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Microsoft

Critical Thinking & Problem Solving for Tech Careers

Microsoft via edX

Overview

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Critical Thinking & Problem Solving for Tech Careers is a practical, workflow-focused course that helps aspiring and early-career technologists tackle messy, ambiguous workplace problems with structured critical thinking—before jumping to code or quick fixes. Across six modules, learners build a repeatable toolkit to clarify problems, avoid common thinking traps (confirmation bias, groupthink, premature optimization), write strong problem statements, and break work into testable subproblems. They learn root-cause diagnosis using tools such as 5 Whys, fishbone categories, and a disciplined debugging loop (reproduce → isolate → verify → prevent).

The course also strengthens evidence-based decision-making: evaluating information quality, surfacing assumptions, and weighing trade-offs with lightweight frameworks (impact—effort, prioritization, basic risk scoring). Collaboration is reinforced through clear reasoning and communication (Context → Problem → Options → Recommendation → Rationale), high-leverage questions, and productive disagreement practices.

By the end, learners can turn vague issues into actionable scope, identify underlying causes, run MVP-style experiments to test solutions, and communicate decisions to reduce rework and improve alignment. Learning is scenario-driven with case studies, self-checks, and assignments culminating in an integrated final application.

Syllabus

  • Define critical thinking for technical decisions.
  • Spot and mitigate common cognitive biases.
  • Avoid confirmation, sunk cost, availability, groupthink.
  • Resist edge-case overfitting and premature optimization.
  • Convert complaints into scoped problem statements.
  • Specify who, what, when, where, impact.
  • Identify constraints and success criteria early.
  • Separate symptoms from underlying problems.
  • Break down messy problems into tests.
  • Use hypotheses to guide investigation.
  • Apply root-cause analysis to incidents.
  • Debug systematically to shrink search space.
  • Judge source reliability, completeness, distortion.
  • Surface assumptions and plan validation checks.
  • Decide with explicit trade-offs, not intuition.
  • Generate multiple options, including do-nothing.
  • Compare options by impact, effort, risk.
  • Pick a first MVP; keep fallbacks.
  • Communicate reasoning: context, options, recommendation.
  • Tailor messages for technical and nontechnical audiences.
  • Ask clarifying questions on goals, constraints.
  • Resolve disagreements using criteria and experiments.

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