riversongs Posted January 8, 2024 Report Share Posted January 8, 2024 Free Download Data Analytics using R programmingLast updated 1/2024Created by Vignesh MuthuvelanMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 147 Lectures ( 14h 3m ) | Size: 5.61 GBData analytics, R programmingWhat you'll learn:What is data and its typesOverview of the R programming language.Installation of R and Rstudio in Ubuntu environmentBasic syntax and data structuresOperators, control and looping statement in RString handling, vector operator in RBuilt-in and user defined function in RVectorization in RData Structure Data Manipulation, Data Reshaping, Data visualizationData visualization using base R, ggplot2 and other visualization libraries.Reading and importing and handling missing data from different source (CSV, Excel, databases).Different Case studies and practical projects.Requirements:Having a basic understanding of programming concepts can be beneficial.A foundational understanding of basic statistical concepts like mean, median, standard deviation, and so on.Basic mathematical operations used in data analytics.An awareness of fundamental data concepts, such as types of data, and basic data structures, can be beneficial.Description:Unlock the power of data with our comprehensive "Data Analytics Using R Programming" course. In this immersive learning experience, participants will delve into the world of data analytics, mastering the R programming language to extract valuable insights from complex datasets. Whether you're a seasoned data professional or a newcomer to the field, this course provides a solid foundation and advanced techniques to elevate your analytical skills.Key Learning Objectives:R Programming Fundamentals:Gain a deep understanding of the R programming language, covering syntax, data structures, and essential functions.Data Import and Cleaning:Learn how to import data from various sources and perform data cleaning and preprocessing to ensure accurate analysis.Exploratory Data Analysis (EDA):Develop skills in descriptive statistics, data summarization, and advanced visualization techniques using ggplot2.Real-World Applications:Apply your newfound knowledge to real-world data analytics challenges, working on hands-on projects that simulate the complexities of professional scenarios.Course Format:This course is delivered through a combination of video lectures, hands-on exercises, and real-world projects. Participants will have access to a supportive online community and regular opportunities for live Q&A sessions.By the end of this course, you will be equipped with the skills to navigate the data analytics landscape confidently, making informed decisions and uncovering hidden patterns in data. Join us on this journey to become a proficient data analyst using the versatile R programming language. 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