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Introduction to Data Science

Data Science
Free Course

Learn how to extract information from data using data science methods such as classification and clustering algorithms.

  • Duration

    2-3 Hours
  • Assessment

  • Certification

  • Publisher

    Channel 9
Description Outcome Certification View course modules

Data science is the key to modern business. With strong data science skills, you can turn massive spreadsheets of numbers that nobody can understand into clear information. This will allow you to better predict market trends, social changes, investment strategies, even the weather. That’s an incredibly valuable skill with almost infinite uses. Consequently, data scientists are in demand around the world and have very profitable, secure, and interesting careers.

This course is designed to give you all the skills you need to enter the world of data science and get those rewards. The course will first introduce you to the field of data science and the methodologies used in the data science process. You will then learn some of the most important algorithms used in machine learning. Next, the course will guide you through regression and classification, and through two of the most commonly used clustering algorithms in data science. You will also be introduced to Azure Machine Learning(ML) Studio and be shown why you would use Azure ML Studio for your data science projects.

By the end of the course, you will have a strong understanding of data science and be much closer to starting your career in this field, or just using these skills to gain some valuable information for your business. That’s not a bad reward for a course that only takes 3 hours. As a prerequisite for this course, you will need to have some programming in Python knowledge, but don’t worry! You can gain this knowledge with our free Introduction to Programming with Python course. If you don’t already have Python, check out the course, and if you do, get started on your exploration of data science today!

Having completed this course you will be able to: - Describe what data science is used for. - List the stages in the data science process. - Explain what machine learning is and the parts that make it up. - Discuss the use of regression and the different types of regression. - Describe the different types of classification algorithms available for you to use. - Describe how the two most popular clustering algorithms work. - Discuss why you would use Azure ML for your data science projects.

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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