Fundamentals of Data Analytics & Visualization using Python
About This Course
This course provides learners with a structured introduction to the practice of data analytics and visualization using Python. It equips participants with the ability to script, automate, and extend simple data workflows, giving them greater control and flexibility in handling datasets. Learners will gain hands-on experience working with curated examples, applying descriptive statistics, cleaning and preparing data programmatically, and creating effective visualizations. The course emphasises building digital and analytical fluency for professionals who want to move beyond spreadsheets and develop practical coding skills that underpin modern analytics.
Designed for professionals across industries, this course bridges the gap between spreadsheet-based analysis and advanced analytics by giving participants confidence in Python as a versatile data tool.
What You'll Learn
• Builds foundational literacy in the data analytics workflow (collection, cleaning, descriptive statistics, exploratory analysis, visualization).
• Addresses lack of confidence among diploma holders and professionals in handling datasets beyond spreadsheets.
• Develops coding-based skills in Python (programming language), ensuring reproducibility and flexibility in analysis.
Employment / Job Development Purpose
• Equips learners for entry-level data analysis and reporting roles.
• Supports upskilling of staff in operational, administrative, and executive functions to make evidence-based decisions.
• Provides transferable data skills relevant to multiple job scopes, improving employability in digitally transformed workplaces.
Industry Relevance
• Applicable across sectors such as business services, healthcare, logistics, finance, and education.
• Enhances organisational capacity for productivity, risk management, and process improvement.
• Strengthens ability of staff to interpret and communicate insights that drive efficiency and informed decision-making.
Entry Requirements
Minimally a general diploma with some basic knowledge of statistics and mathematics. The participant must have completed and attended the 3-day NUS Python Programming course.