Advanced Data Science Programming
Study Case Using R and Python
In today’s digital era, data is a strategic asset that drives decision-making, innovation, and competitive advantage across industries. Advanced Data Science Programming equips professionals with the skills to design scalable workflows, build predictive models, and deploy intelligent systems that transform raw data into actionable insights.
This module goes beyond the fundamentals, focusing on advanced concepts and practices in programming for data science. It introduces modularization and object-oriented programming (OOP) as the foundation for writing clean, reusable, and maintainable code. Readers will also explore API integration for accessing diverse data sources, as well as advanced data wrangling and feature engineering techniques to prepare high-quality datasets for analysis.
The module further delves into predictive modeling and interactive visualization, enabling the creation of models that not only generate accurate forecasts but also communicate results effectively to stakeholders. Emphasis is placed on debugging, testing, and workflow automation, ensuring that projects are reliable, efficient, and reproducible. Finally, learners will gain practical experience in deployment and model monitoring, mastering the tools and methods required to bring data science solutions into production environments and track their long-term performance.
By completing this module, readers will be equipped with the end-to-end programming capabilities needed to tackle real-world data challenges and deliver impactful solutions in research, industry, and beyond.