R is a programming language and environment designed for statistical computing, data analysis, and graphical representation. R is widely used by statisticians, data scientists, researchers, and analysts for various tasks related to data manipulation, statistical modeling, and visualization. R is particularly well-suited for tasks involving data analysis, visualization, and statistics, chosen for its flexibility and a wide array of available tools.
This course takes us on a transformative journey through R programming, from foundational concepts to cutting-edge techniques. We delve into R’s fundamentals, data types, variables, and structures. We will explore R programming with custom functions, control structures, and data manipulation. We will analyze data visualization with leading packages, statistical analysis, hypothesis testing, and regression modeling. With regular expressions, we will understand advanced data manipulation, outlier handling, missing data strategies, and text manipulation. We will learn about ML with regression, classification, and clustering algorithms. We will explore DL, neural networks, image classification, and semantic segmentation.
Upon completion, we will create dynamic web apps with Shiny and emerge as skilled R practitioners, ready to tackle challenges and contribute to data-driven decision-making.
publication date
2023-09-22
what you will learn
Excel in R basics and advanced data science techniques
Transform, visualize, and aggregate data with precision
Craft compelling visuals using ggplot, Plotly, and leaflet
Implement regression, classification, and clustering models
Explore neural networks, image classification, and segmentation
Develop dynamic web apps using R Shiny for engaging user experiences
key features
Learn R fundamentals, advanced analytics, machine learning, and deep learning for data science * Work on practical labs and exercises to reinforce data manipulation, modeling, and visualization * Equip for practical data, projects, case studies, and translate theory into actionable insights
approach
The course takes a hands-on/practical approach, emphasizing real-world applications. Concepts are introduced through interactive lectures, guided labs, and exercises that allow learners to apply what they have learned immediately. This experiential learning approach fosters a deep understanding of R programming, data manipulation, statistical analysis, machine learning, and deep learning techniques.
audience
The course caters to aspiring and established data scientists, analysts, programmers, researchers, and professionals seeking to enhance their skills in data manipulation, statistical analysis, ML, and DL using R programming. It caters to individuals with varying experience levels, from beginners looking to enter the field to experienced practitioners aiming to expand their expertise in data-driven decision-making and advanced analytics. Prerequisites include prior programming experience but this course can accommodate learners with varying levels of data science concepts and R programming familiarity.
short description
Get involved in a learning adventure, mastering R from foundational basics to advanced techniques. This course is a gateway to the realm of data science. Explore statistical machine learning models and intricacies of deep learning and create interactive Shiny apps. Unleash the power of R and elevate your proficiency in data-driven decision-making.
subtitle
Master R from Basics to Deep Learning, Unveiling Data Science, Statistical Models, Shiny, and Beyond
keywords
R programming, data science, machine learning, data manipulation, data visualization, statistical analysis, regression models, deep learning, neural networks, Shiny app development, data modeling, data visualization, machine learning algorithms, deep learning concepts, R Shiny, statistical modeling, semantic segmentation, data-driven decision-making
Product ISBN
9781835082539
