Microsoft Future Ready: Data Science Research Methods Using 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

This course is part the Ethics Laws and Implementing a AI Solution on Microsoft Azure ExpertTrack. It will help you understand and apply legal and ethical frameworks in data analysis, AI, and data research.

This course will teach you the basics of data research, including how to develop good research questions, design data collection strategies, analyse data, and put results into context. Data scientists are crucial in research, not just analysis. This course will teach you how to extract valuable insights from your data.

This course will help you gain confidence in the ability to analyse your data accurately. This includes how to test hypotheses and how to partition data to get additional valid results.

You will learn Python programming during the course. This is an important tool for machine learning and data science. The labs are all done in Python. However, the videos can be viewed in any language. This gives you ample opportunity to improve your Python programming skills.

You will be able to understand the research process by the end of this course and have practical skills in research methods and Python programming. This flexible language is used for everything data science related, as well as cutting-edge and scalable AI solutions.

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

Demonstrated an understanding of the planning aspect around data as well as research practices

Explained the different types of claims

Interpreted and understand the different designs

Examined reliability and validity

Identified the goals of research

Target Students

This self-paced course is designed for learners with an interest in using data for research, and methods of wrangling, compiling and presenting data for research

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