Acerca de este Curso
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Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel avanzado

Aprox. 9 horas para completar

Sugerido: This course requires 7.5 to 9 hours of study....

Inglés (English)

Subtítulos: Inglés (English)
User
Los estudiantes que toman este Course son
  • Data Scientists
  • Software Engineers

Habilidades que obtendrás

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
User
Los estudiantes que toman este Course son
  • Data Scientists
  • Software Engineers

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel avanzado

Aprox. 9 horas para completar

Sugerido: This course requires 7.5 to 9 hours of study....

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
4 horas para completar

Deploying Models

3 videos (Total 11 minutos), 17 lecturas, 4 cuestionarios
3 videos
Introduction to Spark5m
Model Management and Deployment in Watson Studio2m
17 lecturas
Data at scale: Through the eyes of our Working Example4m
Optimizing performance in Python5m
High performance computing4m
Apache Spark30m
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 ejercicios de práctica
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m
Semana
2
2 horas para completar

Deploying Models using Spark

4 videos (Total 12 minutos), 11 lecturas, 4 cuestionarios
4 videos
Spark Recommendations1m
Recommenders6m
Introduction to Model Deployment Case Study2m
11 lecturas
Spark Machine Learning: Through the eyes of our Working Example4m
Spark Pipelines4m
Spark supervised learning4m
Spark unsupervised learning2m
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 ejercicios de práctica
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m

Instructores

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Mark J Grover

Digital Content Delivery Lead
IBM Data & AI Learning
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Ray Lopez, Ph.D.

Data Science Curriculum Leader
IBM Data & Artificial Intelligence

Acerca de IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

Acerca de Programa especializado 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

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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