Data Science
A live, mentor-led, 16-week programme that takes you from data fundamentals through Excel, SQL, Power BI, Tableau and Python into machine learning and deep learning. Eight connected modules, hands-on work on business-style datasets, and a portfolio you can walk an interviewer through. Three months of placement support included.
- TEACHING
- 6 months
- PLACEMENT SUPPORT
- 3 months
- FORMAT
- Live · Saturday & Sunday
- CLASS SIZE
- 24, never more
- NEXT INTAKE
- Dates to come
- FEE
- £2,699
From a spreadsheet to a model that learns from data.
Data science starts long before any algorithm. It starts with a business question, a messy dataset and the judgement to know whether an answer can be trusted. This programme teaches that chain in order: clean and organise data in Excel, query it with SQL, present it in Power BI and Tableau, analyse it with Python and statistics, then move into machine learning and deep learning.
Every module pairs concepts with a hands-on business scenario drawn from sectors such as retail, banking, healthcare and marketing. Because each tool builds on the last, the models you meet in the final weeks rest on data skills you have already practised.
Classes are live at weekends with an instructor who works in the field, two sessions a week over sixteen weeks. Three months of placement support comes with every cohort.
Is this the right course for you?
This is for you if…
- You want one continuous route from analytics fundamentals to machine learning, not separate courses.
- You are changing career or upskilling, and want a portfolio built across several tools.
- You can commit two live sessions a week for sixteen weeks, plus practice between sessions.
This is not for you if…
- You want specialist depth in machine learning. Weeks 13–16 are an introduction, not an ML engineering course.
- You need a regulated qualification for visa or professional registration. This is not one.
- You cannot attend live sessions. The recordings are a backup, not the format.
Sixteen weeks, module by module
No competitor in this market publishes module-level detail. We do, because it is the thing you are actually buying.
- Weeks 1–2Introduction to data scienceThe four types of analytics, types of data, the data science lifecycle and business use cases.DATA FUNDAMENTALS
- Weeks 3–4Advanced ExcelCleaning and managing data, charts, pivot tables, lookups and a one-page summary report.EXCEL
- Weeks 5–6SQLQueries, joins, subqueries, CASE logic, window-function basics, and a live doubt-clearing session.SQL · MYSQL
- Weeks 7–8Power BIPower Query, data modelling, DAX, interactive reports, publishing and scheduled refresh.POWER BI · DAX
- Week 9TableauConnecting to data, building visualisations and designing dashboards for storytelling.TABLEAU
- Weeks 10–12Python for data analyticsPython basics, NumPy, pandas, visualisation, descriptive statistics, distributions and correlation.PYTHON · STATISTICS
- Weeks 13–14Machine learningRegression, classification, unsupervised learning, model evaluation and optimisation.ML
- Weeks 15–16Deep learningNeural networks, CNNs for image data and RNNs for sequential data.DEEP LEARNING
Six things you can show after sixteen weeks.
- An Excel one-page summary report built on pivot tables, lookups and logical functions
- A set of SQL queries that answer business questions across multiple tables
- An interactive Power BI report using DAX measures, published and shared
- A Tableau dashboard designed for readability and storytelling
- A Python analysis using pandas, Matplotlib, Seaborn and core statistics
- Machine learning models for regression, classification and clustering, with an introduction to neural networks, CNNs and RNNs
You finish with work you can show, and people you can name.
Marcus Bell
Analytics Manager, Northgate
Teaches weeks 1–9
Dr Naomi Clarke
Lead Data Scientist, Halden Systems
Python, machine learning and deep learning
Next intakes for Data Science
The next Data Science dates are being scheduled. Book a call and we will tell you as soon as places are released.
Book a callPay in full
£2,699
Instalments
6 monthly payments of £449.83, no interest
Employer sponsorship
We invoice your employer directly
Refund
Full refund to end of week two
Three months of placement support.
It runs alongside and after the programme:
- Role mapping: which analyst, BI, reporting and data science roles fit your background
- CV and LinkedIn rebuilt around tool-specific skills
- A target-employer shortlist and guidance on where to apply
- Mock interviews and professional communication coaching
- Salary negotiation preparation
- What UK employers expect at CV, interview and offer stage
We support your search. We don’t promise a job, because no honest provider can.
Asked before every Data Science cohort
Do I need to know how to code before I start?
No. The first nine weeks are data fundamentals, Excel, SQL, Power BI and Tableau. Python starts in week ten, once you are comfortable with data. What you do need is to put the practice hours in between sessions.
How much maths is there, honestly?
You need to be comfortable with percentages, averages and reading a chart. Descriptive statistics, distributions and correlation are taught in weeks ten to twelve, before any machine learning.
How deep does the machine learning go?
Weeks thirteen to sixteen are an introduction: regression, classification, unsupervised learning and model evaluation, then neural networks, CNNs and RNNs. Four weeks gives you a working grounding, not specialist depth.
How is this different from Data Analytics?
Both start with Excel, SQL, Power BI, Tableau and Python. Data Science runs four weeks longer and carries on into machine learning and deep learning.
What if I miss a session?
The recording is up the same day and your mentor covers it in your next 1:1. Attendance matters for the certificate — you need 80% across the programme — but a handful of missed sessions will not put that at risk.
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