Getting started with Data
Develop the confidence to interpret dashboards, reports and data outputs to understand, question and apply data insights in real workplace situations.
Your course leader
Jenny is a Data Science Lecturer at the Leeds Institute for Data Analytics (LIDA), where she teaches across the MSc Data Science (Statistics), MSc Ethical AI and Society, and leads the “Data Analytics for a Sustainable World” module for Leeds International Summer School, as well as CPD modules including 'Getting Started with Data'.
Jenny specializes in creating inclusive online learning environments where students from all backgrounds can develop data literacy and analytical skills. She works in partnership with students to design curriculum and assessment that builds both confidence and competence, making data science accessible to learners entering the field from diverse educational and professional pathways.
Explore the cirriculum
Unit 1
Learn how discrete random variables and probability distributions help model real‑world experiments. Using a simulated medical trial, you’ll explore how results change across repeated runs and build your own datasets to calculate key summary statistics.
Unit 2
Discover how continuous random variables and cumulative distribution functions can model rainfall and flood‑risk data. You’ll work with real datasets, explore extreme events, and practise adapting simple scripts to analyse continuous data.
Unit 3
Explore how the method of moments helps estimate key parameters in queuing systems, using a hospital patient‑flow simulation. You’ll calculate theoretical moments, run estimation scripts, and build confidence interpreting what these parameters mean for system performance.
Unit 4
Learn maximum likelihood estimation through a case study on student engagement and exam performance. You’ll compare different estimation methods, strengthen your understanding of core statistical ideas, and sharpen your coding clarity and interpretation skills.
Unit 5
Use Markov chains to model traffic flow and investigate long‑term congestion patterns. You’ll work with transition matrices, debug simulation code, and learn to communicate the strengths and limits of Markov‑chain models clearly.
Unit 6
Revisit the medical‑trial dashboard to predict patient outcomes using linear and logistic regression. You’ll explore confounding factors, assess model reliability with resampling methods, and gain insight into designing effective, evidence‑led dashboards and reports.