, HRIS, assessment, and performance data structures
• xAPI statement anatomy, verbs, activities, actors, and context fields
• Learning Record Store extraction patterns and event-level data
• Unique identifiers, master data, and learner-to-employee matching
• Data lineage, refresh cycles, access roles, and retention controls
• Excel Power Query profiling, cleansing, merging, and append operations
• Missing values, duplicate records, and data-quality exception logging

Workshop: Participants prepare and document a joined learning-and-workforce data set in Excel Power Query and produce a data-source map.

Day 3: Skills intelligence and capability measurement

• Skills taxonomies, ontologies, and role-based capability architecture
• Critical-skill identification using strategic value and scarcity criteria
• Proficiency scales and observable evidence descriptors
• Self-assessment, manager assessment, test, and work-sample evidence
• Skill inference rules and confidence scoring
• Skill-gap, skill-supply, and capability-risk calculations
• Bias controls for assessment, inference, and demographic segmentation

Workshop: Participants build a critical-role skills profile, proficiency rubric, and skill-gap analysis for a reskilling case.

Day 4: Analysis, visualisation, and impact evaluation

• Power BI star-schema design for learning and skills data
• DAX measures for participation, completion, proficiency, and skill movement
• Cohort analysis and learner-population segmentation
• Funnel analysis from enrolment through application
• Confidence intervals, sample-size limitations, and uncertainty communication
• Comparison groups, pre-post measures, and contribution analysis
• Dashboard storytelling for operational and executive audiences

Workshop: Participants create a Power BI dashboard wireframe and calculate cohort, proficiency, and skill-gap measures from the case data.

Day 5: Operating model and implementation roadmap

• Learning analytics operating models and accountability roles
• Metric ownership, dashboard release, and change-control procedures
• Data-quality monitoring and reconciliation routines
• Insight-to-action workflows for managers and learning partners
• Prioritising analytics use cases by value, feasibility, and risk
• Ninety-day implementation planning and adoption measures
• Executive narrative and evidence-based recommendation structure

Workshop: Participants present their Learning Analytics and Skills Intelligence Action Pack, including a dashboard concept, governance decisions, and 90-day roadmap.

Tools & standards covered

Microsoft Power BI, Microsoft Excel Power Query, Watershed LRS, xAPI (Experience API)

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions