Data Skills Advanced

Track: Transversal Skills

Provides tools to build organisational alignment and ownership around a shared outcome, and to establish an 'implementation machine' that continually generates, prioritises and delivers innovative solutions. Participants learn the characteristics of an innovation culture and how to lead others through deliberate, proactive innovation.

Track: Transversal Skills

Covers how to organise a data team so members feel empowered and successful, and how to manage that team as it grows. Participants explore the different roles within a data science team and the principles behind high-value-creating teams.

Track: Advanced Data Skills for Professionals

Introduces the Python data science ecosystem, using Pandas to clean, align, sort and merge data through hands-on coding exercises in Jupyter notebooks. Participants also get a first introduction to visualising data and creating charts with Matplotlib.

Track: Advanced Data Skills for Professionals

Explores how to extract value from data and communicate insights effectively, covering the dos and don'ts of good visualisation and building fluency with a 'visual vocabulary' of chart types. Participants learn to use the Python libraries Matplotlib, Seaborn and Plotly, and when each is best suited.

Track: Advanced Data Skills for Professionals

Focuses on identifying and resolving data quality issues using Python and Pandas, including handling missing values, removing duplicates, fixing data types, cleaning text and managing outliers. Participants apply business rules to validate data and produce a clean, analysis-ready dataset from raw, unprocessed data.

Track: Advanced Data Skills for Professionals

Covers the core types and vocabulary of machine learning, then guides participants through building and evaluating supervised models such as linear regression and decision tree classification using Python and Scikit-Learn. The module also covers overfitting, underfitting, and ensemble methods such as Random Forests for improving model performance.

Track: Advanced Data Skills for Professionals

Introduces the practical use of AI and large language models to accelerate data analysis workflows in Python, including a library of reusable starter prompts and more advanced prompting techniques such as iterative refinement. Participants also cover best practices around AI limitations, hallucinations and verification.

Track: Advanced Data Skills for Professionals

A hands-on capstone in which participants apply the skills from the previous modules to clean, analyse and visualise a real dataset, then carry out predictive analytics on it. Datasets may be curated by the instructor team or proposed by participants, with the module finishing on presenting results to colleagues.