Microsoft Future Ready: Data Science Research Methods Using Python Programming
Posted 2 years ago by CloudSwyft Global Systems, Inc.
During this course, you’ll learn the fundamentals of data research including developing good research questions, designing data collection strategies, analysing data and putting results in context. You’ll also understand how data scientists play a key role in the research phase, not just the analysis, and how this will help extract valid insights from your data.
Understand data collection methods and the research process
To help you build the confidence to accurately analyse your data, this course will take you through the full research process. You’ll grow your knowledge of the planning needed for high quality data analysis and learn how to properly query your data for a robust analysis. This includes understanding how to test hypotheses, how to partition data and use inference in order to extra valid results.
Learn how to use and apply Python programming knowledge
During the course, you’ll use Python programming, an essential tool for data science and machine learning. All labs are done with Python, while the videos are language-agnostic, giving you plenty of opportunity to hone your skills with this powerful tool.
Advance your skills in data science
By the end of the course, you’ll understand the research process and develop practical skills across research methods and Python programming, a flexible language used in everything from data science to cutting-edge and scalable AI solutions.
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.
If you want to deepen your understanding of this subject, you may also be interested in these courses by the same provider:
- Microsoft Future ready: Ethics and Law in Data and Analytics
- Microsoft Future Ready: Principles of Machine Learning with Python Programming
- Microsoft Future Ready: Designing and Implementing an Azure AI Solution
Learners will benefit from:
- A basic knowledge of math.
- Some programming experience – Python is preferred.
- A willingness to learn through exploration and perseverance.
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.
If you want to deepen your understanding of this subject, you may also be interested in these courses by the same provider:
- 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
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