Data Science Programming
Study Case Using R and Python
In today’s digital age, data plays a crucial role in decision-making across various industries. Data Science Programming is essential for extracting meaningful insights from large datasets, automating analytical processes, and developing predictive models. Proficiency in data science programming enables professionals to analyze data effectively, optimize workflows, and create intelligent systems that drive innovation and technological advancement.
This module provides a comprehensive introduction to the fundamental concepts and practical applications of programming in data science. It covers key topics such as data manipulation, statistical analysis, machine learning, and automation using widely recognized programming languages like Python and R. Readers will have the opportunity to gain hands-on experience in handling real-world data, creating insightful visualizations, and applying statistical models to uncover patterns and trends.
Furthermore, the module explores data preprocessing, transformation, and integration, which are essential steps in preparing raw data for analysis. Readers will also develop practical skills in debugging, testing, and optimizing code to enhance efficiency and accuracy in data-driven projects.