Data Analyst

A professional development programme building practical data analytics skills

The Imperial College and Corndel Data Analyst Programme establishes a powerful network of data scientists, analysts and database managers at key intersections in your organisation. The programme embeds cutting-edge thinking in machine learning, AI and data science, putting your business at the forefront of innovation. The programme equips professionals with the techniques, skills and knowledge to generate meaningful insights from organisational data that leads to tangible business impact.

Programme Overview 

The 18-month programme is designed to enable professionals across a variety of corporate functions to gain the critical knowledge, skills and behaviours needed to successfully gain business insights. Learners will be manipulate and analyse large volumes of data to inform and enhance key business decisions.

Programme Features:

  • 18-month blended learning delivery model
  • Fortnightly coaching with a Professional Development Expert
  • 16 hands-on workshops delivered by experienced data scientists
  • Bite-sized, practical projects to embed learning¬†
  • Flexible learning content in a range of formats
  • Fully funded through the Apprenticeship Levy

Who is the programme for?

The Imperial College and Corndel Data Analyst Programme is for professionals whose roles will increasingly require them to prepare and analyse large amounts of data and build predictive tools

These individuals are critical champions, specialists and advocates for defining what 'data-driven' means for your organisation.

Business Impact

The Imperial College and Corndel Data Analyst Programme equips professionals with the techniques, skills and knowledge to generate meaningful insights from organisational data that leads to tangible business impact, including:

  • Improved performance based on predictive, automated insights built in-house.
  • Robust analysis throughout the organisation through better designed and managed analytics projects.
  • Increased capacity in centralised highly-skilled functions by building more widespread capability for business-as-usual data analytics tasks.
  • Data analysed more safely and securely within organisational infrastructure.

Essential Data Skills

  • Coding in R and Python to manipulate and analyse vast amounts of internal or external data
  • Identifying trends with advanced techniques such as regression, clustering and classification
  • Communicating meaningful insights with impactful visualisations and dashboards