Practice Essential Data Science Skills With Diamonds Dataset | CodeSignal Learn

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Practice Essential Data Science Skills With Diamonds Dataset

Data Science

5 courses

125 practices

8 hours

Explore fundamental data science skills using the diamonds dataset in this learning path. From exploratory data analysis and data cleaning to feature engineering and regression modeling, gain practical experience with essential Python tools for data manipulation and analysis.

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284 learners

Earn a shareable

Certificate of Achievement

Verified skills you'll gain

INTERMEDIATE

Exploratory Data Analysis and Visualization

DEVELOPING

Data Cleaning and Preprocessing

Tools you'll use

MatPlotLib

Pandas

Python

Scikit-learn

Seaborn

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Course 1

Basic Exploratory Data Analysis with Diamonds

5 lessons

25 practices

Explore how to load, display, and understand the basic information of the diamonds dataset. Learn to summarize statistics and identify missing values.

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Course 2

Intro to Data Cleaning and Preprocessing with Diamonds

5 lessons

25 practices

Learn to clean and preprocess the diamonds dataset, including converting categorical features to ordered types and visualizing data distributions. Gain essential skills in data preparation and visualization techniques, ensuring a solid foundation for deeper data analysis and modeling tasks.

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Course 3

Go Deeper into Exploratory Data Analysis (EDA)

5 lessons

25 practices

Dive into deeper exploratory data analysis with the diamonds dataset. Learn to create visualizations that help uncover intricate patterns within the data.

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Course 4

Feature Engineering and Correlation Analysis in Pandas

5 lessons

25 practices

Learn how to engineer new features from existing data and assess their relationships using correlation analysis, thereby enhancing your understanding and improving model predictions.

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Course 5

Regression Analysis to Model Diamond Prices

5 lessons

25 practices

Final stop to implement regression analysis to model diamond prices based on various features. Learn to train, predict, and evaluate model performance.

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