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Updated in [May 25th, 2023]
What skills and knowledge will you acquire during this course?
Learners in this course will acquire a range of skills and knowledge in the field of data analysis. They will develop a solid understanding of statistical and computational tools, including hypothesis testing, regression, and gradient descent methods. Additionally, they will learn about various models and methods used to analyze specific types of data in different domains, such as epigenetic codes, criminal networks, prices and economics, and environmental data.
Throughout the course, learners will have the opportunity to work with real data sets from these domains and apply their skills to analyze and interpret the data. They will also gain experience in presenting their findings through written reports and engaging in discussions with their peers.
By completing this course, learners will acquire the necessary skills to become informed and effective practitioners of data science. This course is part of the MITx MicroMasters Program in Statistics and Data Science, which provides learners with a comprehensive education in the field. Successful completion of the program, including this course and three others, will earn learners a MicroMasters credential that demonstrates their proficiency in data science. This credential can be used to enhance career prospects or as a stepping stone towards pursuing a PhD or Master's degree in data science at MIT or other universities.
How does this course contribute to professional growth?
This course contributes to professional growth by providing learners with the necessary skills and knowledge to become proficient practitioners of data science. By combining foundational and practical skills in mathematics, statistics, machine learning, problem solving, programming, visualization, and communication, learners will be able to ask and answer questions using real data. The course covers common statistical and computational tools, as well as specific models and methods for analyzing different types of data in various domain areas. Learners will have the opportunity to analyze real data sets and present their findings in written reports, while also engaging in discussions with peers to address relevant and practical issues.
Is this course suitable for preparing further education?
The course "Data Analysis: Statistical Modeling and Computation in Applications" is suitable for preparing further education. It is part of the MITx MicroMasters Program in Statistics and Data Science, which is at a similar pace and level of rigor as an on-campus course at MIT. Completing this course and three others from MITx, along with passing a virtually-proctored exam, will earn learners a MicroMasters credential. This academic credential demonstrates proficiency in data science and can accelerate the path towards an MIT PhD or a Master's at other universities.