Data Science & Exploratory Analysis
Transforming raw numbers into narrative insights through statistical rigour.
Modules4 Sessions
Duration11 weeks
Outcomes5 Skills
Course Overview
In the Architect Phase, you move from logic to large-scale data structures. You will master industrial tools like Pandas and NumPy to clean, manipulate, and analyse high-volume datasets. We focus on exploratory data analysis (EDA) — the art of finding stories in data before models are even built. You'll learn to visualise complex correlations, identify statistical anomalies, and prepare robust data pipelines that form the bedrock of production-grade AI applications.
Tools & Technologies
PandasMatplotlibSeabornScipy
Curriculum
4 ModulesWhat You'll Learn
- Process high-volume datasets using Pandas vectorised operations
- Implement robust data cleaning and outlier detection methods
- Create professional statistical visualisations with Seaborn
- Apply descriptive and inferential statistics to real-world problems
- Construct automated ETL (Extract, Transform, Load) pipelines
Prerequisites
- AI Literacy & Logic