Online Course – Johns Hopkins University Certified Professional Internship in Data Science

A wide range of quality products at affordable prices. Discover our innovations and services that will solve your every need. Order now and join satisfied customers!

Suggested by: Coursera (What is Coursera?)

Start your Coursera.com free trial today
קורס אונליין - התמחות מקצועית מוסמכת במדע הנתונים של Johns Hopkins University

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Receiving data
  • Data cleaning and exploration
  • Programming in R language
  • Conducting reproducible research
  • Installing tools
  • Programming in R language
  • Data Cleanup
  • Performing analyses
  • Peer review tasks

What you will learn in the course

Courses for which the course is suitable

  • Data Analyst
  • Data Scientist
  • Data software developer
  • Statistics expert
  • Machine learning model developer
  • Data scientist
  • Data Project Manager
  • Data Science Consultant
  • Data visualization developer
  • R programmer

Internship – a five-part course series

Ask the right questions, manipulate data sets, and draw visualizations to communicate results.

This specialization covers basic tools and methods in data science, including:

  • Receiving data
  • Data cleaning and exploration
  • Programming in R language
  • Conducting reproducible research

Learners who complete this specialization will be prepared to move on to Data Science: Statistics and Machine Learning, where they will build a data product using real-world data.

The five courses in the specialization

The courses provide the first part of the specialization in data science, and are suitable for those who want to start and complete the basic part before moving on to more advanced topics.

Applied Learning Project

During the Data Science: R Fundamentals specialization, students will complete projects at the end of each course. The projects include:

  • Installing tools
  • Programming in R language
  • Data Cleanup
  • Performing analyses
  • Peer review tasks

Details of the courses that make up the specialization

The Data Scientist Toolkit

Course 1: Installing R and Github

Duration: 18 hours
Rating: 4.6 (33,917 ratings)

  • Install R, R-Studio, Github, and other useful tools
  • Understand the data, problems, and tools used by data analysts
  • Explain essential concepts in research design
  • Create a repository on Github

Course 2: Programming in R

Duration: 57 hours
Rating: 4.5 (22,239 ratings)

  • Understand basic programming concepts
  • Install statistical programming software
  • Use loop functions and debugging tools in R
  • Collect detailed information using R profiler

Course 3: Data Acquisition and Data Cleaning

Duration: 19 hours
Rating: 4.5 (8,060 ratings)

  • Understand common data storage systems
  • Use data cleansing principles to make data “clean”
  • Use R to manipulate text and dates
  • Obtain available data from the internet, APIs and databases

Course 4: Exploratory Data Analysis

Duration: 54 hours
Rating: 4.7 (6,065 ratings)

  • Understand analytical graphs and the basic plotting system in R
  • Use advanced graphic systems such as the matrix system
  • Create graphical displays of highly dimensional air data
  • Apply cluster analysis techniques to detect patterns in data

Course 5: Reproducible Research

Duration: 7 hours
Rating: 4.6 (4,172 ratings)

  • Organize data analysis to make it more reproducible
  • Record reproducible data analysis using knitr
  • Assess the reproducibility of the analysis project
  • Publish retrievable web documents using Markdown

Related products