Data Science Specialization

Started Nov 13

Data Science Specialization

Data Science Specialization

Launch Your Career in Data Science. A nine-course introduction to data science, developed and taught by leading professors.

About This Specialization

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

Created by:

Industry Partners:

courses
10 courses

Follow the suggested order or choose your own.

projects
Projects

Designed to help you practice and apply the skills you learn.

certificates
Certificates

Highlight your new skills on your resume or LinkedIn.

Courses
Beginner Specialization.
No prior experience required.
  1. COURSE 1

    The Data Scientist’s Toolbox

    Current session: Nov 13
    Commitment
    1-4 hours/week
    Subtitles
    English, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, Hebrew

    About the Course

    In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components
  2. COURSE 2

    R Programming

    Current session: Nov 13
    Subtitles
    English, French, Japanese, Chinese (Simplified)

    About the Course

    In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language
  3. COURSE 3

    Getting and Cleaning Data

    Current session: Nov 13
    Subtitles
    English, Russian, French, Chinese (Simplified)

    About the Course

    Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also c
  4. COURSE 4

    Exploratory Data Analysis

    Current session: Nov 13
    Subtitles
    English, Chinese (Simplified)

    About the Course

    This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques
  5. COURSE 5

    Reproducible Research

    Current session: Nov 13
    Commitment
    4-9 hours/week
    Subtitles
    English

    About the Course

    This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code
  6. COURSE 6

    Statistical Inference

    Current session: Nov 13
    Subtitles
    English

    About the Course

    Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of des
  7. COURSE 7

    Regression Models

    Current session: Nov 13
    Subtitles
    English

    About the Course

    Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. Thi
  8. COURSE 8

    Practical Machine Learning

    Current session: Nov 13
    Subtitles
    English

    About the Course

    One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical appli
  9. COURSE 9

    Developing Data Products

    Current session: Nov 13
    Subtitles
    English

    About the Course

    A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creat
  10. COURSE 10

    Data Science Capstone

    Current session: Nov 13
    Commitment
    4-9 hours/week
    Subtitles
    English

    About the Capstone Project

    The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, an

Creators

  • Johns Hopkins University

    Johns Hopkins University is recognized as a destination for excellent, ambitious scholars and a world leader in teaching and research. The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

    The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

  • Roger D. Peng, PhD

    Roger D. Peng, PhD

    Associate Professor, Biostatistics
  • Brian Caffo, PhD

    Brian Caffo, PhD

    Professor, Biostatistics
  • Jeff Leek, PhD

    Jeff Leek, PhD

    Associate Professor, Biostatistics

FAQs

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