Refactor code structure for improved readability and maintainability

content/experiences/hackathon-cnd.md

@@ -0,0 +1,19 @@
+---
+title: Hackathon CND - Machine Learning for Cybersecurity
+type: Hackathon
+company: Commissariat au numérique de défense (CND), French Armies ministry
+companyUrl: https://www.defense.gouv.fr/cnd
+location: Fort du Mont-Valérien, Suresnes, France
+startDate: 2025-11
+endDate: 2025-11
+duration: 3 days
+description: Developed a Python ML pipeline during the CND hackathon to classify system logs for bug and attack detection. Implemented feature extraction and preprocessing, trained and evaluated models (tree-based and lightweight neural), tuned thresholds to favor recall, and delivered a realtime prototype with visualization and reproducible code in collaboration with CND engineers. Implemented a Streamlit application to test the classifier interactively and used an LLM to generate contextual help explaining the likely origin and indicators of detected bugs or attacks for end users.
+tags:
+  - Python
+  - Machine Learning
+  - AI
+  - Cybersecurity
+  - Streamlit
+  - LLM
+emoji: 🔒
+---

content/experiences/hackathon-dirisi.md

@@ -1,19 +0,0 @@
----
-title: Hackathon CND - Machine Learning for Cybersecurity
-type: Hackathon
-company: Commissariat au numérique de défense (CND), French Armies ministry
-companyUrl: https://www.defense.gouv.fr/cnd
-location: Fort du Mont-Valérien, Suresnes, France
-startDate: 2025-11
-endDate: 2025-11
-duration: 3 days
-description: Developed a Python ML pipeline during the Dirisi hackathon to classify system logs for bug and attack detection. Implemented feature extraction and preprocessing, trained and evaluated models (tree-based and lightweight neural), tuned thresholds to favor recall, and delivered a realtime prototype with visualization and reproducible code in collaboration with CND engineers. Implemented a Streamlit application to test the classifier interactively and used an LLM to generate contextual help explaining the likely origin and indicators of detected bugs or attacks for end users.
-tags:
-  - Python
-  - Machine Learning
-  - AI
-  - Cybersecurity
-  - Streamlit
-  - LLM
-emoji: 🔒
----

content/experiences/sevetys.md

@@ -1,5 +1,5 @@
 ---
-title: Data Analyst Intern
+title: Data Engineer Intern
 type: Internship
 company: Sevetys
 companyUrl: https://sevetys.fr
@@ -7,7 +7,7 @@ location: Paris, France
 startDate: 2025-06
 endDate: 2025-07
 duration: 2 months
-description: At Sevetys, I worked as a Data Analyst on topics related to client and patient data. My responsibilities included Python development using PySpark on Microsoft Azure, data modeling based on business needs, and ensuring data quality. This experience allowed me to deepen my data engineering skills while working autonomously in a demanding cloud-based environment.
+description: At Sevetys, I worked as a Data Engineer on topics related to client and patient data. My responsibilities included Python development using PySpark on Microsoft Azure, data modeling based on business needs, and ensuring data quality. This experience allowed me to deepen my data engineering skills while working autonomously in a demanding cloud-based environment.
 tags:
   - Python
   - PySpark