Microsoft Future Ready: Data Science Research Methods on Python Programming

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Course Features

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Duration

3 weeks

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Delivery Method

Online

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Available on

Lifetime Access

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Accessibility

Mobile, Desktop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

5 hours per week

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Teaching Type

Self Paced

Course Description

Data scientists are often focused on data analysis but they need to understand the research process in order to get valid insights. This course will cover the basics of data research, from designing a question to analyzing your results. After completing the course, you will be able to understand basic data analysis, inference and design of data science research. The course will also cover experimental data analysis and modeling. Data is only as good and reliable as the source. Without this information it can be hard to question the validity of your data or make strong statements as a result. This course will teach you how to plan for high-quality analysis and the process of research. This course will help you to understand the process and be able to query external and your own data more effectively for robust analysis. This includes how to partition data and test hypothesis. All labs in this course are performed with Python. The videos, however, are language-independent. You'll have a good understanding of the research process and be able plan for analysis. Additionally, you will know the basics about correlational and experimental design. You will be able to use your skills in Python programming and research methods to develop data science skills that are highly sought after. The industry has seen a 37% increase in jobs over the past three years and a rise in salaries of 11-14% annually. This makes it a great place to begin or change your career.

Course Overview

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Alumni Network

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Applied data analysis and inference

Applied data science research design

Experimented with data analysis and modeling

Target Students

This self-paced course is designed for learners with a basic knowledge of maths *some programming experience – Python is preferred *a willingness to learn through exploration and perseverance

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