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

Data Science: Statistics and Machine Learning Specialization

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

Instructors: Roger D. Peng, PhD

Sponsored by Johns Hopkins University

37,413 already enrolled

Get in-depth knowledge of a subject
4.6

(607 reviews)

Intermediate level
Some related experience required
3 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(607 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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Taught in English

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  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Johns Hopkins University
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Specialization - 5 course series

Statistical Inference

Course 154 hours4.2 (4,434 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: Probability & Statistics
Category: Probability Distribution
Category: Statistical Programming
Category: General Statistics
Category: Mathematics

Regression Models

Course 253 hours4.4 (3,358 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: Probability & Statistics
Category: Regression
Category: Statistical Programming
Category: General Statistics
Category: Data Analysis
Category: Problem Solving

Practical Machine Learning

Course 38 hours4.5 (3,246 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: Algorithms
Category: Applied Machine Learning
Category: Data Analysis
Category: Human Learning
Category: Machine Learning
Category: Machine Learning Algorithms

Developing Data Products

Course 410 hours4.6 (2,255 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: Computer Programming
Category: Data Analysis
Category: Statistical Programming
Category: Computer Graphics
Category: Data Visualization Software
Category: Data Visualization

Data Science Capstone

Course 55 hours4.5 (1,226 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: Data Analysis
Category: Human Learning
Category: Machine Learning
Category: Machine Learning Algorithms
Category: Problem Solving
Category: Computer Programming

Instructors

Roger D. Peng, PhD
Johns Hopkins University
37 Courses1,608,001 learners
Brian Caffo, PhD
Johns Hopkins University
30 Courses1,633,988 learners

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