Data Science - Working with Data - Revised
Learn about working with and preparing data for your data science project.
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In this online course Data Science - Working with Data you will learn about the flow of data in Azure ML. you will learn about joins and the R and Python languages. You will learn about preparing your data, continuous and categorical variables. You will learn about quantization and scaling.
The course starts off with introducing you to the Data flow in Azure ML,where you will learn about batch and real time processing. You will learn about different types of joins you can use on your data. You will learn about R and Python programming languages and what they can do for a data science project.
In the second module, you will be introduced to Data sampling and Preparation. You will learn about continuous and categorical variables. You will learn what quantization is and can do for your data. You will learn about Data munging and how it’s the most time-consuming part of a data science project. You will learn about handling errors and outliners in your project. You will learn about scaling using either python, R or Azure ML module for scaling.
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Having completed this course you will be able to:
- Describe the flow of data in a Azure ML experiment
- Discuss the differences between using R and Python
- Identify which programming language suits you better R or Python
- Describe installing both R and Python in your Azure ML environment
- Discuss data preparation also known as data munging to prepare data for your project
- Explain what quantizing your variables is and does
- Explain how to deal with missing values in your data sets
- Describe why you should scale your variables
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