Not just another Power BI course. A complete programme that prepares you for real situations at work. Excel, SQL, Power BI, Python, AI and storytelling to become a Junior Data Analyst.
No technical prerequisites. If you can use a computer, you can become a Data Analyst.
You work on a single fictional company throughout the bootcamp. Every module brings a new assignment, exactly as at work.
Instead of a string of disconnected exercises, you live a genuine Data Analyst assignment end to end. It is the best preparation for professional life and an excellent portfolio for recruiters.
12 progressive blocks. Every module combines theory, demonstrations and hands-on exercises.
Data fundamentals, roles, the data lifecycle, KPIs and data-driven decisions.
Cleaning, advanced formulas, XLOOKUP, pivot tables, charts and Power Query.
SQL fundamentals for querying and filtering databases.
Joins, subqueries, window functions and performance tuning.
Data import, modelling, table relationships and cleaning in Power Query.
Measures, calculated columns and Time Intelligence functions for time-based analysis.
KPIs, interactive charts, geographic maps, drill down and advanced tooltips.
Connecting to data sources, building visualisations, calculations, filters, interactive dashboards and publishing to Tableau Public.
Data manipulation and visualisation with the essential Python libraries.
Handling missing values, duplicates, outliers and standardising formats.
Correlations, distributions, segmentation and generating insights from data.
Which chart for which message? The golden rules of data visualisation.
Architecture, visual hierarchy, filters and interactivity of an effective dashboard.
Presentation technique, managing nerves and communicating with decision-makers.
Turning data into concrete action and convincing a leadership team.
Using ChatGPT, Claude, Gemini and NotebookLM to speed up your analysis work.
Code faster with the AI assistant: generating Python, SQL and DAX.
Generate visualisations, DAX measures and insights automatically inside Power BI.
Prompting techniques to generate SQL queries, analyses and reports.
Acquisition cost, customer value, churn, funnel and campaign optimisation.
Profitability, cash flow, budget, variance and financial reporting.
Turnover, recruitment, absenteeism and HR metrics.
Inventory management, delivery, turnover and logistics optimisation.
Sales analysis, products, customer behaviour and average basket.
Hospital activity, performance, quality and health metrics.
Design principles, grids, colour, typography and visual hierarchy.
User experience applied to dashboards and interactive reports.
The golden rules of dataviz according to Tufte, Few and Cairo.
The traps of visualisation: misleading charts, scales, 3D and clutter.
Data preparation, cleaning and transformation with visual no-code workflows. Blending, macros and pipeline automation.
Automating recurring report generation with Python and Power BI.
Generate automated presentations from your analyses.
Automated professional Excel reports with formatting and charts.
Published, shareable PDF reports for stakeholders.
Publishing your projects, documenting your code and building your technical presence.
Optimising your profile, publishing data content and growing your network.
Writing a data-focused CV that showcases your skills and projects.
Building an online portfolio that impresses recruiters.
Work on realistic datasets drawn from 7 industries.
Loan analysis, default detection and branch performance.
Claims, fraud detection and customer portfolio analysis.
Sales, churn, product analysis and recommendations.
Cancellations, customer satisfaction and usage analysis.
Hospital activity, waiting times and quality metrics.
Production, quality, maintenance and inventory management.
Recruitment, turnover, training and performance.
The tools most in demand for Data Analyst roles.
Every participant completes a full Data Analyst assignment, exactly as at work:
To earn the certification, every learner must:
3 bonus modules to take your preparation further.
10 weeks, roughly 10 to 15 hours a week. A demanding but manageable pace.
Three levels of support. The same programme, with different guidance.
Launch prices reserved for the waiting list. They will be guaranteed to pre-registered members when the cohort opens, with no payment before.
Professionals who launched their career in data.
"I was an accountant and knew nothing about data. In 10 weeks I landed a Junior Data Analyst role with a 40% pay rise. The programme is clear and progressive."
"Working on a single fictional company for the whole bootcamp is brilliant. You really understand the job. My portfolio impressed recruiters."
"The AI for Data Analysts block gave me an enormous edge. I write SQL queries and DAX measures three times faster than my colleagues. An investment that pays for itself quickly."
Join the next cohort and launch your career in data.