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Titre RNCP 100% CPF

Chef de projets en intelligence artificielle et science des données (MS) - Data Integration and Processing for Value Creation

INSTITUT SUPERIEUR DE L AER ONAUTIQUE ET DE L ESPACE

5 250 €à partir de
Durée variabledurée
0session active
Haute-Garonnelieu

Objectifs de la formation

Bloc 1 : Concevoir et développer un projet d'Intelligence Artificielle et de Sciences de Données
Bloc 4 : Organiser l'extraction, la mise en forme et le stockage en temps réel de données massives structurées ou non sur des plateformes Cloud

Programme

3 modules de 4 jours : AIBT101, AIBT102 et AIBT103.
AIBT101 - Introduction to modern AI (28h):
- AI Basics;
- Landscape and flagship algorithms on Supervised;
- Unsupervised and Reinforcement Learning;
- Understanding the relationship between problem framing;
- Types of data available;
- Actual business outcomes and the applicable algorithms;
- Business intelligence and business models;
- Major success stories of Business and AI;
- Google's Self-driving car; IBM Watson's Medical diagnosis;
- DeepMind's Alpha Go beating the World champion of Go;
- Airbus building the Skywise platform;
- AI to deliver prescription for manufacturing.
AIBT102 - Data integration and exploration (35h):
Data Warehousing: History and recent evolutions, Extract-Transform-Load process, Architecture, Key functions, Layers
Data quality: Indicators, improvement, assurance, control,
Data visualization: visual perception, effective graphical display, tools.
AIBT103 - Big data processing (35h)
Distributed computing with Spark: History, MapReduce paradigm, Hadoop Stack, Hadoop Distributed File, System, MLlib Machine Learning library.
Virtualization and cloud computing: Different approaches to virtualization, Economical models, Technical benefits (snapshots, dynamic deployment and migration, failover...), cloud engines (principles, deployment examples, node choices).
Docker: Fundamental differences w.r.t. virtualization, Docker components, Tools.

Résultats attendus

Learning objectives After completing this course, participants will be able to:
- Explain the key components of ETL-based data warehousing;
- Set up indicators on data quality and management;
- Perform a simple data visualization task;
- Implement the distribution of simple operations via the Map/Reduce principle in Spark;
- Connect on a cloud computing engine (e.g. Google Cloud Platform) and launch a simple task;
- Deploy a Docker container.

Les points forts

- Data warehousing and visualisation
- Data quality management
- Introduction to Big Data processing
- Practical courses
- Formateurs experts de l'ISAE-SUPAERO, de l'IRT Saint Exupéry et de l'industrie.
- Formation labellisée ANITI.

La certification

Chef de projets en intelligence artificielle et sciences des données (MS)

RNCP 40551 RS -1 CertifInfo 118959

Organisme & lieu

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