Data Science: Statistics and Machine Learning

Johns Hopkins University via Coursera Specialization

Coursera Specialization based on 619 ratings

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Overview

The course “Data Science: Statistics and Machine Learning” offers a comprehensive introduction to the foundational principles of statistics and machine learning, two core pillars of modern data science. Learners will explore essential statistical concepts such as probability distributions, hypothesis testing, regression, and exploratory data analysis, which provide the groundwork for understanding data behavior and variability. Building on this, the course dives into machine learning techniques including supervised and unsupervised learning, classification, clustering, decision trees, and model evaluation. Emphasis is placed...

Syllabus

Course 1: Statistical Inference- Offered by Johns Hopkins University. Statistical inference is the process of drawing conclusions about populations or scientific truths from ... Enroll for free.Course 2: Regression Models- Offered by Johns Hopkins University. Linear models, as their name implies, relates an outcome to a set of predictors of interest using ... Enroll for free.Course 3: Practical Machine Learning- Offered by Johns Hopkins University. One of the most common tasks performed by data scientists and data analysts are prediction and machine ... Enroll for free.Course 4: Developing Data Products- Offered by Johns Hopkins University. A data product is the production output from a statistical analysis. Data products automate complex ... Enroll for free.Course 5: Data Science Capstone- Offered by Johns Hopkins University. The capstone project class will allow students to create a usable/public data product that can be used ... Enroll for free.