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US$500
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Duration: 2 Weeks
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Delivery mode: Online
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Group size: 2
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Instruction language:
English
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Certificate provided:
Yes
COURSE OUTLINE
DAY 1 - 2. Introduction to R and RStudio
• Installing R and RStudio
• Basic R syntax and data structures
• Reading and writing data in R
DAY 3 - 4. Data Wrangling and Cleaning
• Importing data from various sources (e.g. CSV, Excel)
• Tidying data using the tidyverse package (e.g. tidyr, dplyr)
• Dealing with missing data and outliers
• Data transformation and manipulation using dplyr
DAY 5 -.7. Data Visualization
• Creating static plots using ggplot2
• Interactive visualization using plotly and ggplotly
• Best practices for data visualization
DAY 8 - 9. Exploratory Data Analysis (EDA)
• Descriptive statistics and distributions
• Correlation analysis
• Hypothesis testing and confidence intervals
DAY 10 -12. Regression Analysis
• Simple and multiple linear regression
• Logistic regression for binary outcomes
• Generalized linear models for non-normal distributions
DAY 13 -16. Machine Learning
• Supervised learning: classification and regression
• Unsupervised learning: clustering and dimensionality reduction
• Evaluation and selection of machine learning models
PS.
The duration and level of detail of each topic can be adjusted depending on the needs and background of the audience.