Global Certificate in Data-Driven Design: R for Motion Graphics
-- ViewingNowThe Global Certificate in Data-Driven Design: R for Motion Graphics is a comprehensive course that bridges the gap between data analysis and creative design. This certification program emphasizes the importance of data-driven decision-making in the motion graphics industry, where data visualization is a critical skill.
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⢠R Programming Basics & Data Manipulation: This unit covers the fundamentals of the R programming language, including data types, variables, functions, and data manipulation techniques. It includes working with data frames, subsetting data, and performing calculations.
⢠Data Visualization with ggplot2: This unit focuses on using the ggplot2 package for data visualization in R. It covers creating static and interactive plots, customizing visual aesthetics, and using advanced features like faceting and statistical transformations.
⢠Data Wrangling with tidyverse: This unit explores the tidyverse package, which includes a suite of tools for data manipulation, transformation, and visualization. It includes working with dplyr, tidyr, and lubridate packages for data wrangling.
⢠Motion Graphics with R: This unit covers creating motion graphics using R and animation packages like gganimate and tweenr. It includes building interactive and static motion graphics, customizing animation parameters, and integrating audio.
⢠Data-Driven Storytelling with R: This unit focuses on using R for data-driven storytelling, including creating compelling narratives, designing effective visualizations, and delivering presentations. It includes using R Markdown for report generation, creating interactive dashboards, and using Shiny for creating web applications.
⢠Machine Learning with R: This unit covers machine learning techniques in R, including supervised and unsupervised learning, regression, classification, and clustering. It includes using packages like caret, mlr, and keras for machine learning.
⢠Big Data Analytics with R: This unit explores working with big data in R, including using packages like sparklyr and ff for processing large datasets. It includes data manipulation, visualization, and machine learning techniques for big data.
⢠Data Security and Ethics: This unit covers best practices for data security and ethical considerations in data-driven design. It includes topics like data privacy, data protection, and ethical decision-making in design.
⢠Final Project: This unit integrates all the concepts learned in the course and requires students to complete a final project that demonstrates proficiency in using
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