PCAD – Certified Associate Data Analyst with Python (SF)
About This Course
The 3 day - PCAD – Certified Associate Data Analyst with Python course provides a comprehensive foundation in data analysis using Python, equipping learners with practical skills across the full data lifecycle—data collection, preprocessing, statistical analysis, modeling, and visualization. Designed for aspiring data professionals, this course covers industry-relevant tools such as Pandas, NumPy, Matplotlib, Seaborn, and SQL, with a focus on real-world problem solving.
Learners will gain hands-on experience in preparing datasets, performing exploratory data analysis, building statistical models, and effectively communicating insights through visualizations and presentations. The course also emphasizes responsible data handling and coding best practices.
The training prepares learners for the PCAD™ certification exam (PCAD-30-01) and provides them with the skills needed for entry-level roles in data analysis and business intelligence.
Disclaimer: This course is independently developed by NTUC LearningHub Pte Ltd. NTUC LearningHub Pte Ltd is not affiliated with, endorsed by, or certified by Python Institute. The certification is a trademark of Python Institute.
What You'll Learn
LO2 Apply machine learning techniques to gain new insights from data using complex software tools.
LO3 Aggregate data through data mining to uncover new business insights and develop data models for outcome testing.
LO4 Manage the creation of interactive data visualisations that align to organisational domains and key business processes.
LO5 Mine data to uncover meaningful insights that drive continuous improvement and generate new problem hypotheses for data storytelling.
LO6 Develop prototype algorithms and proof‑of‑concept demonstrations using methods to identify and prioritise problems to be addressed.
LO7 Use industry standard tools and techniques for data visualisation in line with organisational procedures in developing new business insights.
LO8 Assess business insights to determine their organisational impact by applying methods to interpret data patterns and their relevance to business issues.
LO9 Determine which data patterns are meaningful and which require further analysis by using data model visualisation.
LO10 Apply predictive data modelling techniques to uncover underlying trends and patterns using s hypothesis testing, statistical and experimental techniques.
Entry Requirements
• The candidate should hold a diploma and have at least 2 years of experience working in an IT-related role.
• Candidates who do not meet the above requirements will be assessed on case to case basis.