Dauer
2 Tage
Preise
€
Zielsetzung
Dieser Kurs soll den Teilnehmenden die zentrale Frage beantworten, welcher Mehrwert durch die Verwendung von Data Science in einem Unternehmen geschaffen werden kann.
Zielgruppe
Führungskräfte im Bereich Digitalisierung, Smart Data, Innovation, Data Science Labs, AI Labs, IT, Produktentwicklung
Inhalte
- Begriffsklärung – Was versteht man unter Data Science, Machine Learning, Big Data, Machine Learning, Deep Learning? Wo liegen Gemeinsamkeiten und Unterschiede?
- Machine Learning als End-to-End-Prozess: der Machine Learning Life Cycle - Behandlung verschiedener Use Cases
- Data Strategy – Wie lässt sich Machine Learning möglichst gezielt und gewinnbringend einsetzen?
- Vom Business Problem zum Data Problem – Entwicklung eigener Use Cases und Hypothesen
Dieser Kurs ist als öffentlicher Kurs (vor Ort oder online) und auch als Firmenschulung (vor Ort oder online) verfügbar.
- Machine Learning als End-to-End-Prozess: der Machine Learning Life Cycle - Behandlung verschiedener Use Cases
- Data Strategy – Wie lässt sich Machine Learning möglichst gezielt und gewinnbringend einsetzen?
- Vom Business Problem zum Data Problem – Entwicklung eigener Use Cases und Hypothesen
Dieser Kurs ist als öffentlicher Kurs (vor Ort oder online) und auch als Firmenschulung (vor Ort oder online) verfügbar.
Voraussetzungen
keine
Ihr Kontakt
Kerstin Dosin
Kontakt
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Basic 1: Data Science 4 C-Level (Basic Level)
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Basic 4: Visualization with Plotly & App creation with Dash
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Basic 2: Python Basics
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Basic 3: Introduction to Machine Learning
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Advanced 4: Computer Vision Open CV
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Intermediate 1: Machine Learning - Supervised Methods
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Advanced 1: Introduction to Neural Networks & Deep Learning
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Intermediate 2: Machine Learning - Unsupervised Methods
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Advanced 2: Deep Learning with Keras
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Advanced 3: Introduction to Reinforcement Learning
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Advanced 5: Introduction to Natural Language Processing
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Advanced 6: Advanced Topics in Natural Language Processing
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Basic 4: Visualization with Plotly & App creation with Dash
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Basic 2: Python Basics
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Basic 3: Introduction to Machine Learning
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Advanced 4: Computer Vision Open CV
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Intermediate 1: Machine Learning - Supervised Methods
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Advanced 1: Introduction to Neural Networks & Deep Learning
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Intermediate 2: Machine Learning - Unsupervised Methods
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Advanced 2: Deep Learning with Keras
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Advanced 3: Introduction to Reinforcement Learning
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Advanced 5: Introduction to Natural Language Processing
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Advanced 6: Advanced Topics in Natural Language Processing
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Microsoft Security Operations Analyst
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Angular Grundlagen
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Orientierung Agilität
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Kanban Training
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Scrum Training
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RESTful APIs
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Angular Vertiefung
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Cloud Enabling Workshop
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Führen in Zeiten von Veränderung - kompakt
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IBM Cognos Analytics – Self-Service Reporting
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IBM Cognos Analytics – Reporting Basics
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IBM Cognos Analytics – Reporting Advanced
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IBM Cognos Analytics – Administration
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IBM Planning Analytics - Grundlagen
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IBM Planning Analytics - Administration
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IBM Planning Analytics - Entwickler
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Freshdesk Admin I
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Freshdesk Admin II
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Freshworks Q&A
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Google Workspace Vertiefung (Teil 2)
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Grafana Grundlagen
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Grafana Dateninput
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Grafana Alerting
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Grafana Instrumentierung
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Microsoft Azure Administrator
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Powershell für Systemadministratoren
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OCI-Container und Docker-Grundlagen
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Domino Leap Teil 2 Workflow Applikationen
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Java Grundlagen
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