📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI in Employee Training and Development, from foundations to a certified capstone project.
Needs
• Skills taxonomies and inferring skills from role and project data
• Gap analysis against future capability requirements rather than current roles
• Distinguishing a training problem from a process or incentive problem
Design
• Learning objectives and assessment alignment before content generation
• Generative AI for content drafting, and subject-matter review workflow
• Simulation and scenario-based practice for judgement-heavy roles
Delivery
• Recommendation of learning content and its cold-start problem
• Spacing and reinforcement scheduled around real work demands
• Coaching assistants and the boundary with manager responsibility
Evaluation
• Kirkpatrick levels and why most programmes stop at reaction data
• Transfer to job performance and the measurement designs that detect it
• Control groups and staged rollout as practical evaluation tools
Governance
• Learner data privacy and the reuse of training data in performance decisions
• Accessibility and language inclusion across a distributed workforce
• Avoiding recommendation systems that entrench existing advantage
Earn government-registered certification in AI in Employee Training and Development
e-Certificate and e-Marksheet issued on successful completion.
