Professional Degree in Software Engineering
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Python For Data Science (BDS301)
Python for Data Science (BDS301) introduces students to the fundamentals of Python programming while providing a practical overview of the data science lifecycle. The course emphasizes writing clean, efficient Python code for data analysis, preparation, and visualization.
Through hands-on Python scripting exercises, data wrangling and visualization labs, and real-world projects using libraries like Pandas and Matplotlib, students will learn how to process, analyze, and interpret data. This course prepares learners to use Python effectively in data-driven environments and serves as a foundation for deeper exploration into machine learning and AI.
Learn Python and explore how it's used to power modern data analysis.
Master core structures and algorithms that power efficient software.
Build coding skills while working with real-world datasets.
Build coding skills while working with real-world datasets.
Start coding in Python and understand core data science workflows.
Start coding in Python and understand core data science workflows.
Use Python to collect, clean, and visualize meaningful data.
Use Python to collect, clean, and visualize meaningful data.
Discover how Python libraries turn raw data into insight.
Strengthen computational logic through classic algorithms and techniques.
Students dive into real-world data science tasks using Python — cleaning messy datasets, analyzing trends, and visualizing insights through code. Captured moments show learners writing scripts with Pandas, building charts with Matplotlib, and performing data wrangling exercises to uncover meaningful patterns. Whether exploring CSV files, transforming data structures, or presenting visual findings, these snapshots showcase the development of analytical thinking and practical Python skills in action.
