Excel Data Science is an increasingly valuable skill for professionals who want to analyse data, apply statistics, and build predictive models without relying on complex programming tools. This course is designed to show learners how Microsoft Excel can be used as a powerful platform for data science, statistical analysis, and introductory machine learning techniques.

The course begins by building a clear understanding of machine learning concepts and how they translate into Excel-based workflows. Learners then move into hands-on linear regression, where they learn how to prepare datasets, run models, interpret outputs, and understand key statistical measures. As confidence grows, the course expands into multiple regression analysis, focusing on model assumptions, diagnostic checks, and making reliable predictions using real-world data.

A major strength of this programme is its focus on interpretation, not just calculation. Learners develop the ability to read regression tables, understand variability, evaluate model performance, and avoid common analytical errors such as multicollinearity or overfitting. Logistic regression is also introduced for classification problems, including ROC curve analysis and model evaluation techniques, helping learners understand how predictive models are assessed in professional environments.

This course is ideal for those who want practical, job-relevant skills using a familiar tool. The learning approach is structured, applied, and accessible, making complex data science concepts easier to understand through Excel’s visual and analytical features.

Upon completion, learners receive a free course completion certificate. For those who require formal recognition, multiple premium certificate and transcript options are available for purchase. Students also benefit from 5-star rated learner support available 24/7 via email, ensuring help is always accessible throughout their learning journey.