| Content and Methodology |
In the initial week, participants will acquire introduction to the R and Python programming languages, encompassing the setup of the environment, basic syntax, data types, as well as fundamental data manipulation and analysis.
Moving on to the second week, the learning objectives will revolve around data input/output, employing dplyr in R and pandas in Python for data manipulation, and utilizing ggplot2 in R as well as matplotlib/seaborn in Python for data visualization.
The focus of the third week will shift towards statistical analysis using R and Python, accompanied by an introduction to machine learning. Supervised learning algorithms, including linear regression, logistic regression, decision trees, and random forests, will be introduced.
In the concluding phase, the final project will require students to engage in a practical application of their acquired skills and concepts. This project will involve working with R and/or Python to demonstrate proficiency in the tools and methodologies learned throughout the course. |
