Transforms anyone who works with data regularly into an Advanced Data Analyst or Data Scientist.
The Decoded Data Academy embeds cutting-edge data skills at scale across any organisation.
Modular by design this allows for the creation of highly specialized tracks depending upon the needs and desires of clients.
You can go ‘broad and wide’ to cover the fundamentals of machine learning, or ‘focused and deep’ to concentrate on the skills and techniques most pertinent to your organization.
For learners in England, we deliver our Data Academy programmes to align with a number of different Data Apprenticeship Standards, funded through your organisation's Apprenticeship Levy.
#1 Tech Integration: We seamlessly integrate our program within your existing IT infrastructure.
#2 Live data: We embed your real-life, live company data into the learning journey, enabling learners to apply their new skills to real-world business challenges.
#3 Real-world projects: We coach learners to apply their skills to live projects in your business which senior leadership have identified as being of strategic importance.
#4 Mentorship: Fusing deep technical knowledge and heightened commercial awareness; our data scientist mentors guide learners on how to apply their new skills to business projects in real-time.
How many employees in your business have the ability to work with data, but just need to learn the skills?
These are your organisation’s Data High-Potentials. Our admissions process identifies, recruits and fast-tracks them to next-level data skills.
Designed by our product team in New York and London and delivered to over 1000+ learners, with a 96%* programme retention rate.
Cohorts of 25+
In-house cohorts of Data High-Potentials, recruited from across your business.
With a commitment of 16 hours of learning per month.
In-person workshops, 1-to-1 data science mentoring, self-directed practice & projects.
Continuous measurement, evaluation and reporting on the impact which new data skills are creating in the organisation.
The Academy is underpinned by learners becoming fluent in Python.
This provides the basis for a broad range of analytical techniques, working in a notebook environment (such as Jupyter Notebooks), and curating and orchestrating different data tools, libraries and models to solve problems.
Our full syllabus features 15 modules. These range from unsupervised machine learning techniques such as k-means clustering, through to more predictive techniques such as regression and classification, and specialist techniques such as time series and text analysis.
We work with our clients to select six of these modules and create a 26-week pathway, curated for maximum relevance and impact.
Want to find out more? Leave your details and we’ll be in touch.