Training Calendar

This course introduces you to AWS services and common solutions. It provides you with fundamental knowledge to become more proficient in identifying AWS services. It helps you make informed decisions about IT solutions based on your business requirements and get started working on AWS.

AWS

In Architecting on AWS, you will learn to identify services and features to build resilient, secure and highly available IT solutions on the AWS Cloud. The modules focus on account security, networking, compute, storage, databases, monitoring, automation, containers, serverless architecture, edge services, and backup and recovery.

AWS

In this one-day course, you'll learn cloud-based deep learning solutions on the AWS platform. You'll learn how to run your models on the cloud using Amazon EC2‒based deep learning Amazon Machine Image (AMI) and Apache MXNet on AWS frameworks. In addition, you'll learn how to use Amazon SageMaker and deploy your deep learning models using AWS services like AWS Lambda and Amazon Elastic Container Service (Amazon ECS), all while designing intelligent systems on AWS.

AWS

In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures.

AWS

The Well-Architected Framework enables you to make informed decisions about your customers architectures in a cloud-native way and understand the impact of design decisions that are made. By using the Well-Architected Framework, you will understand the risks in your architecture and ways to mitigate them. This course is designed to provide a deep dive into the AWS Well-Architected Framework and its 5 pillars. This course also covers the Well-Architected Review process, and using the AWS Well-Architected Tool to complete reviews.

AWS

The name Introduction to Life Science Tools on AWS has changed. In this course you will be introduced to several AWS tools and capabilities for Healthcare and Life Sciences that enable you to process biomedical data at scale, allowing you to focus on analyzing data and reproducing results while AWS manages the underlying infrastructure. The course will focus on using Jupyter notebooks as the primary interface with the console

AWS

This course introduces participants to the big data capabilities of Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud.

GCP

The name Fundamentals of Life Science Tools on Google Cloud has changed. In this course you will be introduced to Google Cloud Life Sciences, allowing you to process biomedical data at scale and focusing on analyzing data and reproducing results while Google manages the underlying infrastructure. This course covers getting started with Google Cloud, sharing data with BigQuery and Cloud Storage, taking a container to production, running nextflow pipelines, running query analysis on publicly available datasets such as NIH SRA data, using AI Platform Notebooks, use machine learning APIs on a NCBI molecular dataset, and preparing and analyzing genomic data with Variant Transforms Tool and Cloud Dataflow.

GCP

This one-day course will provide foundational level knowledge on Azure concepts; core Azure services; core solutions and management tools; general security and network security; governance, privacy, and compliance features; Azure cost management and service level agreements.

Azure

In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about modern data warehousing, real-time analytics, and data visualization.

Azure

This course provides foundational level knowledge on security, compliance, and identity concepts and related cloud-based Microsoft solutions.

Azure