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Quête

Data Engineering

Cette quête Qwiklabs de niveau avancé est unique en son genre. Elle se compose d'ateliers pratiques qui permettent aux professionnels de l'informatique de se familiariser avec les sujets et les services au programme de la certification \"Google Cloud Certified – Professional Data Engineer\". De BigQuery à Dataproc en passant par Tensorflow, cette quête mettra à l'épreuve vos connaissances sur l'ingénierie des données GCP. Attention : même si les ateliers constituent une bonne base pour développer vos compétences, ils ne suffisent pas à réussir la quête. L'examen final étant assez difficile, nous vous recommandons d'avoir suivi une formation préalable ou de posséder de l'expérience en matière d'ingénierie des données cloud et de compléter votre apprentissage à l'aide d'autres ressources.

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Quête

Scientific Data Processing

Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.

Quête

Baseline: Data, ML, AI

Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, GCP provides user-friendly services in these areas and Qwiklabs has you covered with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and Cloud ML Engine. Want extra help? 1-minute videos walk you through key concepts for each lab.

Quête

Data Science on the Google Cloud Platform

This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud Platform tools and services.

Quête

Data Science on Google Cloud Platform: Machine Learning

This is the second of two Quests of hands-on labs derived from the exercises from the book Data Science on Google Cloud Platform by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud Platform tools and services.

Quête

Developing Data and Machine Learning Apps with C#

C# has powered Windows .NET application development for nearly two decades and Google Cloud is committed to supporting developers getting their .NET workloads up and running on the GCP platform. In this quest, you will learn how to run C# apps in GCP, and specifically how to take your apps to the next level by interfacing them with the big data and machine learning APIs that are accessible now from C#. By enrolling in Developing Data and Machine Learning Apps with C# you will see firsthand how seamlessly GCP integrates with .NET workloads and what the possibilities are for leveraging big data and ML services in your own C# projects.

Quête

Google Cloud Solutions II: Data and Machine Learning

In this advanced-level quest, you will learn how to harness serious GCP computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why GCP is the go-to platform for running big data and machine learning jobs.

Quête

Security & Identity Fundamentals

Security is an uncompromising feature of Google Cloud Platform services, and GCP has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with GCP’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.

Quête

Cloud SQL

Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this fundamental-level quest, you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and highly available databases that run on GKE containers, Cloud SQL will give you the knowledge and experience needed so you can start integrating this service right away.

Quête

Baseline: Deploy & Develop

In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.

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