R for Data Analytics
Extract insights from data! Make predictions! In this program, you will acquire practical knowledge that will excite you! After mastering the fundamental concepts of the R programming language during the training, you will apply your technical skills to clean and analyze dirty data, and tackle real-world problems encountered in marketing, finance, business, healthcare, and government sectors.
Training table
Data Analytics with R
Data Analytics with R
Datenanalyse mit R
Аналитика данных с R
Information about the training
This training will explain analytical methodologies in a simple and practical manner, teaching you the most commonly used analytical libraries. You will learn to clean, describe, and analyze complex and confusing data using the R programming language, apply various statistical, diagnostic, and analytical methods, and convert your analyses into applications with SHINY. This will enhance your decision-making speed and provide a fast and engaging start to data science!
Who is this training for?
Beginners in Data Science, individuals interested in data analysis using the R programming language, programmers and data engineers wanting to learn analytics, business managers, business analysts, data analysts, those learning data analytics and interested in the field, individuals wanting to work with large datasets, researchers, and students or professionals looking to start a career in Data Science.
Certificate
Certificates will be awarded to individuals who successfully complete the training: a Certified R for Data Analyst certificate for successful participants and a participation certificate for others. You can see a sample certificate on the right.
R Programming Tutorial
Data Analytics with R
freeCodeCamp.org
In this training course, you learn the R programming language. This is a hands-on overview of the statistical programming language R, one of the most important tools in data science. Video Courtesy: freeCodeCamp.org
Syllabus
Session 1
- Introduction to R
- Introduction to R Studio
- Data Types in R
- Data Structures in R (Vector, Matrix, Data Frame, List)
- Functional Programming
- Conditional Operators
Case Study 1
Coding Practice in R.
Session 2
- Introduction to the "dplyr" Library
- Data Manipulation with 'dplyr"
- Data Grouping (Left, Right, Inner, Full Join)
- Working with Advanced Libraries: "tidyr" and "tidyverse"
- Data Formats
- Data Transformations
- Working with Various Databases in R (MS SQL Server, MySQL, Oracle).
Case Study 2
Preparing Sales Data for Analysis.
Session 3
- Why ggplot2?
- Grammar of Graphics
- General Construction of Visualizations in "ggplot2".
- Data Visualization with "plotly" and "ggplot2".
- Advanced Visualization with "ggstatplot" and "tidycharts".
Case Study 3
Visualization and Analysis of Market Data.
Session 4
- Conversion of Data Types
- Imputation of Missing Values Using Various Statistical Methods.
- Identification and Removal of Outliers.
Case Study 4
Cleaning Real Data
Session 5
- Introduction to Shiny
- Getting to Know Shiny
- User Interface
- Control Widgets
- Creating Reactive Outputs
- Using Tables in the Shiny Library
- Utilizing Reactive Operations
Case Study 5
Creating Various Designed Web Applications with Real Data.
Trainers
Turqut Abdullayev
AZERCONNECT GROUP-DA ANALİTİKA KOMANDASININ RƏHBƏRİTurgut Abdullayev, with over 5 years of experience in the field of data, currently works as the Head of the Analytics Team at Azerconnect Group. Our trainer is the first and only Azerbaijani to receive the international title of "R Contributor." He was the first to develop the "fast.ai" library in the R programming language, and this integration was supported by the founder of the library, Jeremy Howard.
List of Contributors from Official R Website
His previous work experience includes:
* Head of the Limits Management Department at Kapital Bank
* Senior Data Scientist at Access Bank
He has extensive knowledge of software tools such as R, Python, HTML, SQL, Docker, CI/CD (Github Actions), Git, Markdown, and LaTeX, and has worked as a professional data analyst in various consulting companies. In particular, he has mastered the intricacies of machine learning and artificial intelligence through R programming and always incorporates the latest developments in this field into his training sessions. He is also the author of numerous blog posts in the field.