Create Your Calculator: Learn R Programming Basics Fast

Why Dive into Data Analysis and Data Science?

According to SAS, there are compelling reasons to pursue a career in data analysis and data science. Here's a breakdown of the top five benefits:

• Sharpen Your Problem-Solving Skills: Develop the ability to think analytically and approach challenges strategically – a highly valuable asset in both your professional and personal life.
• High Demand & Career Growth: Data Analysts and Data Scientists are in high demand. With a growing skill shortage as businesses increasingly leverage data, the value of these professionals will continue to rise.
• Analytics is Ubiquitous: Data is everywhere. Every company generates data and seeks insights to optimize operations. This is an incredibly exciting time to launch a career in analytics.
• Increasing Importance: The explosion of available data presents unprecedented opportunities to uncover valuable insights for informed decision-making. This translates to greater value for data analysts and more abundant job prospects.
• Versatile Skillset: The field of data analysis is interdisciplinary, drawing from computer science, business, and mathematics. Data analysts also need strong communication skills to effectively convey complex information to non-technical audiences. Furthermore, understanding Data Science opens doors to exciting areas like the Internet of Things (IoT) and Smart Cities – where Data Science meets Engineering.

Learn R Programming with Our Bite-Sized Course

This course provides a fast-track introduction to R Programming, equipping you with the skills to analyze data and extract meaningful insights. You'll quickly gain proficiency and build practical skills. You'll be creating your own calculator very soon after starting the course!

Here's a structured learning path:

• Create Your Calculator: Learn R Programming Basics Fast (R Basics)
• Applied Statistics using R with Data Processing: Data Understanding and Data Preparation
• Advanced Data Visualizations using R with Data Processing: Data Understanding and Data Preparation (future modules)
• Machine Learning with R: Modeling and Evaluation

Course Content Overview

• Getting Started:
  • Hello World
  • Software Setup
  • Variables and Data Types
• Data Manipulation:
  • Data type Conversion
  • Vector
  • List
  • Matrix
  • Data Frame
• Operators:
  • Arithmetic Operators
  • Relational Operators
  • Logical Operators
• Control Flow:
  • Decision Making I (IF statements)
  • Loop (while loop, for loop)
• Functions:
  • Functions
• Practical Application:
  • Import CSV
• Descriptive Statistics & Visualization:
  • Descriptive Statistics with Summary()
  • Plot Graphs

Certification: Upon completion, you can take an exam at EMHAcademy to earn the SVBook Certified Data Miner certification using the R certificate.