Embark on a comprehensive journey through statistics, regression models, machine learning, and data product development in the "Data Science: Statistics and Machine Learning" course. This specialization, offered by Johns Hopkins University, builds upon foundational knowledge to equip learners with advanced skills and practical expertise in the dynamic field of data science.
The course covers a range of essential topics, including statistical inference, regression analysis, machine learning, and the creation of interactive data products. Through a series of five engaging modules, participants will delve into the intricacies of drawing conclusions from data, understanding variability and distributions, building prediction functions, developing public data products, and creating efficient and accurate prediction models. The Capstone Project presents an opportunity for learners to apply their acquired skills by developing a data product using real-world data, thereby showcasing their mastery of the material.
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This specialization delves into statistical inference, regression models, practical machine learning, developing data products, and the Capstone Project, providing a comprehensive and practical understanding of advanced data science concepts.
Understand the process of drawing conclusions about populations or scientific truths from data. Describe variability, distributions, limits, and confidence intervals, and make informed data analysis decisions. Gain proficiency in using p-values, confidence intervals, and permutation tests.
Explore regression analysis, least squares, and inference. Understand ANOVA and ANCOVA model cases, investigate analysis of residuals and variability, and describe novel uses of regression models such as scatterplot smoothing.
Learn the basic components of building and applying prediction functions. Understand concepts such as training and test sets, overfitting, and error rates. Describe machine learning methods such as regression or classification trees and explain the complete process of building prediction functions.
Develop basic applications and interactive graphics using GoogleVis, create interactive annotated maps with Leaflet, and build an R Markdown presentation that includes data visualization. Create a data product that tells a story to a mass audience.
Create a useful data product for the public, apply exploratory data analysis skills, build an efficient and accurate prediction model, and produce a presentation deck to showcase your findings in the Capstone Project.
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