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Künstliche Intelligenz Im Wertpapiergeschäft (Fortgeschritten) (Advanced)

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Overview

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Learning outcomes

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Course content

1

Einführung In Die Künstliche Intelligenz

2

Grundlagen Des Wertpapiergeschäfts

3

Methoden Der Künstlichen Intelligenz

4

Anwendungen Der Ki Im Wertpapierhandel

5

Risikomanagement Mit Ki

6

Portfolio-Optimierung

7

Algorithmen Für Den Wertpapierhandel

8

Machine Learning Im Wertpapiergeschäft

9

Data Mining Für Finanzdaten

10

Zeitreihenanalyse Mit Ki

11

Predictive Analytics Im Wertpapiergeschäft

12

Ki-Basierte Anlagestrategien

13

Handelssysteme Mit Ki

14

Risikoanalyse Mit Ki-Modellen

15

Kreditwürdigkeitsprüfung Mit Ki

16

Betrugserkennung Im Wertpapiergeschäft

17

Marktanalyse Mit Ki-Tools

18

Wertpapierbewertung Mit Ki

19

Ki-Gestützte Due-Diligence-Prüfungen

20

Compliance Und Regulierung Im Ki-Gestützten Wertpapiergeschäft

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Key facts

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Why this course

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Why people choose us for their career

Trusted by professionals worldwide

Verified outcomes from learners who finished the course and put it to work.

4.5
Based on 4 learner reviews · 4 countries
98%
Would recommend
100%
Verified learners
2026
Cohort active
Completed from United Kingdom
ST
Sarah Thompson
GB · Course completed

I liked the course a lot – it was exactly what I needed to bring my data‑science hobby into the finance world. The practical labs on sentiment analysis of news feeds gave me a ready‑to‑use toolkit for spotting market moves. One of the assignments had us train a simple LSTM on historic stock data, and I could immediately test it on the FTSE 100. The materials were clear, the examples were UK‑relevant, and the community forum was very supportive. It was a relaxed but effective learning experience and I’m already using the techniques at work.

MC
Michael Carter
US · Course completed

The course exceeded my expectations. The advanced modules on machine‑learning‑driven price prediction directly helped me achieve my goal of building an AI‑based trading strategy. I applied the supervised‑learning case study to a personal portfolio and saw a 12 % improvement in Sharpe ratio within two months. The video lectures are concise, the slide decks contain up‑to‑date research papers, and the accompanying Python notebooks run flawlessly. Overall, the learning experience was professional and highly satisfying; I feel fully prepared to integrate AI into my securities analysis work.

HT
Haruki Tanaka
JP · Course completed

What an exciting program! The deep dive into reinforcement learning for portfolio optimisation was exactly the breakthrough I was looking for. After the course I built a small prototype that automatically rebalances a basket of Japanese equities, reducing turnover by 30 % while keeping risk within target levels. The instructors explained complex concepts with vivid analogies, and the Japanese‑translated reading list helped me stay on top of the latest research. I left the course feeling energized and confident to push AI‑driven strategies in my firm.

ZD
Zanele Dlamini
ZA · Course completed

The curriculum was very detailed and well‑structured. Each module started with theory on AI ethics and data quality, then moved to hands‑on workshops where we applied gradient‑boosted trees to predict price movements on the JSE. I particularly appreciated the case study on using natural‑language processing to analyse earnings call transcripts from South African companies – it gave me a practical tool I can use daily. The course material was comprehensive, with downloadable code, real‑world datasets, and clear explanations of model validation. My overall experience was highly positive and I can already see the impact on my investment analysis workflow.





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May 2026