COURSE CURRICULUM

This course provides a comprehensive foundation in data analytics, combining technical skills with business understanding. It begins with an introduction to the concepts and tools of data analytics, where learners explore the data ecosystem, pre-processing methods, and fundamental analysis techniques. The course also covers relational database management, introducing data modelling, relational theory, and Structured Query Language (SQL) for designing and manipulating databases. Machine learning is addressed in two units: supervised and unsupervised learning. Both units emphasize applied techniques over theoretical statistics, with hands-on practice involving real-world scenarios, unbalanced data sets, model evaluation, and best practices in training and testing models. Learners also develop skills in data storytelling and visualization by transforming data into insightful visuals to support business decision-making, using appropriate chart types and design principles. A capstone project allows learners to integrate and apply their knowledge through a full data analysis cycle—problem formulation, data preparation, modelling, evaluation, and dashboard presentation—mirroring real-world data analyst responsibilities. In addition to technical subjects, the course includes finance management, providing foundational knowledge in financial accounting and financial management principles and their practical application in business contexts. Finally, the introduction to the business environment unit equips learners with an understanding of various business types, functions, and structures, as well as essential marketing principles. It also explores the internal and external factors influencing businesses, the importance of quality, and basic business analysis methods. Overall, this course is designed to prepare learners for the practical demands of a data analyst role by integrating analytics, machine learning, visualization, and essential business knowledge.