Glossary
Dataset: the raw material of a model
A dataset gathers the observations an analysis or a model rests on. Its preparation decides the reliability of the result long before the algorithm is chosen. Assembling, harmonising, checking representativeness: most of the work happens there.
What a dataset must carry
A dataset gathers observations described by variables. Preparation takes up most of the work: bringing sources together, harmonising formats, handling missing values, checking the sample genuinely represents the target population, then setting aside a share for evaluation. The data and artificial intelligence field holds 67 modules in the catalogue.
- Observations, variables and a clearly stated target population
- The evaluation share is set aside before any training begins
- 67 modules in the data and artificial intelligence field
From raw data to a ready dataset
The Data Science programme has candidates assemble a complete dataset from heterogeneous sources, through to the training and evaluation split. The Artificial Intelligence programme works on representativeness: what the dataset contains determines what the model will be able to handle once in service.
- 01
1 — Bring the sources together
Internal databases, operational files, field readings: each source arrives in its own format.
- 02
2 — Harmonise
Units, dates, identifiers and labels are brought to a single documented form.
- 03
3 — Check representativeness
The sample is compared with the target population: that check is what makes the result transferable.
- 04
4 — Set aside the evaluation
A share is set aside before any training and serves only to measure the final model.
Programmes that have you prepare one
2 catalogue programmes put “Dataset” to work: 240 credits and 2400 taught hours in total. The official rule holds throughout — one credit stands for 25 hours of work, 10 of them taught. Every line below is recomputed from the programme page: level, duration, credits, taught volume and fees in Guinean francs appear exactly as filed in the official catalogue.
| Programme | Level | Duration | Volume | Fees |
|---|---|---|---|---|
| Data Science programme — Bac+5 level | Master's degree | 2 years | 120 credits · 1200 taught hours | 7 200 000 GNF per year |
| Artificial Intelligence programme — Bac+5 level | Master's degree | 2 years | 120 credits · 1200 taught hours | 7 800 000 GNF per year |
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