Expert en sciences des données spécialité Data Engineering for Artificial Intelligence

• Expert en sciences des données - Code CertifInfo 107213
  • Niveau de qualification : 7 - Savoirs hautement spécialisés

Objectifs

- Maîtriser l'informatique et l'architecture
- Adopter les méthodologies
- Maîtrisez le Machine Learning et le Deep Learning
- Concevez des Clusters de Calcul hautement distribués.

Programme de la formation

Warmup Courses (75hrs) - 6 ECTS

Distributed & Performance IT – 200 Hours / 25 ECTS :
- Cloud Computing - Amazon AWS “Cloud-Computing DSTI Chair” (50hrs) - 4 ECTS
- Cloud Computing – Microsoft Azure (25hrs) - 3 ECTS
- Semantic Web technologies for Data Science developments (25hrs) - 4 ECTS
- Software Engineering Part 1 (25hrs) - 3 ECTS
- Software Engineering Part 2 (25hrs) - 3 ECTS
- Python Machine Learning Labs (25hrs) - 4 ECTS
- Web Engineering (25hrs) - 4 ECTS
Data Management – 180 Hours / 25 ECTS :
- Data Wrangling with SQL (25hrs) - 6 ECTS
- Data warehousing & ETL (25hrs) - 6 ECTS
- Graph Databases – NoSQL – Part 1 (25hrs) - 6 ECTS
- Document Databases – NoSQL – Part 2 (5hrs) - 2 ECTS
- Big Data Ecosystem by Adaltas (50hrs) - 4 ECTS
- Data Pipeline Part 1 & 2 (50hrs) - 8 ECTS
Operational Methodologies - 150 Hours / 16 ECTS :
- Data Laws & Regulations – Philosophies, Geopolitics & Ethics (25hrs) - 2 ECTS
- IT Project Management – PMP-PMI and Agile Approaches (25hrs) - 2 ECTS
- CRM Data Management (25hrs) - 4 ECTS
- DevOps by Adaltas (50hrs) - 4 ECTS
- Cybersecurity (25hrs) - 4 ECTS
Data Science – 125 Hours / 18 ECTS :
- Applied Mathematics for Data Science (25hrs) - 3 ECTS
- Foundations of Statistical Analysis & Machine Learning Part 1 (25hrs) - 3 ECTS
- Big Data Processing with R (25hrs) - 4 ECTS
- Artificial Neural Networks (25hrs) - 4 ECTS
- Deep Learning (25hrs) - 4 ECTS

50 Hours of Support Sessions

Validation et sanction

Certification

Type de formation

Certifiante

Sortie

Bac + 5 et plus