Datascience with R

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Data Science with R refers to the use of the R programming language in the field of data science to analyze and interpret complex data sets, enabling decision-making based on data. R is particularly popular in academic and research settings due to its extensive range of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more.

Data Science with R Certification Training Course

The Data Science with R Certification Training Course is designed for individuals looking to develop their skills in data analysis, statistical modeling, and data visualization using the R programming language. R is widely recognized for its extensive library of packages, ease of data manipulation, and graphical capabilities, making it a popular choice among data scientists and statisticians. This course aims to equip learners with the fundamental knowledge and practical skills needed to analyze complex data, extract actionable insights, and make data-driven decisions.

Course Content

Introduction to Data Science

Overview of data science and its applications.
Introduction to R and RStudio.
Basics of R programming: data types, variables, operators, etc.

Data Manipulation with R

Importing and exporting data.
Data manipulation with dplyr and tidyr.
Data cleaning and preprocessing techniques.

Data Visualization with R

Introduction to ggplot2 for creating static plots.
Interactive visualizations with plotly and ggplotly.
Customizing plots for effective communication of data insights.

Statistical Analysis with R

Descriptive statistics: mean, median, standard deviation, etc.
Inferential statistics: hypothesis testing, confidence intervals, p-values.
Correlation and regression analysis.

Machine Learning with R

Introduction to machine learning concepts.
Supervised learning: regression, classification.
Unsupervised learning: clustering, dimensionality reduction.
Model evaluation and validation techniques.

Big Data Processing with R

Working with large datasets using dplyr and data.table.
Introduction to distributed computing with sparklyr and sparkR.

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Data science with R Certification Course Overview

The Data Science with R Certification Course is designed for individuals aiming to gain expertise in data analysis, statistical modeling, and data visualization utilizing the R programming language. This course caters to a wide range of professionals, including those new to data science and those looking to enhance their existing skills with R’s powerful capabilities.

Data Science Training Key Features

R Programming Skills
Data Manipulation and Cleaning
Statistical Analysis
Data Visualization
Machine Learning
Big Data Processing with R
Advanced Topics

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In Group

Learners can share insights, ask questions, and engage in discussions, fostering a collaborative learning atmosphere.
Courses are typically designed with a set curriculum that aims to meet the learning objectives of the group as a whole.
Training sessions are scheduled at predetermined times, which can help learners maintain a consistent learning routine.

One on One

The trainer focuses solely on one student, allowing for immediate feedback, personalized guidance, and a learning pace that suits the individual.
One-on-one training often comes with the flexibility to schedule sessions at times that are most convenient for the learner, accommodating their personal and professional commitments.

Weekend Batch

Classes are usually held on weekends, making it convenient for those who are busy during the weekdays.
Since the classes are on weekends, the training sessions might be longer than typical weekday classes, aiming to cover the syllabus efficiently over a shorter period.