Computer Programming for Data Science and Artificial Intelligence (CPDSAI) provides students with a practical foundation in programming and computational techniques for data science and artificial intelligence. Using Python as the primary programming language, students learn to acquire, manipulate, clean, analyze, and visualize real-world data using commonly used scientific computing and data analysis libraries.
The course progresses from Python programming, NumPy, data acquisition, and data wrangling with Pandas to data visualization and exploratory data analysis. It then introduces the fundamental machine-learning workflow, including data preprocessing, supervised learning, model evaluation, model selection, cross-validation, hyperparameter tuning, and the construction of reproducible machine-learning pipelines. Students are also introduced to unsupervised learning techniques and practical considerations for deploying data-driven models.
Emphasis is placed on hands-on programming, problem solving, and learning through realistic datasets and computational exercises. By the end of the course, students should be able to transform raw data into useful representations, conduct systematic exploratory analysis, build and evaluate basic machine-learning models, and implement an end-to-end data science workflow using Python and its modern data science ecosystem.
- Teacher: Anushka Ojha
- Teacher: Chantri Polprasert
- Teacher: Wut Yee Aung