AI-augmented data analyst
Answer a business question with figures, and defend the answer.
- Block code
- DATA-ANA
The format
Three months, two hours a day.
- Certificate programme · 128 h
- Two hours a day
- 250,000 F — the same fee for all sixty
- All in the same format, at the same fee.
The qualification
A CQP under MINEFOP accreditation.
- Leads to the CQP — Certificat de Qualification Professionnelle, which the ministry used to call the AQP.
- Awarded under MINEFOP accreditation.
- The full programme for the same profession remains open to anyone aiming for the complete qualification.
Sessions
A new session opens every quarter.
Next intake: Monday 5 October, with enrolment open until 9 October. The following one starts on 4 January 2027.
- First-quarter intake — enrolment closes on 9 October5 Oct.
- Second-quarter intake — 20274 Jan.
Objectives
What you will be able to do.
Describe a distribution and read a cross-tabulation without drawing the wrong conclusion
Distinguish correlation from causation, and say so to whoever commissioned the work
Explore a real dataset: profile, volume, anomalies
Handle missing values and outliers, standing by the choice made
Choose the chart that answers the question asked
Build a coherent dashboard and publish it
Evaluate a simple model and state what cannot be predicted
Programme
Four modules.
Module 0132 h Module 0232 h Exploring and preparing a real dataset
Module 0332 h Visualisation and presenting to a decision-maker
Module 0432 h AI in support of analysis: assistants and simple models
Who it is for
Who it is aimed at.
- Learners comfortable with figures and spreadsheets. No prior knowledge of statistics is required; the block starts from describing a distribution.
Afterwards
Where it leads.
- Data analyst, research officer, management controller with data tools. Natural next step towards steering by indicators (Business intelligence and steering by indicators).
Method
How it works.
Systematic alternation between short theory sessions and practical work, with most of the time spent on practice
Progression from simple to complex: each module builds on what was learnt in the previous one
Realistic role-plays drawn from Cameroonian business cases
Considered use of generative AI as a working tool, in line with the common core
Regular formative assessments and a final integrative project drawing on all four modules
Assessment
How you are assessed.
Formative assessment at the end of each module (graded role-play and practical exercises)
Practical work assessed against competency sheets
Final integrative project, presented and defended before the trainer
One graded assignment per module in the online course space
Tools
What you work with.
Python, pandas and a visualisation library
SQL on a demonstration data warehouse
Power BI or Metabase — dashboards and publishing
An AI assistant for natural-language querying
Anonymised datasets from Cameroonian companies
Keep exploring
In the same field.
Join the next session
Ready to get started?
Sessions open every quarter. Apply now or request the detailed brochure — our advisers will get back to you.