Although data scientists often focus on data analysis, they must understand the research process to gain valid insights from this work. This course covers the fundamentals of data research - from developing a good question to designing good data collection strategies that will put your results in context. Upon completion of the course, you will have a basic understanding of data analysis and inference, and data science research design. You’ll also explore experimental data analysis and modelling. Understand the data research process Data is only as good as its source - without this key information, it can be difficult to query the validity or context of your data, or make robust statements as a result of your analysis. This course will help you to understand the research process and grow your knowledge of the planning required for high quality analysis. Build the confidence to query your data You’ll build your understanding of the process so that you can properly query your own and external data for more robust analysis. That includes understanding how to partition data, test hypothesis, and use inference. Apply Python programming knowledge in your labs In this course, all of the labs are done with Python, while the videos are language-agnostic. By the end, you’ll understand the basics of the research process, you’ll be able to plan for analysis, and you’ll know the basics of correlational and experimental design. Start a career in data science Developing practical skills across research methods and Python programming will mean that you have some of the most in-demand skills within data science. Jobs in the industry have grown 37% in the last three years, while salaries have grown 11-14% year on year, making it an excellent area to start or change careers today.
The techniques and tools covered in Microsoft Future Ready: Data Science Research Methods on Python Programming are most similar to the requirements found in Business Analyst job advertisements.
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