Data Science - Visualizing Data and Exploring Models - Revised
Learn about data science techniques, applying visualizations to display data, feature engineering methods, and more!
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CertificationView course modules
This course begins by discussing the importance of data exploration. It will teach you what to use for data visualizations in R and in Python. You will study different plots for different views such as scatter and line plots, bar plots, histograms, box plots, violin plots, Q-Q plots. You will also learn that scatter plot of individual columns can be useful for detailed exploration of the features in your dataset.
You will then study feature engineering which is the process of using domain knowledge of the data to create features that make machine learning algorithms work. You will look into models which are evaluated based on statistics about the errors, or residuals, in the predicted values. You will study the features and methods available in R and Python for creating Machine learning models including the process and options for evaluation.
Learn about about data science theory and practice with this free, online course. Upon completing the course, you will have a better understanding of the functions of exploratory data analysis and what factors can affect your views of data, as well as a much better insight into the different types of charts to help visualize your data as well as the libraries and packages available for R and Python. Start this course today to improve your data literacy!
Data Exploration and Visualization
Data Exploration and Visualization Learning Outcomes
Exploratory data analysis
Data visualization with R
Data visualization with Python
Data Exploration and Visualization Lesson Summary
Building Models in Azure ML
Building Models in Azure ML Learning Outcomes
Creating and Scoring Models
Modeling in R
Modeling in Python
Model Evaluation and Comparison
Building Models in Azure ML Lesson Summary
Upon successful completion of this course the learner will be able to:
- Discuss the importance of data exploration
- Recognize what you use for data visualizations in R
- Recognize what you use for data visualizations in Python
- Identify the different types of plots or charts you can use to visualize your data
- Discuss the process of feature engineering
- Identify features and methods available in R for creating Machine learning models
- Identify features and methods available in Python for creating Machine learning models
- Outline the process and options for evaluating your machine learning model
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