Über diesen Kurs

5,116 kürzliche Aufrufe
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Ca. 6 Stunden zum Abschließen
Englisch
Untertitel: Englisch

Kompetenzen, die Sie erwerben

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Fortgeschritten“
Ca. 6 Stunden zum Abschließen
Englisch
Untertitel: Englisch

von

IBM-Logo

IBM

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1

Woche 1

4 Stunden zum Abschließen

Deploying Models

4 Stunden zum Abschließen
3 Videos (Gesamt 11 min), 17 Lektüren, 4 Quiz
3 Videos
Introduction to Spark5m
Model Management and Deployment in Watson Studio2m
17 Lektüren
Data at scale: Through the eyes of our Working Example4m
Optimizing performance in Python5m
High performance computing4m
Apache Spark (hands-on)30m
Spark-submit4m
Docker containers: Through the eyes of our Working Example3m
On containers and Docker2m
Docker installation and setup2m
NVIDIA Docker4m
Getting started with Docker4m
Getting started with Flask4m
Putting it all together (hands-on tutorial)45m
More on containers3m
Watson Machine Learning: Through the eyes of our Working Example3m
Getting Started (hands-on)20m
Tutorial (hands-on)40m
Summary/Review10m
4 praktische Übungen
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m
Woche
2

Woche 2

3 Stunden zum Abschließen

Deploying Models using Spark

3 Stunden zum Abschließen
4 Videos (Gesamt 12 min), 11 Lektüren, 4 Quiz
4 Videos
Spark Recommendations1m
Recommenders6m
Introduction to Model Deployment Case Study2m
11 Lektüren
Spark Machine Learning: Through the eyes of our Working Example4m
Spark Pipelines4m
Spark supervised learning4m
Spark unsupervised learning (hands-on)45m
Model4m
Spark Recommenders: Through the eyes of our Working Example4m
Recommendation systems4m
Recommendation systems in production4m
Model Deployment: Through the eyes of our Working Example3m
Getting Started (hands-on)1h
Summary/Review
4 praktische Übungen
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m

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Über den Spezialisierung IBM AI Enterprise Workflow

This six course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. The learning aims to elevate the skills of practicing data scientists by explicitly connecting business priorities to technical implementations, connecting machine learning to specialized AI use cases such as visual recognition and NLP, and connecting Python to IBM Cloud technologies. The videos, readings, and case studies in these courses are designed to guide you through your work as a data scientist at a hypothetical streaming media company. Throughout this specialization, the focus will be on the practice of data science in large, modern enterprises. You will be guided through the use of enterprise-class tools on the IBM Cloud, tools that you will use to create, deploy and test machine learning models. Your favorite open source tools, such a Jupyter notebooks and Python libraries will be used extensively for data preparation and building models. Models will be deployed on the IBM Cloud using IBM Watson tooling that works seamlessly with open source tools. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow....
IBM AI Enterprise Workflow

Häufig gestellte Fragen

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