Johns Hopkins University
Data Science: Statistics and Machine Learning Specialization
Johns Hopkins University

Data Science: Statistics and Machine Learning Specialization

Taught in English

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Roger D. Peng, PhD
Brian Caffo, PhD
Jeff Leek, PhD

Instructors: Roger D. Peng, PhD

35,731 already enrolled

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.6

(593 reviews)

Intermediate level
Some related experience required
3 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Perform regression analysis, least squares and inference using regression models.

  • Build and apply prediction functions

  • Develop public data products

Details to know

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.6

(593 reviews)

Intermediate level
Some related experience required
3 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 5 course series

Statistical Inference

Course 154 hours4.2 (4,425 ratings)

What you'll learn

  • Understand the process of drawing conclusions about populations or scientific truths from data

  • Describe variability, distributions, limits, and confidence intervals

  • Use p-values, confidence intervals, and permutation tests

  • Make informed data analysis decisions

Skills you'll gain

Category: Statistics
Category: Statistical Inference
Category: Statistical Hypothesis Testing

Regression Models

Course 253 hours4.4 (3,341 ratings)

What you'll learn

  • Use regression analysis, least squares and inference

  • Understand ANOVA and ANCOVA model cases

  • Investigate analysis of residuals and variability

  • Describe novel uses of regression models such as scatterplot smoothing

Skills you'll gain

Category: Random Forest
Category: Machine Learning (ML) Algorithms
Category: Machine Learning
Category: R Programming

Practical Machine Learning

Course 38 hours4.5 (3,241 ratings)

What you'll learn

  • Use the basic components of building and applying prediction functions

  • Understand concepts such as training and tests sets, overfitting, and error rates

  • Describe machine learning methods such as regression or classification trees

  • Explain the complete process of building prediction functions

Skills you'll gain

Category: Interactivity
Category: Plotly
Category: Web Application
Category: R Programming

Developing Data Products

Course 410 hours4.6 (2,253 ratings)

What you'll learn

  • Develop basic applications and interactive graphics using GoogleVis

  • Use Leaflet to create interactive annotated maps

  • Build an R Markdown presentation that includes a data visualization

  • Create a data product that tells a story to a mass audience

Skills you'll gain

Category: Data Science
Category: Machine Learning
Category: R Programming
Category: Natural Language Processing

Data Science Capstone

Course 55 hours4.5 (1,224 ratings)

What you'll learn

  • Create a useful data product for the public

  • Apply your exploratory data analysis skills

  • Build an efficient and accurate prediction model

  • Produce a presentation deck to showcase your findings

Skills you'll gain

Category: Model Selection
Category: Generalized Linear Model
Category: Linear Regression
Category: Regression Analysis

Instructors

Roger D. Peng, PhD
Johns Hopkins University
37 Courses1,572,654 learners
Brian Caffo, PhD
Johns Hopkins University
30 Courses1,597,805 learners

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