Acerca de este Curso

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Certificado para compartir

Obtén un certificado al finalizar

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. 7 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

Habilidades que obtendrás

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

Certificado para compartir

Obtén un certificado al finalizar

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. 7 horas para completar

Inglés (English)

Subtítulos: Inglés (English)

ofrecido por

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IBM

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

4 horas para completar

Data transforms and feature engineering

4 horas para completar
6 videos (Total 31 minutos), 14 lecturas, 5 cuestionarios
6 videos
Introduction to Class Imbalance1m
Class Imbalance Deep Dive9m
Introduction to Dimensionality Reduction2m
Dimension Reduction13m
Case study intro / Feature Engineering1m
14 lecturas
Data Transformation: Through the eyes of our Working Example3m
Transforms / Scikit-learn3m
Pipelines3m
Class imbalance: Through the eyes of our Working Example3m
Class Imbalance5m
Sampling techniques2m
Models that naturally handle imbalance2m
Data bias2m
Dimensionality Reduction: Through the eyes of our Working Example3m
Why is dimensionality reduction important?3m
Dimensionality reduction and Topic models5m
Topic modeling: Through the eyes of our Working Example3m
Getting Started with the topic modeling case study (hands-on)2h
Data transforms and feature engineering: Summary/Review5m
5 ejercicios de práctica
Getting Started: Check for Understanding2m
Class imbalance, data bias: Check for Understanding2m
Dimensionality Reduction: Check for Understanding3m
CASE STUDY - Topic modeling: Check for Understanding2m
Data transforms and feature engineering:End of Module Quiz10m
Semana
2

Semana 2

3 horas para completar

Pattern recognition and data mining best practices

3 horas para completar
4 videos (Total 10 minutos), 11 lecturas, 5 cuestionarios
4 videos
Introduction to Outliers2m
Outlier Detection3m
Introduction to Unsupervised learning2m
11 lecturas
ai360: Through the eyes of our Working Example3m
Introduction to ai360 (hands-on)15m
Outlier detection: Through the eyes of our Working Example3m
Outliers3m
Unsupervised learning: Through the eyes of our Working Example3m
An overview of unsupervised learning2m
Clustering3m
Clustering evaluation3m
Clustering: Through the eyes of our Working Example3m
Getting Started with the clustering case study (hands-on)2h 10m
Pattern recognition and data mining best practices: Summary/Review4m
5 ejercicios de práctica
ai360 Tutorial: Check for Understanding2m
Outlier detection: Check for Understanding2m
Unsupervised learning: Check for Understanding2m
CASE STUDY - Clustering: Check for Understanding2m
Pattern recognition and data mining best practices: End of Module Quiz12m

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.

  • Si estás suscrito, obtienes una prueba gratis de 7 días, que podrás cancelar cuando desees sin ningún tipo de penalidad. Una vez transcurrido ese tiempo, no realizamos reembolsos. No obstante, puedes cancelar tu suscripción cuando quieras. Consulta nuestra política completa de reembolsos.

  • Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.

  • This course assumes that you are already familiar with basic data science concepts including probability and statistics, linear algebra, machine learning, and the use of Python and Jupyter. It is assumed you have completed the first two courses of the specialization: AI Workflow: Business Priorities and Data Ingestion, AI Workflow: Data Analysis and Hypothesis Testing.

  • No. The certification exam is administered by Pearson VUE and must be taken at one of their testing facilities. You may visit their site at https://home.pearsonvue.com/ for more information.

  • Please visit the Pearson VUE web site at https://home.pearsonvue.com/ for the latest information on taking the AI Enterprise Workflow certification test.

  • It is highly recommended that you have at least a basic working knowledge of design thinking and Watson Studio prior to taking this course. Please visit the IBM Skills Gateway at http://ibm.com/training/badges and "Find a Badge" related to "design thinking" or "Watson Studio". From there you will be directed to courses covering these topics.

  • No. Most of the exercises may be completed with open source tools running on your personal computer. However, the exercises are designed with an enterprise focus and are intended to be run in an enterprise environment that allows for easier sharing and collaboration. The exercises in the last two modules of the course are heavily focused on deployment and testing of machine learning models and use the IBM Watson tooling found on the IBM Cloud.

  • Yes. All IBM Cloud Data and AI services are based upon open source technologies.

  • The exercises in the course may be completed by anyone using the IBM Cloud "Lite" plan, which is free for use.

  • Este Curso no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del curso para obtener crédito. Consulta con tu institución para obtener más información. Los Títulos en línea y los Certificados Mastertrack™ de Coursera brindan la oportunidad de obtener créditos universitarios.

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