Finally after a few month spent studying I decided to jump the fence and register for the exam. Here is how I prepared and what I found the most useful. First I studied the cursus offered on Coursera, the 5 modules. As I never touched a cloud before and had Read more…
Selecting Appropriate Storage Technologies Know the four stages of the data lifecycle: ingest, storage, process and analyze, and explore and visualize. Ingestion is the process of bringing application data, streaming data, and batch data into the cloud. The storage stage focuses on persisting data to an appropriate storage system. Processing Read more…
Stream analytics has many applications Data Integration Access data warehousesin real-time Take the load off scource databases with change data capture (CDC) Utilize microservices more effectively Online decisions Real-time recommandations Fraud detection Gaming events Finance back office apps Volume (Terabites of data) + Velocity (Real time) + Variety (Unstructured data) Read more…
Module 01 : What is Machine Learning (ML)? Machine learning is a way to use standard algorithms to derive predictive insights from data and make repeated decisions. Business intelligence is understand the past Machine learning use past data to predict the future Stage 1 : Train an Model model with Read more…
Notes for the Google Cloud Platform Big Data and Machine Learning Fundamentals course. https://www.coursera.org/learn/gcp-big-data-ml-fundamentals/home/welcome https://console.cloud.google.com WEEK 1 1. Google Cloud Architecture -2. Abstract away scaling, infrastructure -1. Process, store, and deliver pipelines, ML models, etc. -0. Auth 2. Creating a VM on Compute Engine 2.1 Setting up the VM https://cloud.google.com Read more…