Informações sobre o curso
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100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível avançado

Aprox. 9 horas para completar

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

Inglês

Legendas: Inglês

Habilidades que você terá

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível avançado

Aprox. 9 horas para completar

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

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
4 horas para concluir

Deploying Models

3 vídeos (Total 11 mín.), 17 leituras, 4 testes
3 videos
Introduction to Spark5min
Model Management and Deployment in Watson Studio2min
17 leituras
Data at scale: Through the eyes of our Working Example4min
Optimizing performance in Python5min
High performance computing4min
Apache Spark30min
Spark-submit4min
Docker containers: Through the eyes of our Working Example3min
On containers and Docker2min
Docker installation and setup2min
NVIDIA Docker4min
Getting started with Docker4min
Getting started with Flask4min
Putting it all together (hands-on tutorial)45min
More on containers3min
Watson Machine Learning: Through the eyes of our Working Example3min
Getting Started (hands-on)20min
Tutorial (hands-on)40min
Summary/Review10min
4 exercícios práticos
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
End of Module Quiz10min
Semana
2
2 horas para concluir

Deploying Models using Spark

4 vídeos (Total 12 mín.), 11 leituras, 4 testes
4 videos
Spark Recommendations1min
Recommenders6min
Introduction to Model Deployment Case Study2min
11 leituras
Spark Machine Learning: Through the eyes of our Working Example4min
Spark Pipelines4min
Spark supervised learning4min
Spark unsupervised learning2min
Model4min
Spark Recommenders: Through the eyes of our Working Example4min
Recommendation systems4min
Recommendation systems in production4min
Model Deployment: Through the eyes of our Working Example3min
Getting Started (hands-on)1h
Summary/Review
4 exercícios práticos
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
End of Module Quiz10min

Instrutores

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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

Sobre 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....

Sobre Programa de cursos integrados 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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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