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R Free Resources | This repo collects 15 of free resources for R. 📈 Dive into data science with our R Studio repository! Packed with a comprehensive collection of free R resources and online tools, this is your go-to place for mastering R programming. Perfect for statisticians, data analysts, and...

A tool to support the Resident Corrections Analyst program through bespoke functions written in R and data sets for learning purposes.

In at present's aggressive business surroundings, Data evaluation helps to assemble optimum Data and utilize it in each sector; be it a small begin-up or an established group. After present process this course the members will develop into data engineers who can carry out analytics operations on Data utilizing various instruments. Sentimental Analytics: Creating Sentimental Analytics by Downloading the Tweets from Twitter and Feeds the trending Data to the Application. Today, Big Data analytics are producing invaluable insights in almost all enterprise functions, whether it is advertising evaluation, forecasting worker attrition or making strategic selections. The key parameters primarily based on which these coaching institutes have been ranked comprised in fact content material & comprehensiveness, college details comparable to those with PhD or business experience, scholar experience resembling post completion engagement. Effectively, with our coaching, members can excel of their profession as a Data Analyst and statistics will stand as proof of our quality services. Imarticus Studying has also established alliances with global analytics companies namely, Genpact and DXC Technology. We bring to you the analytics and data science training institute ranking for the 12 months 2018. As a part of this course, find out about Textual content analytics, the various textual content mining techniques, its utility, text mining algorithms and sentiment analysis. The institute aims to address the challenges within the industry and empower professionals through their transformational programs in Huge Data and Data Science. They offer coaching in multiple common and niche instruments resembling Data science, machine studying, large Data and AI applied sciences. We provide on-line large ExcelR Data analytics courses and certification program so you possibly can be residing wherever in India, like Delhi, Gurgaon, Bangalore, Mumbai, Hyderabad, Pune and so forth. Description: Be taught in regards to the other moments of business determination as a part of Statistical Analysis Study extra about Visual Data representation and graphical techniques. Find out about Python, R programming with respect to Data Science and Machine Learning Understand the best way to work with different Python IDE and Python programming examples.

R Programming Fundamentals for Data Analysts

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Learning R programming language for data analyst

R tutorial from R Programming for Data Analysts by Jared P Lander (video)

2024 Training - Data Analysts Skills - Statistics, R Programming Language, SQL and Tableau for Data Visualization

A sample collection of R programs for Udacity Data Analyst program.

Welcome to the R_Programming_Language repository for the R programming language! This repository is a central hub for R enthusiasts and data analysts looking to explore, learn, and collaborate on R projects.

Structured R programming for data science. From basics to advanced analytics with hands-on exercises & real projects. Perfect for beginners & analysts.

I worked as Data Analyst on this project in the course R Programming for Data Science by IBM.

R is a programming language used for statistical analysis, data visualization, and data science. It is widely used by researchers, data analysts, and scientists around the world.

Includes learning and coding the R programming language to get used to many quantitative analysts as a programming tool since it's useful for data importing and cleaning. It consists of an introduction to R, Fundamental knowledge of R, Basics of R, Input and Output of R, and Data structures of R

This project is for my capstone project Professional Data Analyst. For data exploration and manipulation I used program R.

Built as part of my R Programming for Data Analysts course, this dashboard explores top Tesla models, electric range vs MSRP, BEV vs PHEV trends, and utility distribution. Designed for executive insights and data storytelling.

This is a capstone project for the data analyst program by Google on Coursera coded in R and visualized in Tableau.

A comprehensive and extensible collection of R programs for professional data visualization, built using modern libraries like ggplot2 and dplyr. This project is designed to help developers, analysts, and data scientists create high-quality, publication-ready visualizations with clean and reproducible code.

I am an effervescent Data-Analyst seeking an Internship, Entry-Level, or basically a Junior Data-Analyst role. Over the past few months, I have been able to garner some skills that are imperative for me to triumph in becoming a Data Analyst. Skills such as: Excel, SQL, and R Programming Language. I am not an expert yet, but I'd become one with time

I completed the statistics for data analyst and scientist 2023 udemy course by olanrewaju oyingbooke and recreated the statistics test carried out by him in the course using SPSS with R program

This is a part of Exploratory Data Analysis project for Udacity. This project is a part of the Data Analyst Nanodegree program. Here we have used R studio to analyze the Prosper loan Data set. If more information for Prosper is needed, refer to https://www.prosper.com/

This repo was created for the Corsera.org free online course titled: "The Data Scientist's Toolbox". This course introduces the main tools and ideas in the data scientists toolbox. It gives an overview of the data, questions, and tools that data analysts and data scientists use. There are two components to the course. 1) A conceptual introduction to the ideas behind turning data into actionable knowledge. 2) A practical introduction to the tools that will be used in the program like version control, markdown, git, Github, R, and Rstudio.

For my capstone project from the Google Data Analytics Course, I have decided to take on the Cyclistic case study. I will be taking on the role of a data analyst for Cyclistic, a bike-share company based in Chicago. I have followed the six steps in the process detailed in the course, which are Ask, Prepare, Process, Analyze, Share, and Act. I completed the project using R programming.

The Bellabeat Marketing Analysis is the second case study of Google’s Data Analytics Professional Certificate program. The case study requires the analyst to follow to the steps of the data analysis process (ask, prepare, process, analyze, share, and act) for a dataset that represents a fictional company (Cyclistic Bike-Share). I utilized SQL, R, and Google Sheets in this case study.

Cyclistic bikeshare analysis case study is part of Google Data Analytics Capstone - Complete a Case study project. The objective of this case study is to perform some real-world tasks of a junior data analyst. Cyclistic’s historical trip dataset is provided by Motivate International Inc. under the [license](https://ride.divvybikes.com/data-license-agreement). Motivate International Inc. (“Motivate”) operates the City of Chicago’s (“City”) Divvy bicycle sharing service. The programming language used for analysis of the dataset is R.

This introductory course is designed to train you in statistical analysis using the R programming language. Statistical analysis is a kind of quantitative analysis that involves descriptive data, such as survey data and observational data. This type of analysis enables the analyst to validate assumptions, hypothesis, and test theories using standard statistical models. This course provides the attendees with a lecture of probability theory and provides exercises of how those techniques are being used to deliver tremendous value for organizations across various industries. While introducing you to the theory, we'll pay special attention to practical aspects for working with probabilities, sampling, data analysis, and data visualization.

This introductory course is designed to train you in statistical analysis using the R programming language. Statistical analysis is a kind of quantitative analysis that involves descriptive data, such as survey data and observational data. This type of analysis enables the analyst to validate assumptions, hypothesis, and test theories using standard statistical models. This course provides the attendees with a lecture of probability theory and provides exercises of how those techniques are being used to deliver tremendous value for organizations across various industries. While introducing you to the theory, we'll pay special attention to practical aspects for working with probabilities, sampling, data analysis, and data visualization.