Pierre Meyssonnier

Data Processing for AI:

• Database modeling
• Structured data manipulation
• Data warehousing with SSIS
• Data modeling lab for AI
• Business Intelligence lab

Programming for AI:

• Advanced Machine Learning algorithms in OOP with NumPy
• MongoDB
• Algorithms and data structures for AI with Python
• Object-Oriented Python development
• AI libraries in Python: data mining and machine learning
• Data cleaning and preparation with NumPy and Pandas
• Flask

Data Analysis and Data Science Tools:

• Statistics with Matplotlib and Seaborn
• Power BI
• Deep Learning

Advanced Aspects and Applications of AI:

• Individual AI Development Project
• Reinforcement, consolidation, and going beyond in AI topics

• Developed operational and financial dashboards (KPI, data quality, and reporting) using Business Objects and Qlik Sense.
• Designed and implemented ETL workflows in PL/SQL, Pentaho, and KNIME.
• Tools: Oracle 20, SQL Developer, Python.

• Designed and optimized Business Object reports for KPI and data quality monitoring.
• Streamlined ETL processes for the DG BUG and RTD Data Warehouses using PL/SQL.

• Developed and migrated Business Object universes, dashboards, and reports across public and banking sectors.
• Ensured data quality and created ETL processes using SAS Data Integration and Oracle 10g.

• Provided BI consultancy for Belgacom Mobile, Eurocontrol, Pfizer, and Fortis Bank, focusing on report migration and dashboard development.