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Masters in Machine Learning

Eberhard Karls University, Tübingen

Masters Program

Machine Learning ,

Department of Data Science and Business Intelligence

Overview

Masters in Machine Learning at the prestigious Eberhard Karls University, Tübingen is an opportunity for students to enhance their knowledge, skills, and career through innovation and research. Being a renowned university, Eberhard Karls University, Tübingen receives enough funds to ensure the best education facilities for its students across all programs.

This post-graduate program offered on a full time basis has a well-designed curriculum that perfectly blends theory and practical learning. It prepares the students for their professional life to reach new heights of success.

Masters in Machine Learning at Uni Tuebingen is ranked globally by estimated organisations. Such recognition speaks volumes about the course’s importance and effectiveness in the present scenario.

The top-notch faculty, modern facilities, and the aura of creativity and innovation in the Uni Tuebingen campus is a life-changing experience for the students looking forward to kickstarting or upgrading their careers. Overall, a Masters in Machine Learning at Eberhard Karls University, Tübingen is an excellent opportunity to grow into a learned professional and bring new developments in the world.

Course Highlights

Program duration

24 Months

Degree type

Data Science and Business Intelligence

Semesters

4


Delivery type

Full time

Delivery medium

On Campus


Tuition fees

waived flag Fees mentioned may differ from the actual amount.

Annual tuition fees

$3,000

Full course fees (24 months)

$6,000

Application Fee

NA

Application date

01/02/2023

Deadlines

Application Deadline

Rolling

Pre-Requisities

Application pre-requisites

  • Online application
  • Application fee
  • Official Transcripts
  • CV
  • Letter of motivation
  • Proof of English language proficiency

Test score requirements

Minimum English Scores

TOEFL

94

IELTS

7

Course Details

Core subject areas

  • Deep Learning
  • Statistical Machine Learning
  • Probabilistic Inference and Learning

Class profile

Total no. of students in the class

99


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