Data Science With R Programming Basics
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Data Science With R Programming Basics
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Author : Dr.Sudhakar.K
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-08-13
Data Science With R Programming Basics written by Dr.Sudhakar.K and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-13 with Computers categories.
Dr.Sudhakar.K, Associate Professor, Department of Artificial Intelligence & Data Science, NITTE Meenakshi Institute of Technology, Bangalore, Karnataka, India. Mrs.Geethanjali.S.G, Assistant Professor, Department of Computer Science & Engineering, DON BOSCO Institute of Technology, Bangalore, Karnataka, India. Mrs.Rashmi.D.M, Assistant Professor, Department of Computer Science & Engineering, DON BOSCO Institute of Technology, Bangalore, Karnataka, India. Mrs.Sinchana K.P, Assistant Professor, Department of Computer Science & Engineering, DON BOSCO Institute of Technology, Bangalore, Karnataka, India.
R Programming For Beginners
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Author : Peter Simon
language : en
Publisher: Peter Simon
Release Date :
R Programming For Beginners written by Peter Simon and has been published by Peter Simon this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
R Programming for Beginners: Master the Fundamentals of R, Even with Zero Coding Experience The Ultimate Beginner’s Guide to Learning R—Perfect for First-Time Coders, Data Enthusiasts, and Future Analysts! Ready to dive into the world of data but not sure where to start? Whether you're exploring data science with R, planning to take an R programming online course, or just curious about coding, R Programming for Beginners is your go-to guide for mastering the essentials of the R programming language—no technical background needed. This book is more than just a read—it's a hands-on R course for beginners that walks you step by step through real-world examples, making learning R programming for beginners simple, effective, and even fun. 🔍 What This R Programming Book Covers: ✅ Introduction to R Software for Beginners Learn what R is, how to install and use R Studio for beginners, and why it's one of the top tools for data analysis and statistical computing. ✅ Essential R Programming Language Basics Master the core concepts: Data types and variables Vectors, matrices, and data frames Control structures (if statements, loops) Writing custom functions Basic R programs for data manipulation and cleaning ✅ Hands-On Practice for Real Learning Apply what you learn with practical examples and exercises—just like a real R programming course for beginners or an R programming tutorial for beginners would provide. 🎯 Why This Is the Best Way to Learn R Programming Online: 📘 Structured Like an R Programming Language Online Course – With clear progression and learning checkpoints. 💡 Beginner-Friendly Explanations – No jargon. Just step-by-step help for anyone who wants to learn R programming the right way. 💻 Perfect Alternative to an R Software Online Course – Learn at your own pace, with full control. 📊 Built for Data Analysis – This is not just theory—you'll learn how to apply R to real data. 🔧 Your First Step into Data Science with R – Ideal for building a strong foundation before advancing to machine learning, statistics, or big data. 👨🏫 Who This R Programming Training Is For: Absolute beginners who want a friendly R language tutorial for beginners Students looking to learn R language for beginners without overwhelming content Professionals starting a data career and seeking an easy-to-follow R software tutorial for beginners Self-learners who want a book-based R programming language course that replaces expensive bootcamps Anyone interested in R programming for dummies-style guidance, minus the fluff 🎁 Bonus Learning Tools Included: Practice datasets and sample code Clear R exercises with solutions Downloadable materials via our R language website Recommendations for the best tools to learn R language online Guidance on how to continue with an R programming online course after completing this book ✅ Start Your R Coding Journey Today If you’ve been searching for a beginner R tutorial that makes sense, or a way to learn R programming without frustration, this is the book for you. Whether you’re taking your first steps or using it as a supplement to an R programming language online course, this beginner guide will help you learn R language fast and with confidence. 🛒 Scroll up and get your copy today—start your journey with R, the powerful programming language for data science, now!
Introduction To Biomedical Data Science
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Author : Robert Hoyt
language : en
Publisher: Lulu.com
Release Date : 2019-11-24
Introduction To Biomedical Data Science written by Robert Hoyt and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-24 with Science categories.
Overview of biomedical data science -- Spreadsheet tools and tips -- Biostatistics primer -- Data visualization -- Introduction to databases -- Big data -- Bioinformatics and precision medicine -- Programming languages for data analysis -- Machine learning -- Artificial intelligence -- Biomedical data science resources -- Appendix A: Glossary -- Appendix B: Using data.world -- Appendix C: Chapter exercises.
Fundamentals Of Data Science
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Author : Dr. N. Bharathi, Dr. Jayshri Harde, Mr. Pradeep Kumar Tiwari, Mr. Abhendra Pratap Singh
language : en
Publisher: BR Publications
Release Date : 2025-09-16
Fundamentals Of Data Science written by Dr. N. Bharathi, Dr. Jayshri Harde, Mr. Pradeep Kumar Tiwari, Mr. Abhendra Pratap Singh and has been published by BR Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-16 with Computers categories.
Fundamentals of Data Science” provides a comprehensive introduction to the principles, methodologies, and practical applications of data-driven analysis. The book explores the complete data science pipeline — from data collection, preprocessing, and visualization to statistical modeling, machine learning, and decision-making.
E Learning And Enhancing Soft Skills
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Author : Eugenia Smyrnova-Trybulska
language : en
Publisher: Springer Nature
Release Date : 2025-03-10
E Learning And Enhancing Soft Skills written by Eugenia Smyrnova-Trybulska and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-10 with Education categories.
This volume E-Learning and Enhancing Soft Skills is a collection of articles by participants of the 16th annual scientific international conference “Theoretical and Practical Aspects of Distance Learning: E-Learning and Enhancing of Soft Skills. This conference, held on the 14th and 15th October 2024 in hybrid mode, is organized by the Faculty of Arts and Educational Sciences in Cieszyn, the Faculty of Social Sciences, the Institute of Pedagogy, the Faculty of Science and Technology, the Institute of Computer Science, University of Silesia in Katowice, Poland. Co-organizers and partners included: University of Ostrava (UO), Czech Republic, Silesian University in Opava (SU), Czech Republic, Constantine the Philosopher University in Nitra (UKF) Slovakia, University of Extremadura (UEx), Spain, University of Twente (UT), The Netherlands, Lisbon Lucíada University (LU), Portugal, Curtin University in Perth (CU), Australia, Borys Grinchenko Kyiv University (BGKU), Ukraine, Dniprovsk State Technical University (DSTU), Ukraine, IADIS - International Association for Development, of the Information Society, a non-profit association, Polish Pedagogical Society, Branch in Cieszyn, Polish Scientific Society for Internet Education, Association of Academic E-learning, Poland. Experts on e-learning from different countries provide insights into their studies, present their recent research results and discuss their further scientific work. The authors include experts, well-known scholars, young researchers, highly trained academic lecturers with long experience in the field of e-learning, AI and robotics in education, MOOCs, teacher training an area digutak and soft skills, m-learning, smart technologies, VR/AR; PhD students, distance course developers, authors of multimedia teaching materials, designers of websites and digital educational resources. This monograph therefore describes the theoretical, methodological and practical issues in the field of e-learning and the developing of key competencies and soft skills, contemporary models of education in the era of artificial intelligence, proposing solutions to important problems and showing the road to further research in this field. Built from the findings of an international retinue of scholars, this work will be of particular interest to academic researchers, educators, courseware designers, corporate trainers, and educational technology practitioners.
R Programming For Data Science
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Author : Roger D. Peng
language : en
Publisher:
Release Date : 2012-04-19
R Programming For Data Science written by Roger D. Peng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-19 with R (Computer program language) categories.
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.
R Programming
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Author : Daniel Daniel Bell
language : en
Publisher:
Release Date : 2020-06
R Programming written by Daniel Daniel Bell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06 with categories.
2020- Second Edition, updated version. Get your copy!! Why Learn R? What are the reasons to learn R for Data Science? In this small textbook recommended for absolute beginners, the author tried to answer these types of questions. After reading this guide, maybe in one or two days, you will learn the basics of R programming and its utility for each Data Scientist. Indeed, R is a programming language and software environment for statistical analysis, graphics representation, and reporting. If you are trying to understand the R programming language as a beginner, this short book will give you enough understanding of almost all the concepts of the R language. The author will guide you through examples, how to program in R and how to use R for effective data analysis.Get your copy Now! Book Objectives This book is about R programming. The following are the objectives of the author: To familiarize you with the basics of R programming language. To help you understand the various fields where R can be applied and its use cases in each field. To equip you with R programming skills, both beginner and advanced skills. To introduce you to R programming for data analysis. To introduce you to R programming for machine learning. To help you understand and appreciate the power of R in statistical computing, data analysis, and scientific research. Who this Book is for? Anybody who is a complete beginner to R Programming. Anybody in need of advancing their R Programming skills. Professionals in computer programming. Professors, lecturers or tutors who are looking to find better ways to explain R programming to their students in the simplest and easiest way. Students and academicians, especially those focusing on R, Data Analysis,Machine Learning , computer science, and Databases development. Requirements The author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. What is inside the book? R BASICS R DATA TYPES R VARIABLES AND CONSTANTS R OPERATORS DECISION MAKING IN R R LOOPS R FUNCTIONS R CLASSES AND OBJECTS R FOR DATA SCIENCE R FOR MACHINE LEARNING From the Back Cover. R programming language is one of the most popular languages used by statisticians, data analysts, researchers to retrieve, clean, analyze, visualize and present data. This is a comprehensive book on how to get started with R programming, why you should learn it and how you can learn it. Daniel Bell begins by introducing the readers to the foundations of the R programming language. The aim is to help you understand, how the R interpreter works, the origin of the name R, how to set up the R programming environment, etc. The author has discussed the process of installing R on Windows, Linux and Mac OS. Moreover, the author has explored the basics of R programming including writing comments, using the R console, creating R script files, etc. The various features provided by R have been discussed in depth, including data types, variables, loops, decision making, functions, operators, classes, and objects, etc. The author has also discussed R for data science and R for machine learning. The book has been organized into chapters, with each chapter having many sub-chapters. R code scripts have been provided, alongside thorough explanations of the code and images showing the expected output upon the execution of every script. Get your copy
R Programming
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Author : Andy Vickler
language : en
Publisher: R Programming
Release Date : 2023-05-06
R Programming written by Andy Vickler and has been published by R Programming this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-06 with categories.
R is an open-source statistical environment and programming language that has grown in popularity for data management and analysis in various industries. "R" Programming teaches you all the R you'll ever need in a rapid and painless manner. This accessible tutorial taught you your way around a list with no previous programming expertise and loads of practical examples, step-by-step exercises, and sample code. This book covers the most significant modeling and prediction methods, as well as their applications. Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. This book is meant to get you practicing data science as fast as possible, even if you have no prior programming expertise. You'll get a comprehensive grasp of the data science cycle and the fundamental tools you'll need to handle the details. R is becoming more well-known by the day, as large institutions embrace it as a standard. Its popularity stems partly from the fact that it is a free tool replacing expensive statistical software products that may take an undue amount of time to master. Furthermore, R allows a user to do complicated statistical analyses with only a few keystrokes, making advanced studies accessible and clear to a broad audience. Learn how to import data, construct and dismantle data objects, traverse R's environment system, develop your own functions, and utilize all of R's programming tools with this book. This book will not only teach you how to program but also how to use R for more than simply displaying and analyzing data. Most of the chapters are written for you to understand statistical data, so if you are a student, this book can guarantee to teach you some basic statistics that will help you get good grades. The first two chapters are based on beginner's level of R programming, mainly teaching how to successfully install and run the program on your device and introducing Rstudio to you. You will get complete guidance. Chapters three and four will teach you some basic and simple lines of code and how you can successfully execute them on your device. There will be some simple maths included. After that, you will start chapter five, which is completely based on statistics. Chapters six and seven will take your attention to more IT. If you already know basic HTML you will get more information in these chapters as they include similar topics as HTML. Finally, you arrived at chapters eight, nine, and ten, which will enable you to create and run your data. These chapters will complete your journey by allowing you to understand how data frames work and how you can work with different types of data. You will also see how you can install premade data packages that can be helpful when you want to practice more. After that, you will know how to visualize your data in different forms of charts, graphs, etc. The book is highly informative with lots of code, and also I added tons of pictures of how the code will look in r studio. Following the book, you will be able to start Rstudio and use the program smoothly.
Data Science With R Programming Basics
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Author : Mrs.Rasmita Kumari Mohanty
language : en
Publisher: Leilani Katie Publication
Release Date : 2025-03-25
Data Science With R Programming Basics written by Mrs.Rasmita Kumari Mohanty and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-25 with Computers categories.
Mrs.Rasmita Kumari Mohanty, Assistant Professor, Department of CSE-(CyS, DS) and AI & DS, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India. Mr.A.Pramod Kumar, Assistant Professor, Department of (CSE-CyS, DS) and AI & DS, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India. Dr.Yuvaraju Macha, Associate Professor, Department of Mathematics, Matrusri Engineering College, Saidabad, Hyderabad, Telangana, India. R.Madhavi, Assistant Professor, Deparment of Mathematics, Matrusri Engineering College, Saidabad, Hyderabad, India.
Learn R Programming In 24 Hours
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Author : Alex Nordeen
language : en
Publisher: Guru99
Release Date : 2020-10-31
Learn R Programming In 24 Hours written by Alex Nordeen and has been published by Guru99 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-31 with Computers categories.
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?