Liora Data Scientist Bootcamp
The Liora Data Scientist Bootcamp is a 400-hour French remote hybrid training path for becoming a data scientist, combining Python/data foundations, machine learning, deep learning, LLMs, data engineering, MLOps, a 120-hour project, cloud certification exposure, and career support.
Key points
- Liora offers the Data Scientist path in two formats: a 3-month intensive bootcamp at 35-40 hours per week, or a 9-month part-time rhythm at 10-12 hours per week [src-050].
- Both formats total 400 hours and include about 120 hours of project work, with learners working in pairs or trios on real, uncleaned data and presenting projects through quarterly Data Days [src-050].
- Admission expects a level 6 certification or equivalent in IT/digital fields plus a good math level, with possible derogation through application review and written test [src-050].
- The curriculum covers Python, NumPy, Pandas, Matplotlib, Seaborn, Plotly, Linux/Bash, Git/GitHub, Pytest, Scikit-learn, bagging/boosting, clustering, regression, anomaly detection, ARIMA/SARIMA, PCA, SHAP, text mining, BeautifulSoup, TensorFlow, PyTorch, Hugging Face, LLMs, GenAI, SQL, PySpark, Docker, and MLflow [src-050].
- The certification layer includes a Data Scientist certificate from Ecole des Mines Paris – PSL Executive Education and block 2 of the RNCP38587 level 7 AI engineering certification delivered by ANAPIJ [src-050].
- Liora includes a one-day AWS Cloud Practitioner preparation track, taught remotely by certified Amazon Authorized Instructors, as part of the Data Scientist path [src-050].
- The syllabus frames employability through career coaching, alumni resources, salary expectations, funding options, accessibility accommodations, and pathways toward data engineer, AI engineer, ML/deep learning engineer, DevOps, and related roles [src-050].
Related entities
Related concepts
- Data Science & AI Bootcamp
- Retrieval-Augmented Generation (RAG)
- Continuous Agent Evaluation
- AI Product Experimentation
- Offline Evals to Online Experiments
Source references
- [src-050] Liora – “Liora Data Scientist Syllabus” (2026-01)
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