Data Analysis with R
About This Course
Data analysis becomes essential part of every day life. After this course, you will be able to conduct data analysis task yourself. Gain insights from the data.
Will be using R – widely used tool for data analysis and visualization.
Data Science project will be core course component – will be working on it after mastering all necessary background. Doing data analysis from ground up to final insights.
Starting from very basics we will move to various input and output methods. Yet another important concept – visualization capabilities. After the course you will be able to produce convincing graphs.
Background behind functional programming will be presented – including building your own functions.
After finishing the course you will feel much more comfortable programming in other languages as well. This is because R being fully empowered programming language itself. Main programming concepts presented:
- Various data types
- Conditional statements
- For and While loops
No previous programming knowledge required.
Finally, data mining and data science techniques in R delivered in clear fashion together with assignments to make sure you understand topics. Main statistical capabilities behind data science covered.
Course is interactive. Specific topic covered in each lecture. Each lecture includes multiple examples. All material covered in videos are available for download! This way student is able to program himself – break things and fix them.
Students will finish course in approximately 7-10 days working 3 hours per day. Time spent working individually included.
After each section assignment should be completed to make sure you understand material in the section.After you are ready with the solution – watch video explaining concepts behind assignment.
I will be ready to give you a hand by answering your questions.
Finally, this course is specifically designed to get up to speed fast. Biggest emphasis put on real examples and programming yourself. This distinguishes this course from other material available online – usual courses includes vague slides and long textbooks with no real practise.
What are the requirements?
- Internet connection
- Computer with Mac, Windows or Linux
- Desire to master data analysis
What am I going to get from this course?
- Data Science project at the end of the course
- Learn programming concepts
- Conduct your independent data analysis
- Learn by examples
- Assignments after each section
- Have fun by doing all above
- Introduction to data science and analytics
What is the target audience?
- Beginners data analysts
- Users of other analysis tools
- Those who loves data
|Section 1: Introduction|
|Section 2: Getting feet wet|
Working with directories
|Section 3: Data types|
|Section 4: External Data|
|Section 5: Control structures|
|Section 6: Functions|
More complex functions
|Section 7: Graphs|
Line, Scatter charts
Bar, Pie charts. Graph export
|Section 8: Additional data types|
Dates and Times
|Section 9: Data mining|
Summarize – Data frames
Summarize – Lists
Reshape data – reshape2 package
Reshape data – plyr package
|Section 10: Data Science Project|
Data Science workflow
Possible project suggestion(data included)
|Section 11: Additional material|
Useful Cheat Sheets
Popular R packages
|Section 12: Final thoughts|
Data analyst with more than 3 years of experience.
Employing various tools for data analysis. Always picking the right tool to do the job. I use R package often combining it with Excel, SQL databases and Access on daily basis.
Graduated econometrics from Vilnius University faculty of Mathematics and Informatics. Afterwards I worked as economical forecaster. Currently my position being analyst of online advertising data in leading advertising platform – focusing on insights from large datasets.
I am constantly participating in events/conferences regarding data analysis. Currently interested in open data initiatives – possibilities to open up more government data for public use. Participating in contests of predictive analytics.
Let me know if you have any questions/suggestions regarding data and analysis. You can find my on Google+ or Linkedin.
- Lectures 0
- Quizzes 0
- Duration 50 hours
- Skill level All level
- Language English
- Students 1085
- Assessments Self