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Each step of my academic journey has refined my understanding of my strengths and passions, leading me to specialize in data, AI, and analytics. This journey reflects my curiosity and commitment to continuous learning.
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I earned a Scientific Baccalaureate (Bac S) with a specialization in Mathematics and honors.
In addition to my core studies, I pursued an option in Chinese and studied English (LV1) and German (LV2) as part of my curriculum.
High school was where my passion for mathematics truly flourished, and my diverse language studies gave me an appreciation for global perspectives, fueling my curiosity to explore and learn.
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During my two years in the preparatory program at Polytech Nancy, I studied a wide range of subjects, including Mathematics, Physics, Mechanics, Computer Science, Chemistry, Thermodynamics, and Programming.
This experience allowed me to build a strong foundation in analytical thainking and technical problem-solving. Despite the program's intensity, I appreciated the diversity of subjects, which solidified my interest in data and mathematics.
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During the engineering cycle at Polytech Nancy, I pursued a specialization in IA2R (Computer Science, Automation, Robotics, and Networks).
While I gained valuable skills in programming and algorithm design, I realized that fields like robotics and networks were not aligned with my interests. This experience was pivotal in helping me clarify my true passion for data analysis and AI development.
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After refining my academic focus, I enrolled at Polytech Nantes to pursue an Engineering Degree in Data & AI through an apprenticeship program. This shift allowed me to concentrate on data analysis, machine learning, and AI development, aligning perfectly with my strengths in mathematics and analytics.
During my time at Polytech Nantes, I studied a variety of subjects, including Advanced Mathematics, Data Science, Machine Learning, Probabilities, Statistics, and Data Visualization. Opting for an apprenticeship provided the opportunity to combine theoretical knowledge with practical, real-world applications, particularly in data-driven projects.
