Srbija Posted November 17, 2020 Share #1 Posted November 17, 2020 The Complete R Programming for Data Science - 7 courses in 1MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + .srt | Duration: 228 lectures (18h 32m) | Size: 6.72 GBBeginner to Pro: Learn R programming language, R studio, ggplot2, dplyr, statistics, caret, machine learning, projects What you'll learn:Learn to program in R LanguageLearn to use R StudioMaster statistics for machine learningMaster Vectors, Lists & DataframesCreate variables and run loopsPerform binding functions & set operationsCreate professional plots using GGPlot2Master statistics for machine learningLearn to use ML models for businessSolve Industry projects end-to-endAdvanced data manipulation with Data TableAdvanced programming with Dplyr packageCreate full featured plots using base graphicsElegant pipe syntax codes using MagrittrLearn Data Manipulation verbsLearn Law of large numbersCentral Limit Theorem & Normal DistributionStatistical significance tests: t Tests , ANOVA, and moreMaster linear & Logistics regression modelsBuild Statistical models from scratchPerform post model building diagnosticsHand computation of statistical testsMaster model insight generation skillsLearn how to present insights to stakeholdersRequirementsNo prior knowledge or experience needed - Only passion to learn and succeed!DescriptionIn The Complete R-Programming for Data Science & Statistics program, we have carefully designed 7 Full-Fledged courses into 1 Master Course of 200+ videos, 50+ R-Packages, Core Machine Learning and statistics concepts, 75+ practice problems and 2 Industrial projectsBy end of this course, you will be able to solve Industry Data Science project in R starting including model building, model diagnostics and presenting actionable business insightsHere's how you will progress across the 7 courses in the Master Course:Getting started with R-programming: First, you will learn to write your own R code and perform basic programming tasks. You will begin with the base R programming course, where you will master the fundamental data structures such as vectors, lists, dataframes , understand the core programming constructs and get enough coding practice. You will also create full featured plots for data analysis using base graphics.Advanced coding with Tidyverse: Then you will move to advanced coding in R based on the tidyverse using the dplyr package. You will start using the elegant pipe syntax provided by the magrittr package and the data manipulation verbs.Data.table for data wrangling in R: Then You will move on to master the data.table package which has advanced capabilities for fast data manipulation. Data Scientists love this package for its incredible speed gains. Here, you will do fast data imports, create pivot tables and get comfortable with wrangling data. You will learn techniques to make your R code run super fast.Ggplot2 Graphics in R: Once you gather the core R programming skills, you start creating professional looking plots using the famous ggplot2 package. You will be able to create any data analysis plot. Be it box plots, scatterplots, dual axis time series plots, because you will not just learn the syntax, but also learn the underlying structure behind it.Statistical Foundations for Machine Learning: You will gain mastery over the 'statistical foundations for machine learning', which by itself is a full fledged statistics course. You will understand the core statistics concepts such as the law of large numbers, central limit theorem, normal distribution, how statistical significance tests such as the t-test and ANOVA work and more, by solving multiple use cases of when and how to use them. You will know exactly how they work by following step-by-step hand computations and then implement in R to match the results. All the concepts are completely explained and demonstrated.Statistical Modeling with Linear Regression and Case Study: After mastering statistics, you will achieve professional-level R skills with linear regression. You will understand:What sort of industrial problems you can apply them onUnderstand the math behind itYou will build the algorithm itself from scratchLearn how to interpret the resultsPerform post model building diagnosticsLearn how to present the model results in a way that is valuable to the business and project stakeholders7. Logistics Regression for Business and Case Problem: You will understand: Then you learn the logistics regression with the same methodology of application, mathematics, building algorithm, interpreting results, diagnosing models and presenting insightsProfessional Level Industry Projects: Finally, to gain and end-to-end professional Data Science project skills, you will solve two Industry projects -> Predict Customer Purchase Propensity (Banking Domain)> Predict U.S. Institute performance (Education Sector)Throughout the program you will get interesting challenges, forum support for your queries and R-DataScience certification for your CV.Who this course is forThis course is for you if you are starting out on Learning R programmingThis course is for you if you are a data science aspirant and want to master data science with RThis course is for you if you are a data scientist and want to add R Datascience skills in your toolkitThis course is for you if you are statistics student or statistician and want to improve your skills in RThis course is for you if you are preparing for jobs and want to master Statistics, ML and R-programmingHomepagehttp://anonymz.com/?https://www.udemy.com/course/r-programming-datascience/https://nitroflare.com/view/862B09D77D877EF/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part1.rarhttps://nitroflare.com/view/474C4A5558BD1C1/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part2.rarhttps://nitroflare.com/view/CE6A42020317806/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part3.rarhttps://nitroflare.com/view/F8F7607B2AC167B/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part4.rarhttps://nitroflare.com/view/FBD53EAAB45CB1C/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part5.rarhttps://nitroflare.com/view/1286320AC805D79/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part6.rarhttps://nitroflare.com/view/53595B22C457DD0/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part7.rarhttps://nitroflare.com/view/C5B03B2B0949D08/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part8.rarhttps://rapidgator.net/file/d2f68e4a5c009f486076c1abec7e80aa/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part1.rar.htmlhttps://rapidgator.net/file/783a4c15e220829460a4eacfd5592fdf/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part2.rar.htmlhttps://rapidgator.net/file/2dbfd41a57a479e371da34b17f560e4e/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part3.rar.htmlhttps://rapidgator.net/file/cd917755def18571a46ed6ffae01a214/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part4.rar.htmlhttps://rapidgator.net/file/a75f1a7f3d398c48530c9028ac7d6f8f/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part5.rar.htmlhttps://rapidgator.net/file/38b58c333726fc9c3da3c8076b2689a2/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part6.rar.htmlhttps://rapidgator.net/file/86e056232b9710538abdebfc2d368a15/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part7.rar.htmlhttps://rapidgator.net/file/9245c2224dd824ca3560243151dde59c/The_Complete_R_Programming_for_Data_Science_-_7_courses_in_1.part8.rar.html Link to comment
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