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Lab: Hybrid Learning and Applications

This lab offers a comprehensive introduction to using hybrid learning, merging machine learning and deep learning techniques to address complex problems. By integrating foundation models with downstream tasks using various machine learning methods, students explore a range of fascinating applications. They are encouraged to select and research their own project topics, gaining hands-on experience in data preprocessing, model building, evaluation, and optimization. This course is designed to equip students with practical skills to design and implement effective hybrid learning solutions.

Lab Activities

Prerequisites

Required:

Recommended:

Remarks

To be considered for the lab, we ask you to submit a short proposal (maximum a page) describing the project you would like to work on to amllab[at]bit.uni-bonn.de. Please make sure your proposal addresses the following points:

Deadline for proposal submission is Wed, 10 Oct 2026, 23:59 (AOE).

Lecturers

Course Schedule

Date Time Title Location
Wed, 10 Oct 2026 23:59 (AOE) Proposal Submission Deadline  
Fri, 23 Oct 2026 14:00–16:00 HLA Lab Info Remote
Fri, 30 Oct 2026 14:00–16:00 HLA Lab Pitch Remote
Fri, 11 Dec 2026 14:00–16:00 HLA Midterm Remote
Fri, 29 Jan 2027 14:00–16:00 HLA Final Presentation In person
Sun, 28 Feb 2027 23:59 (AOE) Final Report — submit to amllab[at]bit.uni-bonn.de