- Duration: Flexible
Course details
Hi I'm Sam, a big data engineer, full stack web developer and machine learning/AI Enthusiast teaching you GCP in the most efficient and down to earth approach. I will teach you the core components of GCP required to pass the data engineers exam using a real world applications approach. All the practicals in this course show you techniques used by big data engineers on the GCP.
Course is streamlined to aim to get you to pass the GCP Data Engineers Certification. Therefore, it is the most time efficient course to learn about GCP if you want to have a good understanding of GCP's products and have the intention of becoming a certified data engineer in the future. The course is streamlined to under 5 hours! Learn all about GCP over a weekend or in a day !
Infrastructure solutions will be presented for various use cases as you learn the most when solving real problems! Theory and Practicals will be placed to aim to pass the Data Engineers Exam with the shortest amount of time. In the exam most questions will be targeted on the why and not the how. For example you will be very hard pressed to find a question that asks you to choose the correct code snippet out of the 3 code snippets etc.
Course is split up into sections as below:
Introduction - Explore questions, Why Cloud, Why GCP, main differentiators of GCP/main selling points, setup your free GCP account
Compute Engine - Overview of compute engine and pricing innovations, zones & regions, various machine types and practical to spin up VMs and access them via SSH, Mac and Windows supported
Storage Solutions - Overview of GCP's data storage solutions including Cloud Storage, Cloud Datastore, Cloud Spanner, Cloud SQL, BigQuery & BigTable. We will compare these storage solutions with each other and explain use cases where one storage solution will excel over another.
IAM & Billing - Different member types, roles and permissions, resource hierarchy and billing process
BigQuery - BigQuery Pricing structure, tips for reducing processing cost, Partitioned & Wildcard tables, Authorised views, Practicals in BigQuery using standard SQL
Cloud Datalab - How to use Cloud Datalab in a practical with a live feed from BigQuery to explore the dataset.
Cloud Pub/Sub - Pub/Sub concepts and its components especially decoupling and the uses of Pub/Sub
Hadoop & Dataproc - Overview of hadoop and major components which will be tested in the exam
Cloud Dataflow - What is dataflow, the dataflow model, how and why its used with relation to other GCP Products
Stackdriver - Stackdriver functions such as debugging, error reporting, monitoring, alerting, tracing and logging.
Tensorflow & AI - Brief overview of machine learning and neural networks, play with neural networks with a playground and understand GCP's AI products and APIs
Case Study - Finally, Put your new learnt GCP knowledge to use in a real world application business case. Similar case studies will be present in the exams.
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