Small cohorts
Capped so that every submission gets written feedback from the person who taught the session — not a checklist from an assistant.
Loreon Academy
Learn from people
who ship.
Every session is taught by engineers from our delivery team, working on client systems the same week. You get current practice, real trade-offs, and the parts the tutorials leave out.
The premise
Courses are
everywhere.
Review is not.
Almost anyone can now learn the syntax for free. What is scarce is someone senior reading your work and telling you precisely why it would not survive a production incident.
So the Academy is built around review, not lectures. You build; we tear it apart the way we tear apart our own pull requests; you rebuild. Cohorts stay small for exactly that reason.
Real datasets
Messy, incomplete, ambiguous data of the kind you will actually be handed. No pre-cleaned toy files.
Portfolio out the other end
You finish with a deployed capstone and a written technical narrative you can defend in an interview.
Programmes
Six ways
to work with us.
Three cohort tracks, one-to-one mentorship, private training for organisations, and a small number of internship placements. Dates and fees are shared on enquiry.
Data Science &
Machine Learning
Python for analysis, statistics that matter in practice, feature engineering, supervised and unsupervised modelling, honest validation, and deployment of a model behind an API with monitoring attached. Closes with a capstone on a real dataset.
Data Analytics &
Business Intelligence
SQL to a professional standard, data modelling, warehouse thinking, dashboard design that respects the reader, and the analytical framing that turns a request for "a report" into a question worth answering.
Software
Engineering
Building and shipping a real web application: version control discipline, API design, databases, testing, review culture, CI/CD and deployment. Weighted toward the habits that make a hireable engineer.
One-to-one
Mentorship
For career switchers and early-career engineers. Fortnightly sessions, code and portfolio review between them, and a plan pointed at a specific role. Honest assessment included — even when the answer is "not yet".
Corporate &
Team Training
Private programmes built on your stack, your data and your conventions. Common requests: SQL and analytics for non-analysts, Python for engineering teams, applied AI for product and operations leads, and data-literacy sessions for management.
Internships
A limited number of placements each intake, working alongside our engineers on real client and internal projects. Supervised, reviewed, and treated as a job rather than an observation exercise.
Curriculum
What gets
covered.
Weighted toward practice. Every topic is taught against a dataset or a codebase, never as slides alone.
- /Foundations of data analysisFraming a question, choosing a method, and knowing what a result does and does not support.
- /Excel for business analyticsModelling, lookups, pivots and clean workbook structure — the tool most organisations actually run on.
- /SQL for data managementJoins, aggregation, window functions, and writing queries someone else can maintain.
- /Python for data analysispandas, visualisation, reproducible notebooks, and the transition from notebook to production script.
- /Power BI & TableauData modelling inside BI tools, DAX fundamentals, and dashboard design that respects the reader.
- /Data cleaning & interpretationHandling missing, duplicated and contradictory records — then communicating the caveats honestly.
- /Machine learning & AISupervised and unsupervised modelling, validation discipline, and deploying a model behind an API.
- /Project-based capstoneA real dataset, a real deliverable, and a review as demanding as the ones we run internally.
How a track runs
Build, review,
rebuild.
The rhythm is deliberately repetitive. Competence comes from the loop, not from the lecture.
Fit call
A short conversation about where you are and what you want next. We will tell you if a different track — or a different provider — suits you better.
Foundations
Live sessions with weekly assignments. Every submission comes back annotated, with a specific thing to fix before the next one.
Capstone
A project you choose, scoped with a mentor, taken all the way to deployed and documented. Reviewed like client work.
Launch
Portfolio and CV review, interview preparation, and a mock technical interview with an engineer who runs real ones.
We would rather turn someone away than take a fee for a programme that will not change their prospects. That filter is the whole point.
Loreon Academy — admissions principle
Fit
Who this
is for.
- ✓Graduates with the theory but no shipped workYou can explain gradient descent and have never deployed anything. We fix the second half.
- ✓Career switchers from adjacent fieldsFinance, engineering, sciences, operations — people with domain judgement who need the technical craft.
- ✓Analysts ready to go deeperComfortable in spreadsheets and stuck there. Moving to SQL, modelling and a proper warehouse.
- ✓Teams inheriting a new stackOrganisations that just adopted a warehouse, a BI tool or an AI workflow and need their people fluent quickly.
- ✕Anyone looking for a certificate onlyWe do not award participation credentials. The output is the work, and the work is reviewed.
Admissions
Start with the
fit call.
Tell us which track interests you and where you are starting from. We will send dates, fees and an honest view of whether it is the right move.