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Programming for Data Science with R

3 Months

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Brief Introduction

The Programming for Data Science Nanodegree program offers you the opportunity to learn the most important programming languages used by data scientists today. Get your start into the fascinating field of data science and learn R, SQL, terminal, and git with the help of experienced instructors.

Course Summary

Learn how to program for data science using R. This course will teach you the basics of programming in R and how to use it for data analysis, visualization, and manipulation.

Key Learning Points

Focuses on programming in R specifically for data science
Covers data analysis, visualization, and manipulation
Includes real-world projects to apply what you've learned

Learning Outcomes

Understand the basics of programming in R
Use R for data analysis, visualization, and manipulation
Complete real-world projects to showcase your skills

Prerequisites or good to have knowledge before taking this course

Basic understanding of statistics
No prior programming experience required

Course Difficulty Level

Beginner

Course Format

Online
Self-paced

Similar Courses

Python for Data Science
Data Analyst

Related Education Paths

Notable People in This Field

Hadley Wickham
Hilary Parker

Related Books

Description

Prepare for a data science career by learning the fundamental data programming tools: R, SQL, command line, and git.

Knowledge

This is an introductory program that is not designed to prepare you for a specific job. However, as a graduate of this program, you will be proficient in the programming skills used in many data analysis and data science roles, including R, SQL, Terminal, and Git.

Outline

Learn the programming fundamentals required for a career in data science. By the end of the program, you will be able to use R, SQL, Command Line, and Git. Learn to code with R, SQL, Command Line, and Git to solve problems with data.

Summary of User Reviews

Discover the power of R programming for data science with this comprehensive nanodegree program. Students have found this course to be a valuable resource for gaining skills in data analysis and visualization, while also learning how to use R for machine learning and statistical modeling.

Key Aspect Users Liked About This Course

The course material is well-organized and easy to follow.

Pros from User Reviews

Excellent instructors with a wealth of knowledge and experience.
The curriculum is up-to-date and covers a wide range of topics.
The projects and assignments are challenging but rewarding.
The community support is strong and helpful.
The resources and tools provided are top-notch.

Cons from User Reviews

Some students have found the course to be too fast-paced and difficult to keep up with.
The course may not be suitable for complete beginners with no prior programming experience.
The grading and feedback on projects can be inconsistent.
The price of the course may be high for some learners.
There is a heavy emphasis on R programming, which may not be relevant for some data science roles.

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