Where you train.
From Bachelor to PhD
DATEXIS trains the next generation of data scientists, NLP engineers, and AI researchers. Students join real projects from the first semester and ship code, papers, and demos alongside our researchers.
TRACK 01
MSc Data Science
Four-semester program at Berliner Hochschule für Technik. DATEXIS contributes 5 courses and supervises master theses on active research projects.
120 ECTS
4 semesters
5
DATEXIS courses
TRACK 02
PhD Training
We train PhD researchers in partnership with selected universities, focusing on deep learning for ‘small data’ environments where training sets are limited. Our candidates work on fully funded projects, backed by government or industry grants, within the ‘Data Science+X’ Graduate School.
~5
years
CURRENT IN CURRICULUM
What’s being taught by DATEXIS
DBS1 Database Systems
BACHELOR- Representations and Models: ER/M, relational Model, normal forms
- Query Processing: Relational operators, SQL, query optimization
- Integration: JDBC, transaction management
- Hot topics, such as platform economy, data mining in a database
EDM: Enterprise Data Management
MASTER- Data Value: Platform economy, data products
- Data Mining: Clustering, Classification, measuring success
- Search: query intentions, retrieval models (TF/IDF, Page Rank, Language Models)
- Selected topics in deep learning and text mining
We cooperate with companies in student projects, such as Zalando, SpringerNature, HERE, WebTrekk, Heise.de etc. Students can also combine projects in EDM with their master thesis in the next semester.
Business Intelligence
MASTER- Data warehousing overview
- ETL and ELT
- OLAP operators (with a focus on the in-memory RDBMS Exasol)
- Data value: Platform economy, data products
- Your cap stone project/Your startup project (I)
Text Mining
MASTER- Introduction to foundation models for text
- Distributional Semantics
- LLM Architectures, Pre-, Mid and Post Training
- RAG, Reasoning and Agents
- Explainability and Benchmarking
- Hot topics
Enterprise Data Science
MASTER- Data Science Organizations
- Iterative Data Product Design and transfer from research into products
- Platform economy and data products
- Researching for scientific literature, methods and data sets
- Advanced AI topics, Economic Effects of AI
Students can also combine projects in EDS with their master thesis in the next semester.
HOW IT WORKS
Write your thesis with DATEXIS
Thank you very much for your interest in writing a master’s thesis in collaboration with DATEXIS. When deciding on a topic, please refer to our focus areas and current publications.
01
Initial meeting
A short coordination meeting, for example after the Enterprise Data Management lecture.
02
Two-page exposé
Present your idea, context within our research areas, relevant literature, and methodology.
03
Go / No-go decision
After submitting the exposé, we jointly decide whether your work fits the focus areas of DATEXIS.
04
Research & writing
~3 months (3-4 days/week)
for concept, implementation, evaluation. ~2 months for writing.
Regular Colloquium
If there is a “go”, we recommend participating in our regular colloquia, where students exchange ideas with each other and receive feedback on their progress. Participation is strongly encouraged after the go-decision. For structuring and organizing your thesis, we provide an orientation guide.
Access our orientation guide for structural requirements, or explore our past graduates to see the impact of our alumni.
THESIS TOPICS
Available thesis topics
Each of our PhD candidates’ profiles lists their open thesis topics. Browse to find one that fits, and contact Prof. Löser via email to apply.
ACADEMIC EXCELLENCE