Data Exploration and Visualisation
About This Course
This two-day module provides a comprehensive understanding of the characteristics of Big Data and practical hands-on experience in data exploration using Python. It emphasises accessing data via APIs (Application Programming Interface) and converting common file formats into suitable data formats for analysis. Data profiling techniques, including column profiling for descriptive statistics and cross-column profiling for bivariate and multivariate analysis, will also be explored.
What You'll Learn
• Perform data discovery by accessing data from multiple sources and importing various file formats into suitable data formats.
• Create and manipulate NumPy arrays, and produce visualisations using the Matplotlib and Seaborn libraries with Python.
• Conduct data profiling by obtaining descriptive statistics, checking for missing values, and visualising data with common plots.
• Conduct cross-column profiling to analyse relationships between numerical and categorical data through various bivariate and multivariate plots.
Entry Requirements
• Participants should preferably have passed mathematics at least ‘O’ Level or equivalent.
• Participants should be conversant with basic IT skills such as software installation, file management and web navigation.
• Participants are encouraged to complete the Foundation of Data Science before enrolling in this course.
• Participants are required to pass a pre-course assessment to ensure participants have the requisite knowledge of Python programming. This assessment can be waived if participants have completed both Fundamentals in Python (Basic) and Fundamentals in Python (Intermediate).