Advanced R Training Course

Big Data is a term used to describe solutions designed for storing and processing extensive data sets. Initially developed by Google, these Big Data solutions have since evolved and inspired numerous similar projects, many of which are available as open-source. R is a widely used programming language in the financial sector.

R is an open-source programming language that is freely available for statistical computing, data analysis, and graphical representation. It is increasingly being adopted by managers and data analysts in both corporate and academic settings. R has also gained a following among statisticians, engineers, and scientists who lack formal computer programming skills due to its user-friendly nature. The growing popularity of R can be attributed to the rising importance of data mining for various objectives, such as setting advertising prices, accelerating drug discovery, or refining financial models. R offers a comprehensive range of packages specifically designed for data mining.

R is a widely used, open-source environment for statistical computing, data analytics, and graphics. This course introduces students to the R programming language, covering its fundamental concepts, libraries, and advanced topics. It also delves into advanced data analytics and graphing using real-world data.

Audience

Developers and Data Analysts

Duration

3 days

Format

Lectures and Practical Sessions

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

By the end of this training, participants will be able to:

• Understand the fundamentals of forecasting techniques in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Utilize the ‘forecast’ package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

Audience

This course is designed for business owners, including marketing managers, product managers, and customer base managers, along with their teams. It also caters to professionals in the field of customer insights.

Overview

The course covers the entire customer life cycle, starting from acquiring new customers, managing existing ones to enhance profitability, retaining valuable customers, and understanding why certain customers are leaving. We will work with real (though anonymized) data from various industries such as telecommunications, insurance, media, and high technology.

Format

The training is led by an instructor over five half-day sessions, featuring in-class exercises and homework assignments. It can be conducted either in a classroom setting or online.

R is an open-source programming language that is widely used for statistical computing, data analysis, and creating graphics. It is increasingly favored by managers and data analysts both in corporate settings and academic institutions. R offers a vast array of packages designed for data mining.

Audience

• managers
• developers
• scientists
• students

Course Format

The course will be conducted through online instruction and discussion, or in-person workshops.

R is an open-source programming language used for statistical computing, data analysis, and creating graphics. It has gained increasing popularity among managers and data analysts in both corporate and academic settings. R has also attracted users such as statisticians, engineers, and scientists who lack formal programming skills due to its user-friendly nature. The growing use of data mining for various purposes, such as setting ad prices, accelerating drug discovery, or refining financial models, has further contributed to its popularity. R offers a vast array of packages specifically designed for data mining.

This course focuses on the manipulation of objects in R, including reading data, accessing R packages, writing functions, and generating informative graphs. It also covers analyzing data using common statistical models. The course provides comprehensive instruction on how to use the R software (https://www.r-project.org) through both command-line interfaces and graphical user interfaces (GUIs).

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly favored by managers and data analysts both in corporate settings and academic institutions. R has also gained a following among statisticians, engineers, and scientists who may not have extensive programming skills, as they find it user-friendly. The growing popularity of R can be attributed to the rising importance of data mining for diverse objectives, such as setting advertising prices, accelerating drug discovery, or refining financial models. R offers a broad range of packages specifically tailored for data mining applications.

R is an open-source programming language designed for statistical computing, data analysis, and creating graphics. It is increasingly favored by managers and data analysts both in corporate environments and academic institutions. R has also gained a following among statisticians, engineers, and scientists who lack formal computer programming skills due to its user-friendly nature. The growing popularity of R can be attributed to the expanding use of data mining for various purposes, such as setting advertisement prices, accelerating drug discovery, or refining financial models. R offers a broad range of packages specifically tailored for data mining.

This course provides an introduction to implementing neural networks in practical scenarios using the R-project software.

This course is designed for data scientists and statisticians who already possess basic R and C++ coding skills and need to enhance their advanced R coding abilities.

The objective is to provide a practical, advanced R programming course for participants who are interested in applying these methods in their professional work.

Sector-specific examples are utilized to ensure the training is relevant to the audience.

This course is an integral component of the Data Scientist skill set, falling under the domain of Data and Technology.

Audience

Format of the Course

By the end of this training, participants will be able to:

In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages designed for cleaning, processing, modeling, and visualizing data. Some of these packages include: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and visualization

• The course combines lectures with discussions, exercises, and extensive hands-on practice.

• Perform data analysis and create compelling visualizations
• Draw meaningful insights from various datasets of sample data
• Filter, sort, and summarize data to answer exploratory questions
• Transform processed data into informative line plots, bar plots, and histograms
• Import and filter data from a variety of sources, including Excel, CSV, and SPSS files

Description:

This course is tailored for R users who want to develop web applications without having to delve into cross-browser HTML, Javascript, and CSS.

Objective:

The course provides an introduction to the fundamental workings of Shiny apps.

It covers all the commonly used input, output, rendering, and paneling functions from the Shiny library.