e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.Most performance problems don’t fail because people don’t care—they fail because “good” is unclear, feedback is fuzzy, and development has no system behind it.

In this course, you’ll learn a practical, repeatable approach to improving performance that’s grounded in clear standards, coaching conversations that lead to behavior change, and development mechanisms that actually stick. You’ll start by turning vague expectations (like “be more proactive”) into observable performance standards tied to outcomes and behaviors. Then you’ll build a lightweight scorecard using a handful of leading and lagging signals—so performance discussions are fair, specific, and based on shared evidence instead of memory or impressions. Next, you’ll practice giving feedback that’s actionable and non-judgmental using structured models like SBI and AID, and you’ll add feed-forward techniques to shift conversations from rehashing mistakes to improving what happens next. From there, you’ll design development systems that scale: delegation levels matched to readiness and risk, Individual Development Plans with milestones, and deliberate practice loops supported by mini-rubrics. Finally, you’ll learn how to manage performance variance across a team—supporting high performers without creating hero culture, unlocking growth in solid contributors, and addressing low performance with clarity—while building peer coaching and mentorship structures that reinforce development beyond the manager.