Data Science Machine Learning

Kaushik Mukherjee Address: Gallierweg **, ***** Bonn

Mobile: +491*********

E-mail: ad4usc@r.postjobfree.com

Websites: https://www.linkedin.com/in/kaushik-

mukherjee-23846a146/ (LinkedIn)

https://github.com/kaushikmastro (Github)

PERSONAL Place of Birth: Kolkata, India

Citizenship: Indian

INTERESTS Astrophysics, Data Science, Data Engineering, Data Analysis, Machine Learning, Neural Network, Big Data, Databases, Cloud Computing. EDUCATION Masters in Astrophysics October 2019 – April 2022 University of Bonn

Thesis: Detectability of the higher order Sunyaev-Zeldovich effect with future experiments.

Masters in Applied Physics September 2015 – May 2017 Amity University Kolkata

Thesis: Maximal temperature in a thermodynamical system. Bachelors in Science in Physics July 2010 – May 2015 University of Calcutta

Studied physics, mathematics and computer science. WORK EXPERIENCE IT Student Assistant

University of Bonn

September 2021 – April 2022

Responsible for the maintenance of the website of the economics school of Uni Bonn.

Maintaining data on Excel sheets.

Debugging HTML codes.

Other IT related tasks.

Student Assistant

University of Bonn

September 2021 - November 2021

• Responsible for image annotations at the photogrammetry institute of Uni Bonn.

• Looking for image patterns for ML applications.

COMPUTATIONAL

SKILLS

Programming - Python (proficient), Fortran (basics), C (basics), SQL. Machine Learning Libraries - Scikit-learn, TensorFlow, Keras, NumPy, Pandas, Matplotlib.

Data Visialization Tools- Matplotlib, Seaborn, Google Charts. Operating System- Linux, Windows.

Office- Microsoft Word, Excel, LibreOffice Writer. Others: Jupyter Notebook, SPSS, IBM Db2, Latex, HTML, Github. CERTIFICATIONS AND

INTERNSHIPS

Advanced Machine Learning from Coursera.

• Regression, Gradient Descend, Time Series Forecasting, Neural Network, Scipy, Tensorflow, Keras.

Advanced SQL from Coursera.

• Database models, Queries, Tables.

Data Science Training at Brainnest.

• Data preparation, Data cleaning, Complex data analysis, Statistical theorems, SPSS tool.

IBM Data Engineering from Coursera.

• Relational Database Management System, Big Data, ETL, IBM Db2, NoSQL, Data Pipelines.

LANGUAGES • English (Fluent)

• Bengali (Native)

• Hindi (Native)

• Deutsch (Basic)

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