Este curso forma parte de Programa especializado: Building Cloud Computing Solutions at Scale

4.1
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55 calificaciones

Noah Gift

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Ofrecido Por

Programa especializado: Building Cloud Computing Solutions at ScaleUniversidad Duke

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Welcome to the third course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to apply Data Engineering to real-world projects using the Cloud computing concepts introduced in the first two courses of this series. By the end of this course, you will be able to develop Data Engineering applications and use software development best practices to create data engineering applications. These will include continuous deployment, code quality tools, logging, instrumentation and monitoring. Finally, you will use Cloud-native technologies to tackle complex data engineering solutions. 
This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a serverless data engineering pipeline in a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP).

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Curso 3 de 4 en

Programa especializado: Building Cloud Computing Solutions at Scale

Nivel intermedio

Beginner level Linux and Python skills

Aprox. 17 horas para completar

Inglés (English)

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 3 de 4 en

Programa especializado: Building Cloud Computing Solutions at Scale

Nivel intermedio

Beginner level Linux and Python skills

Aprox. 17 horas para completar

Inglés (English)

Instructor

Calificación del instructor

4,5/5 (18 calificaciones)

Noah Gift

Executive in Residence and Founder of Pragmatic AI Labs

Interdisciplinary Data Science (MIDS)

32.317 alumnos

10 cursos

Ofrecido por

Universidad Duke

Programa - Qué aprenderás en este curso

Semana

Semana 1

4 horas para completar

Getting Started with Cloud Data Engineering

This week, you will learn about the methodologies involved in Data Engineering. You will also learn to evaluate best practices for dealing with the end of Moore’s Law, develop distributed systems that apply software engineering best practices and evaluate best practices for implementing solutions with Big Data. You will apply these practices to build a GPU programming project using Numba and the CUDA SDK.

4 horas para completar

24 videos (Total 101 minutos), 6 lecturas, 1 cuestionario

24 videos

Instructor Introduction1m

Course Introduction1m

Lab Onboarding1m

Course 3 Project Overview1m

Introduction to the End of Moore's Law2m

The Problem with Concurrency in Python2m

Exploring the End of Moore's Law3m

Using CUDA and Numba6m

What is an ASIC?2m

Taking Advantage of Colab Pro1m

Introduction to Distributed Systems1m

Logging and Instrumentation Distributed Systems1m

CAP Theorem2m

Amdahl's Law2m

Elasticity3m

Highly Available Nine Nine's1m

Debugging Python Code25m

Introduction to Big Data1m

What is Big Data?2m

The Three V's of Big Data2m

Data Lakes2m

Big Data Processing3m

Data Feedback Loop1m

Using EMR Spark to Run Parallel Jobs25m

6 lecturas

Specialization Project Roadmap: Course 3 10m

Course Structure and Discussion Etiquette10m

The End of Moore's Law10m

Challenges and Opportunities in Distributed Systems10m

Challenges in Big Data10m

Creating high-performance code10m

1 ejercicio de práctica

Week 1 Quiz30m

Semana

Semana 2

6 horas para completar

Examining Principles of Data Engineering

6 horas para completar

9 videos (Total 156 minutos), 1 lectura, 1 cuestionario

9 videos

Introduction to Data Engineering1m

What is Data Engineering?48s

Batch vs. Streaming vs. Events1m

Building CLI Tools with Click33m

Building Containerized Command-line Tools12m

Advanced Testing with Amazon CodeGuru15m

Advanced Testing with AWS CodeBuild29m

Mapping Functions to CLI: Part 131m

Mapping Functions to CLI: Part 227m

1 lectura

Extending Command-Line Data Processing Tool10m

1 ejercicio de práctica

Week 2 Quiz30m

Semana

Semana 3

4 horas para completar

Building Data Engineering Pipelines

4 horas para completar

22 videos (Total 192 minutos), 2 lecturas, 1 cuestionario

22 videos

Introduction to Serverless Data Engineering54s

What is Serverless?51s

Serverless Concepts: Service Model6m

Serverless Concepts: Functions4m

Serverless Concepts: Ecosystem7m

AWS Lambda: Overview37s

Introduction to AWS Cloud97m

AWS Lambda: Hello World12m

AWS Lambda: Deploy Testing4m

AWS Lambda: Event Handling5m

AWS Lambda: Wikipedia Example14m

Build a Serverless Data Pipeline37m

Serverless Cookbook with AWS32m

Serverless Cookbook with GCP17m

Introduction to Data Governance48s

What is Data Governance?52s

The Principle of Least Privilege1m

Cloud Security with IAM on AWS6m

AWS Shared Security Model7m

AWS IAM Service12m

AWS Cloud Security Operations5m

Encrypt at Rest and Transit3m

2 lecturas

Using Amazon EFS for AWS Lambda10m

Building Computer Vision Label Trigger for S310m

1 ejercicio de práctica

Week 3 Quiz30m

Semana

Semana 4

3 horas para completar

Applying Key Data Engineering Tasks

3 horas para completar

14 videos (Total 116 minutos), 3 lecturas, 1 cuestionario

14 videos

Introduction to Extract, Transform, Load (ETL)44s

What is ETL?51s

Using Amazon Athena with AWS Glue22m

Real-World Problems in ETL13m

Introduction to Cloud Databases6m

One Size Does Not Fit All in the Cloud?1m

Using Google BigQuery15m

Using AWS Aurora Serverless2m

Using AWS DynamoDB2m

Using AWS Redshift30m

Introduction to Cloud Storage46s

Why Cloud Storage?1m

Cloud Storage Deep Dive13m

Using Amazon S34m

3 lecturas

Cloud Databases10m

Cloud Storage Solutions10m

Create a serverless Data Engineering Pipeline10m

1 ejercicio de práctica

Week 4 Quiz30m

Reseñas

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Acerca de Programa especializado: Building Cloud Computing Solutions at Scale

With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find. This Specialization is designed to address the Cloud talent gap by providing training to anyone interested in developing the job-ready, pragmatic skills needed for careers that leverage Cloud-native technologies.

In the first course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines, using the best practices of DevOps. The second course will teach you how to build effective Microservices using technologies like Flask and Kubernetes that are continuously deployed to a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP). The third course begins to put together all of the Cloud concepts introduced in the first two courses to tackle more complex data engineering solutions. And finally, in the fourth course you will apply Machine Learning Engineering to build a Flask web application that serves out Machine Learning predictions.

Building Cloud Computing Solutions at Scale

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
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.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.

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Cloud Data Engineering

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