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Microsoft Future Ready: Research Methods on Python Programming

Fundamentals of developing a good question to designing good data collection strategies to putting results in context.

  • Duration

    3 weeks

  • Weekly study

    5 hours
Overview
Requirements

You will be familiar with the Python Programming concepts and techniques

Data scientists are often trained in the analysis of data. However, the goal of data Data scientists are often trained in the analysis of data. However, the goal of data science is to produce a good understanding of some problem or idea and build useful models on this understanding. Because of the principle of “garbage in, garbage out,” it is vital that a data scientist know how to evaluate the quality of information that comes into a data analysis. This is especially the case when data are collected specifically for some analysis (e.g., a survey).

In this course, you will learn the fundamentals of the research process—from developing a good question to designing good data collection strategies to putting results in context. Although a data scientist may often play a key part in data analysis, the entire research process must work cohesively for valid insights to be gleaned.

Developed as a powerful and flexible language used in everything from Data Science to cutting-edge and scalable Artificial Intelligence solutions, Python has become an essential tool for doing Data Science and Machine Learning. With this edition of Data Science Research Methods, all of the labs are done with Python, while the videos are language-agnostic. If you prefer your Data Science to be done with R, please see Data Science Research Methods: R Edition.

WHAT YOU’LL LEARNscience is to produce a good understanding of some problem or idea and build useful models on this understanding. Because of the principle of “garbage in, garbage out,” it is vital that a data scientist know how to evaluate the quality of information that comes into a data analysis. This is especially the case when data are collected specifically for some analysis (e.g., a survey).

What topics will you cover?

  • The Research Process
  • Planning for Analysis
  • Research Claims
  • Measurement
  • Correlational and Experimental Design

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Data analysis and inference
  • Data science research design
  • Experimental data analysis and modeling

Who is the course for?

After completing this course, you will be familiar with the following concepts and techniques:

Data analysis and inference Data science research design Experimental data analysis and modeling

Who developed the course?

CloudSwyft Global Systems, Inc.

CloudSwyft has partnered with the top global technology companies to deliver cutting edge digital skills learning across the modern workplace.

Learning on FutureLearn

Your learning, your rules

  • Courses are split into weeks, activities, and steps to help you keep track of your learning
  • Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
  • Stay motivated by using the Progress page to keep track of your step completion and assessment scores

Join a global classroom

  • Experience the power of social learning, and get inspired by an international network of learners
  • Share ideas with your peers and course educators on every step of the course
  • Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others

Map your progress

  • As you work through the course, use notifications and the Progress page to guide your learning
  • Whenever you’re ready, mark each step as complete, you’re in control
  • Complete 90% of course steps and all of the assessments to earn your certificate

Want to know more about learning on FutureLearn? Using FutureLearn