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Thomas Quadt

Thomas Quadt

Student

Eindhoven University of Technology

Technologies

My Portfolio Highlights

My New Course

Introduction to Python

My New Project

Introduction to DataCamp Projects

Data whisperer, listening closely to the stories hidden within the numbers.

My Work

Take a look at my latest work.

course

Data Manipulation with pandas

course

Introduction to Python

course

Intermediate Python

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

My Work Experience

Where I've interned and worked during my career.

Eindhoven University of Technology | Jan 2019 - Jul 2022

Student Assistant Mathematics and Computer Science

Student assistant for a great variety of courses. Mainly focusing on Machine learning, programming and statistics Student assistant for all the Data challenges. Data challenges are projects for Bachelor students to apply their learned data science skills
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Data Science Association Pattern | Mar 2021 - Jun 2021

Chairman Datathon Committee

ETZ hospital. The datathon introduces participants to anonymized real life medical data and asks them to predict neurological functioning after a surgery

Data Science Association Pattern | Apr 2019 - Nov 2019

Committee Member - IntroWeek Comittee

N/A

Data Science Association Pattern | Sep 2018 - Sep 2019

Secretary Activity Committee

N/A

Eindhoven University of Technology | Jan 2019 - Jun 2019

Teacher support

N/A

Data Science Association Pattern | Oct 2018 - Apr 2019

Committee Member Study Trip Committee

N/A

Jumbo Supermarkten | Aug 2015 - Jul 2016

Sales Assistant

N/A

My Education

Take a look at my formal education

Master, Data Science in EngineeringTU/e | 2023
Bachelor of Data Science Eindhoven University of Technology | 2020
High School Diploma Theresia Lyceum | 2017

About Me

Thomas Quadt

I am a Master's student at TU/e. Currently, I am doing my Master's Thesis on Concept-based explanations for Convolutional Neural Networks. In particular, I have designed a dashboard where users can generate explanations for any CNN.

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