Introduction to Data Science Specialization

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Course Features

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Duration

4 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Effort

3 hours per week

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Teaching Type

Self Paced

Course Description

Are you interested in data science but are unsure where to begin? This 4-course IBM Specialization will give you the foundational skills that data scientists need to be successful in a career or further learning in this field. This Specialization will explain what data science is, and what data scientists do. Data science is applicable across all fields. You will also learn how data analysis can be used to help you make data-driven decisions. This Specialization will help you to get started in your field of work without having to know anything about programming languages or computer science. This Specialization will help you understand concepts such as big data, statistical analysis and relational databases. You will also be familiar with the various open-source tools and data science programs used in data scientists like Jupyter Notebooks and RStudio. To learn how to tackle data science problems, you will be able to apply the skills and knowledge gained to real-world data sets through hands-on projects and labs. You will receive a Coursera Specialization completion certificate and a digital badge from IBM that recognizes you as a specialist on data science foundations. This Specialization can be used to earn the IBM Data Science Professional Certificate.

Course Overview

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International Faculty

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Develop the mindset to work like a data scientist, and follow a methodology to tackle different types of data science problems

Gain hands-on familiarity with common data science tools including JupyterLab, R Studio, GitHub and Watson Studio

Write SQL statements and query Cloud databases using Python from Jupyter notebooks

Describe what data science and machine learning are, their applications & use cases, and various types of tasks performed by data scientists

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