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Johns Hopkins University

Data Science

Johns Hopkins University via Coursera Specialization

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
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.

Syllabus

Course 1: The Data Scientist’s Toolbox
- Offered by Johns Hopkins University. In this course you will get an introduction to the main tools and ideas in the data scientist's ... Enroll for free.

Course 2: R Programming
- Offered by Johns Hopkins University. In this course you will learn how to program in R and how to use R for effective data analysis. You ... Enroll for free.

Course 3: Getting and Cleaning Data
- Offered by Johns Hopkins University. Before you can work with data you have to get some. This course will cover the basic ways that data can ... Enroll for free.

Course 4: Exploratory Data Analysis
- Offered by Johns Hopkins University. This course covers the essential exploratory techniques for summarizing data. These techniques are ... Enroll for free.

Course 5: Reproducible Research
- Offered by Johns Hopkins University. This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible ... Enroll for free.

Course 6: 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 7: 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 8: 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 9: 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 10: 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.

Courses

Taught by

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

Reviews

4.6 rating, based on 9 Class Central reviews

Start your review of Data Science

  • Dave Hurst
    Coursera Data Science Specialization (John Hopkins Universitu) Successfully completing the inaugural capstone for the JHU/Coursera data science track was a thrill for me. The timing for the first track couldn't have been better, as at the time I wa…
  • Anonymous
    Great for folks new to computer science, data science, coding! The courses are great. There's videos and resources for learning, quizzes to make sure you're retaining information, and at least one assignment demonstrating your learning per course. T…
  • Anonymous
    An entry course that opens up your data science career I strongly recommend this course to anyone who has taken statistics/economics/data analysis courses at college and would like to get some training in big-data analysis. My training background is…
  • Anonymous
    Very good certificate for starting a career in Data Science
    I think this certificate is a very good way of starting a career in Data Science. It covers all the themes you need for developing in R with statistical knowledge. It also has more lectures for curious people. The coursera staff is always helping and the platform is amazing.
  • Good intro to data science for the well prepared Suppose you: - have programming experience (preferably C, C++, C# or Java ) - have a solid knowledge of the basics of statistics (descriptive and inferential). then this specialization is a great int…
  • Anonymous
    Great introductory Data Science course This course covers all the major aspects of the Data Science field. The instructors are reasonably good. However, some of the statistics aspects will be easier if you have some basic knowledge. (I took a basic…
  • Anonymous
    Informative and Valuable course with great resources
    This course is a great introduction to data science and related disciplines like analytics, statistics, machine learning etc.
    Stats and R programming can be challenging for those who do not have a stats or programming background. All in all, this was a very informative learning experience.
  • Anonymous
    4 stars all around
    I learned what I needed to know to manage and hire data scientists and coordinate well with statisticians. I might have completed the series (only skipped the capstone) if the capstone had been a project more related to my work (mapping).
  • Anonymous
    interesting capstone
    The capstone project is good experience to apply the basics of data science and machine learning. The courses covered the major topics of statistics along with R programming.

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