courseraАнализ данных

Data Science Fundamentals, Part 2: Data–Analysis and Visualization

Курс от Pearson

Начальный≈ 7.6 чАнглийский

О курсе

This course teaches how to ask the right questions and extract meaningful insights from complex datasets. Through hands-on lessons, you’ll master industry-standard Python libraries such as matplotlib and seaborn, enabling you to create compelling visualizations like histograms, boxplots, and scatter plots. You'll learn to uncover patterns, relationships, and correlations within your data, and develop a critical eye for interpreting results. You'll also learn about the pitfalls of data interpretation, including the impact of mixed effects and the nuances of Simpson’s Paradox, ensuring you can navigate and communicate findings with confidence. Whether you’re a beginner or looking to deepen your analytical toolkit, this course will empower you to transform raw data into actionable knowledge.

Навыки, которые вы освоите

Seaborn Scatter Plots Matplotlib Data Visualization Software Box Plots Histogram Exploratory Data Analysis Data Literacy Plot (Graphics)Descriptive Statistics Statistics Analytical Skills Data Analysis Correlation Analysis Statistical Analysis Descriptive Analytics Statistical Visualization

Программа курса

1 модулей · 21 учебных материалов

01Data Science Fundamentals Part 2: Machine Learning and Statistical Analysis: Unit 1 21 материалов

Module Introduction

Specialization IntroductionВидео

Exploring Data--Analysis and Visualization

TopicsВидео Introduction to the pandas Library, Part 1Видео Introduction to the pandas Library, Part 2Видео

Учитесь у экспертов

Pearson

Преподаватель курса

Jonathan Dinu

Freelance ML Engineer