Mastering R: The Comprehensive Journey from Fundamentals to Data Mastery | Part 2/2 скачать в хорошем качестве

Mastering R: The Comprehensive Journey from Fundamentals to Data Mastery | Part 2/2

Embark on an enchanting voyage into the realm of R, where data casts its spell through the art of analysis and visualization. "Mastering R: The Comprehensive Journey from Fundamentals to Data Mastery" is your grand grimoire, guiding you through the mystical basics to the arcane heights of machine learning. With this comprehensive course, you'll conjure the power of R's versatile data structures, unravel the incantations of data manipulation, and unlock the secrets of statistical sorcery. As you progress, the alchemy of graphics will illustrate your insights, while the dark arts of advanced programming and object-oriented spells strengthen your command over data's hidden layers. Whether you're an apprentice in analytics or a wizard of data science, this video is your crystal ball into mastering the potent magic of R. Join us, and let programming prowess be the wand at your fingertips! 🧙‍♂️✨ 📘 Key chapters: Part 1/2 chapters: 🖥️ Introduction to R: Explore the essentials of R programming, a powerful tool for statistical computing and data science. 🧮 Basic Operations in R: Gain proficiency in R by understanding arithmetic operations, variable assignment, and basic functions. 🗃️ Data Types and Structures: Learn about the variety of data types in R and how to organize data using vectors, lists, matrices, and data frames. 🔨 Data Manipulation: Master techniques to clean, reshape, and get your datasets ready for analysis. ⬇️ Data Import and Export: Discover how to seamlessly import data from various sources and export your results for use in other applications. 💻 Programming Basics: Build a solid foundation in programming with conditionals, loops, and user-defined functions in R. 📊 Graphics and Data Visualization: Create insightful and attractive visualizations that bring your data's story to life. Part 2/2 chapters: 📈 Statistical Analysis: Dive into statistical models and techniques to derive meaningful conclusions from your data. 🔍 Advanced Data Manipulation: Elevate your data manipulation skills using dplyr and tidyr for efficient data processing. 🤖 Object-Oriented Programming: Uncover the principles of object-oriented programming in R to structure your code with classes and methods. ⏭️ Advanced Topics in R: Explore more complex functionalities and packages that will take your R skills to the next level. 🤖 Machine Learning with R: Embark on a journey through machine learning methods in R to build predictive models and unlock data insights. Whether you're a beginner eager to get started or an intermediate user aiming to consolidate and expand your knowledge, 'Mastering R: The Comprehensive Journey from Fundamentals to Data Mastery' is tailored to elevate your R programming abilities to new heights. Journey through the chapters at your pace and harness the power of R to uncover the hidden stories within your data. Join us and transform data into wisdom, one line of R code at a time. Graphics and Data Visualization 00:00 - Base R Graphics 00:38 - ggplot2 01:17 - Plot Customization 01:47 - Interactive Graphics with Shiny and plotly 02:51 - Creating Reports with R Markdown Statistical Analysis 03:54 - Descriptive Statistics 04:43 - Probability Distributions 05:49 - Hypothesis Testing 06:40 - Linear Regression and Diagnostics 07:48 - ANOVA 08:42 - Time Series Analysis Advanced Data Manipulation 09:33 - Data Table Package 10:12 - Dplyr Tricks and Tips 10:44 - Handling Missing Data 11:23 - Date and String Manipulation 11:59 - Efficient Operations with purrr Object-Oriented Programming 12:52 - S3 & S4 Classes 13:40 - Reference Classes (R6) 14:28 - Methods and Generic Functions 15:11 - Method Dispatch 16:08 - Prototypes Advanced Topics in R 16:51 - Efficient Programming (Memory and Speed Considerations) 17:37 - Parallel Computation 18:28 - Integration with Other Languages (C/C++, Python) 19:15 - Bioconductor for Genomic Data Analysis 19:55 - Creating R Packages Machine Learning with R 20:30 - Supervised Learning Algorithms 21:14 - Unsupervised Learning Algorithms 22:16 - Cross-Validation and Bootstrap 23:13 - Model Selection and Tuning 24:22 - Ensemble Methods 25:20 - Machine Learning Pipelines 26:15 - Working with caret, mlr, and tidymodels #study #programming #r #rprogramming #statistics #coding #code #course #learning #tutorial #software