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Data Science - Working with Data

Data Science
Free Course

Learn about data types, data sampling methods and data preparation techniques using R and Python programming in data science.

  • Duration

    2-3 Hours
  • Assessment

    Yes
  • Certification

    Yes
  • Publisher

    Channel 9
Description Outcome Certification View course modules

The course Data Science - Working with Data will introduce you to methods for preparing data, how to differentiate between continuous and categorical variables, and what quantization and scaling involve.

The course begins by introducing you to the data flow in Azure ML, you will learn about batch and real time processing, and the different types of joins you can use on your data. You will learn about R and Python programing languages and how they can be used in a data science project.

Next, you will be introduced to data sampling and preparation. You will learn about continuous and categorical variables, and what quantization can do for your data. The course will teach you about data munging which is the process of manually converting or mapping data from one "raw" form into another format, and how it is the most time-consuming part of a data science project. You will also learn about handling errors and outliers in your project. Finally, you will learn about scaling using either Python, R or Azure ML module for scaling.

This course will be of great interest to those who wish to learn about data science.

Prerequisites: To complete this course successfully you need a basic knowledge of mathematics, including linear algebra. Additionally, some programming experience, ideally in either R or Python, is assumed and you will need to have completed the previous course Introduction to Data Science.

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.

All Alison courses are free to enrol, study and complete. To successfully complete this Certificate course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Certificate course, you have the option to acquire official Certification, which is a great way to share your achievement with the world. Your Alison Certification is:

Ideal for sharing with potential employers - include it in your CV, professional social media profiles and job applications
An indication of your commitment to continuously learn, upskill and achieve high results
An incentive for you to continue empowering yourself through lifelong learning

Alison offers 3 types of Certification for completed Certificate courses:

Digital Certificate - a downloadable Certificate in PDF format, immediately available to you when you complete your purchase
Certificate - a physical version of your officially branded and security-marked Certificate, posted to you with FREE shipping
Framed Certificate - a physical version of your officially branded and security-marked Certificate in a stylish frame, posted to you with FREE shipping

All Certification is available to purchase through the Alison Shop. For more information on purchasing Alison Certification, please visit our faqs. If you decide not to purchase your Alison Certification, you can still demonstrate your achievement by sharing your Learner Record or Learner Achievement Verification, both of which are accessible from your Dashboard. For more details on our Certification pricing, please visit our Pricing Page.

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