Careers
Data and applied AI technician
Preparing a dataset, training an available model, evaluating it honestly and wiring it into a real use: the data and applied AI technician takes artificial intelligence from demonstration to daily working tool.
What « applied » actually means
Most of the time goes to the data: finding it, understanding it, cleaning it, splitting it honestly between training and evaluation. Training itself builds on existing models rather than architectures designed from scratch. Then comes the part that marks out a serious technician: measuring performance on realistic cases, including those where the model is wrong, and saying so. Integration closes the cycle, with monitoring that detects drift over time.
- Build and document a usable dataset
- Train an available model and tune its parameters
- Evaluate performance on realistic cases and report it
- Integrate a model into a business use and monitor its drift
Uses being deployed in the region
- Risk scoring and fraud detection in banking and microfinance
- Demand forecasting and inventory optimisation in retail
- Document recognition and automation of administrative data entry
- Language processing for French and national languages
- Predictive maintenance on instrumented industrial equipment
The four figures that decide
How long, how many hours in the room or online, how many credits, for what level of responsibility: those four answers are enough to know whether the programme fits your calendar and your plan. They sit here, at the top of the page, rather than at the end of a call with an adviser.
- qualification level
- 5
- months of programme
- 10
- taught hours
- 700 h
- credits
- 70
- competency blocks
- 5
Senior technician and supervisor
Led by an instructor.
1 credit = 25 h of work, 10 of them taught.
Framework of the « Data and Applied AI Technician » qualification, code TP47.
How the framework is built
A professional qualification reads through its blocks: they state what the holder can run alone, and under what conditions. The hours attached to each block show where the framework places the effort. That distribution is a design decision, it is published as such, and it compares block by block with any other programme.
| Competency block | What it covers | Taught hours |
|---|---|---|
| Data processing pipelines | Extraction, transformation, loading, scheduling, error recovery, quality | 190 h |
| Analysis and reporting | SQL, descriptive analysis, indicators, dashboards, distribution | 170 h |
| Deploying models and assistants | Pre-trained models, interface calls, writing instructions, retrieval augmentation, fitting into a process | 200 h |
| Evaluating and monitoring outputs | Test sets, accuracy measurement, drift detection, logging, inference cost | 100 h |
| Professional conduct | Documentation, flagging a doubtful output rather than shipping it, working with the business | 40 h |
Training in applied artificial intelligence
The path to this occupation is chosen on facts: how long, how many hours with an instructor, how many recognised credits and what amount in Guinean francs. The table gathers them for every open option, in the order a candidate reviews them before filing an application.
| Programme | Duration | Credits | Taught hours | Fees |
|---|---|---|---|---|
| Data Science programme — Bac+5 level · Master's degree | 2 years | 120 | 1200 h | 7 200 000 GNF per year |
| Applied AI for Business Certificate · Professional certification | 4 months | 12 | 120 h | 3 200 000 GNF in total |
Answers to the most frequent questions
Is a high level of mathematics required?
The qualification targets application: descriptive statistics, the notion of distribution, performance measurement. Designing new models belongs to the Bac+5 artificial intelligence programme, which mobilises a considerably broader mathematical apparatus.
Does this occupation really exist in the region?
It is taking root through the uses that pay off immediately: risk scoring, forecasting, data-entry automation. Organisations holding usable history — banks, telecoms, retail — open these roles first, and they are the most numerous.
What place for ethics and compliance?
An explicit one. A model that decides on a loan or a hire commits the organisation using it. The framework covers data traceability, explaining a decision and human validation of sensitive cases.
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