Data Analysis with R

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.