Course description
Data Analysis with R: learn exploratory data analysis (EDA)
This course is designed to guide learners through a clear approach to data analysis for the purpose of summarizing and visualizing the most important characteristics of a given data set. Learners will gain a hands-on understanding of how to work with Exploratory Data Analysis (EDA) for highlighting structure and variables, considering the origin of a dataset, intuiting the best course of action and determining how to move forward with formal statistical methods.
Upon completion of this course, participants will understand how to:
- Conduct data analysis via EDA as a journey and a way to explore data
- Explore data at multiple levels using appropriate visualizations
- Acquire statistical knowledge for summarizing data
- Demonstrate curiosity and skepticism when performing data analysis
- Develop intuition around a data set and understand how the data was generated
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Upcoming start dates
Who should attend?
This Data Analysis with R programming is designed for anyone hoping to gain a better understanding of EDA as a means of data exploration, create plots and summarize findings in a meaningful way.
Pre-Requisites
This course makes no formal requirements, however a background in statistics and familiarity with CS and Math topics such as comparison and logical operators, if else statements, square roots, logarithms and exponentials would all be helpful.
Find out if this course is right for you - request more information here!
Training content
Projects
- Jump into a new dataset. Explore, create plots, and summarize the fascinating things you find.
Lessons:
- What is EDA? (1 hour)
- R Basics (3 hours)
- Explore One Variable (4 hours)
- Problem Set 3 (2 hours)
- Explore Two Variables (4 hours)
- Problem Set 4 (2 hours)
- Explore Many Variables (4 hours)
- Problem Set 5 (2 hours)
- Diamonds and Price Predictions (2 hours)
Final Project (10+ hours)
At this point participants have worked with simulated Facebook data. Now, it's time to build your own exploratory data analysis. Choose one data set to explore (one provided by Udacity or your own) and create a RMD file that uncovers the patterns, anomalies and relationships of the data set.
Costs
It is free to start this Introduction to Java Programming course
Estimated time for completion assuming 6 hours per week: Approx. 2 months
2-Week Free Trial: Love it or Leave it
All Udacity courses are offered with a two-week free trial. Learners will have plenty of time to make sure that the program fits their needs. If it's not working out for any reason - user can cancel their subscription fee of charge.