Applied Data Analytics & Visualization using Python
About This Course
In today’s data-driven economy, organisations require professionals who can go beyond descriptive analysis and generate actionable insights from complex datasets. This course builds on the Foundations of Data Analytics & Visualization and equips learners with applied data science techniques using Python to solve practical business problems. Participants will revisit core analytical methods and extend them with predictive and segmentation approaches such as regression, classification, clustering, principal component analysis, and text analysis.
The course also introduces advanced visualisation and dashboard design in Python, focusing on creating responsive and interactive visuals to communicate insights effectively to different stakeholders. Through hands-on coding exercises and a capstone project, learners will gain confidence in applying Python to real-world business contexts, transforming raw data into compelling stories and actionable recommendations.
What You'll Learn
• Build on foundational data analytics skills to apply intermediate to advanced data science techniques in Python.
• Strengthen competencies in predictive and segmentation methods (e.g., regression, classification, clustering, principal component analysis).
• Develop ability to handle unstructured datasets such as text, broadening the scope of data sources that can be analysed.
• Enhance skills in dashboard creation and advanced visualisation for effective data storytelling.
Employment / Job Development Purpose
• Support career progression into roles such as data analyst, business analyst, reporting specialist, or business intelligence (BI) developer.
• Enable learners to move from descriptive reporting to providing forward-looking recommendations for strategy and operations.
• Equip participants with applied coding and analytical skills that are transferable across functions and industries.
Industry Relevance
• Applicable across sectors adopting data-driven practices, including finance, healthcare, logistics, manufacturing, retail, and government.
• Improves organisational capacity to leverage advanced analytics for efficiency, customer engagement, and operational improvement.
• Strengthens workforce readiness to support digital transformation through actionable, Python-based analytics workflows.
Entry Requirements
The participant must have completed and attended the 3-day NUS Python Programming and 3-day Fundamentals of Data Analytics & Visualization using Python course.