Data Science Fundamentals, Part 2: Estimation and Evaluation

О курсе

Thsi course explores foundational and advanced techniques for making reliable inferences from data, starting with a the history and evolution of statistical analysis. Through hands-on lessons, you’ll learn how to leverage computational and sampling-based methods to draw meaningful conclusions, and gain practical experience with hypothesis testing—a cornerstone skill for optimizing digital experiences, such as through A/B testing. The course emphasizes the importance of understanding and quantifying uncertainty, equipping you with the tools to interpret confidence intervals and make well-informed decisions. You’ll also tackle the critical distinction between correlation and causation, ensuring your analyses are robust and actionable. Whether you’re looking to enhance your analytical toolkit or drive impactful business outcomes, this course teaches essential skills for today’s data-centric world.

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Pearson

Преподаватель курса

Jonathan Dinu

Freelance ML Engineer