Issued 22 December 2025
• Data science fundamentals and workflows • Data cleaning, preparation, and feature engineering • Exploratory data analysis (EDA) • Statistical analysis and data interpretation • Data visualization and insight communication • Introduction to machine learning concepts • Supervised and unsupervised learning basics • Model evaluation and performance metrics • Ethical and responsible use of data and AI
Upon successful completion of this professional diploma, learners will be able to: • Prepare and analyze datasets using data science techniques • Apply statistical methods to uncover insights from data • Perform exploratory data analysis and visualization • Understand and apply basic machine learning models • Evaluate and interpret machine learning results • Communicate data-driven insights effectively • Demonstrate foundational competence in data science and machine learning practices
This is your permanent, verifiable record of achievement.
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