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⏱ 2h 48m📚 28 lessons
Quantitative Percentages for Competitive Exams
Master the foundational arithmetic and rapid calculation strategies needed to quickly and accurately solve percentage problems in standardized aptitude tests.
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About this course
Quantitative aptitude sections often rely heavily on a solid understanding of percentages. Success in competitive exams demands both conceptual clarity and speed in problem-solving.
This course provides a comprehensive text-based guide to percentage concepts, equipping you with the fundamental knowledge and essential short tricks necessary to approach complex quantitative questions with confidence and precision.
What you'll learn:
* Understand the core definitions of percentages, base values, and percentage change calculations.
* Learn efficient methods for converting between percentages, decimals, and common fractions for rapid mental arithmetic.
* Apply percentage increase and decrease concepts to real-world scenarios like profit, loss, and discounts.
* Practice solving typical aptitude exam question types, including population growth, mixtures, and successive percentage changes.
* Develop reliable strategies for breaking down complex word problems and identifying the fastest path to the correct solution.
We begin with key terminology and foundational rules before moving into systematic problem-solving techniques. The course emphasizes reading comprehension and applying efficient calculation shortcuts through written examples and practice exercises.
This course is designed for absolute beginners preparing for quantitative sections of standardized aptitude tests or competitive examinations, such as the CAT. No prior high-level mathematics knowledge is required.
Start building your quantitative foundation today.
What you'll get
📜Certificate of completion Add it to your LinkedIn profile
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💸14-day refund No questions asked
⚡Short & focused 2h 48m 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.