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⏱ 2h 54m📚 29 lessons
Linear Programming for UN and SBMPTN Math Exams
Master linear programming concepts, inequalities, and optimization techniques to ace your high school graduation and university entrance math exams.
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About this course
Preparing for major standardized math exams like the UN or SBMPTN can feel overwhelming, especially when tackling optimization and coordinate geometry problems. Linear programming is a guaranteed source of high-scoring points if you master the foundational steps. This text-based course guides you from absolute math basics to solving complex exam-style linear programming problems with speed and confidence. You will learn to translate word problems into mathematical models, graph inequalities, and find maximum or minimum values using proven exam strategies.
What you'll learn:
- Understand the core terminology of linear programming, including objective functions, constraints, and feasible regions
- Set up systems of linear inequalities from real-world word problems and exam questions
- Graph inequalities accurately on Cartesian coordinates to identify the solution area
- Apply the corner point method and search line techniques to find optimal values
- Solve past exam questions from UN and SBMPTN using efficient, time-saving shortcuts
- Avoid common algebraic errors and misinterpretations that lead to incorrect coordinates
Starting with fundamental algebraic concepts, you will progress through structured text-based lessons that break down system modeling, graphing, and optimization step-by-step with clear, written walkthroughs. This course is designed for high school students, college aspirants, and anyone preparing for standardized mathematics exams, requiring no advanced mathematical background. Begin reading today and secure your exam points in linear programming.
What you'll get
📜Certificate of completion Add it to your LinkedIn profile
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⚡Short & focused 2h 54m of practical content
Certificate of completion
Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.