We are organizing this lecture together with Prof. Dr. Gerard de Melo and the chair of „Artificial Intelligence and Intelligent Systems“ in the fall semester of 2022/2023.
Target group: Students of the HPI Master's Programmes
Lecturers:
Prof. Dr. Gerard de Melo (Chair of Artificial Intelligence and Intelligent Systems)
Tolga Buz (HPI E-School)
If you are a HPI student interested in the course, please check the course's Moodle page.
Goals of the lecture
- Work on and solve practical and realistic problems in small teams
- Provide the partner companies with practical approaches to solving problems in the field of artificial intelligence
Procedure/Organisation
- Start: October 17th, 2022, Duration: 3 Months
- Workload for students: 1 day per week
- After an introductory event for presenting the tasks and finding the teams, the students will work on the solution throughout the semester and then present it at a final presentation.
- Accompanying events, coaching and feedback sessions will take place to support the solution of the tasks and enable further contact points.
Close, practical cooperation with partner companies
- Introduce a Data Analysis/ML challenge with practical relevance
- Participation in the introductory event to present the problem definition and in the final event to receive and evaluate the project results
- Regular feedback sessions with the students (1-4 times per month)
Example topics for challenges
- Exploratory data analysis of a company dataset (e.g., unstructured text data, machine or sensor data)
- Development of a data analytics dashboard to monitor signals extracted from incoming data
- Implementation of a machine learning model based on a suitable real-world dataset in order to tackle a current business / operational challenge
- Automating a manual business process by prototyping an AI-driven approach (e.g., extracting relevant information from incoming documents)
- Devising a data integration strategy to connect multiple existing internal data sources
- Analysis of the current data landscape & identification of data engineering, analytics, and optimisation possibilities
