Participants in this training typically have a background in software or data engineering or IT architect. In order to get most value out of the practical part of the training, you should understand the fundamentals of file storage, databases and virtual machines and have some command line experience (ssh connections, keys, etc). Basic knowledge about machine learning workflow comes in handy.
During the training you will learn:
After the training you receive a Certificate of Completion.
This training consists of 3 Classes. Join the Cloud Platform Training on one of these dates in our office or contact us for a tailored training:
May 15, 2020
July 03, 2020 | October 09, 2020
August 07, 2020 | November 13, 2020
This training focuses on the Amazon corner of the cloud universe and aims to give an overview of their most important services and their relevance for Data Science and Machine Learning.
We start the theoretical part of this training by going into the history and background of Cloud Infrastructure in general, and Amazon Web Services in specific. Then, we discuss their solutions for access management, storage, compute, monitoring, etc before moving to Machine Learning services such as Sagemaker (ML), Rekognition (Image and Vision) and Comprehend (NLP) and concluding by mentioning some interesting others.
Having learned about this ecosystem of services we then gain hands-on experience during the lab session, in which we tie multiple components together and eventually train a prediction model for beer preferences based on a dataset of customer reviews.
The training includes theory, demos, and hands-on exercises. After this training you will have gained knowledge about:
This training focuses on the Google corner of the cloud universe and aims to give an overview of their most important services and their relevance for Data Science and Machine Learning.
We start the theoretical part of this training by going into the history and background of Cloud Infrastructure in general, and Google Cloud Platform in specific. During this lesson on Google Cloud Platform you will learn about several topics that touch upon what a Machine Learning Engineer needs. We will do some data processing with Apache Beam, train and deploy a model via Kubeflow and publish the results on Pub/Sub.
Having learned about this ecosystem of services we then gain hands-on experience during the lab session, in which we tie multiple components together and eventually train a prediction model for beer preferences based on a dataset of customer reviews.
The training includes theory, demos, and hands-on exercises. After this training you will have gained knowledge about:
Microsoft Azure is one of the most popular cloud computing services today, offering dozens of capabilities ranging from storage and databases to scalable data processing. This training provides an overview of the Azure landscape with a focus on IaaS, PaaS and Serverless services like VM’s, Networking (IaaS), storage, databases, serverless functions, and more. During the training, participants set up their own Virtual Machine and build a small data pipeline which automatically rescales images put in storage.
The training includes theory and practical exercises. After this training you will have gained knowledge about:
Are you interested in the Cloud Platform Fundamentals training or do you have questions? Fill out the form and we will contact you personally.