GCP100RESEARCH

Google Cloud Fundamentals for Researchers

In this course you will learn how to use various tools in Google Cloud to ingest, manage and leverage your data to derive insights in your research. You will be introduced to tools used on Google Cloud by researchers, then you will learn how to ingest your unstructured and structured data into Cloud Storage and BigQuery respectively. Next, you will learn how to curate your data and understand costs in Google Cloud. Finally you will learn how to leverage notebook environments and other Google Cloud tools for descriptive and predictive analysis.

✓ Formation officielle Google CloudNiveau Fundamentals⏱️ 1 jour (7h)

Ce que vous allez apprendre

Understand products available in Google Cloud for research
Load unstructured and structured data into Google Cloud
Manage access and sharing your data on Google Cloud
Understand costs on Google Cloud
Leverage Jupyter Notebook environments in Vertex AI Workbench
Utilize machine learning solutions on Google Cloud

Prérequis

Basic knowledge of data types and SQL
Basic programming knowledge
Machine learning models such as supervised versus unsupervised models

Public cible

Customers, Researchers

Programme de la Formation

6 modules pour maîtriser les fondamentaux

Objectifs

Explore research use cases in Google Cloud through interactive demos.

Sujets abordés

→Demo: Provision Compute Engine virtual machines
→Demo: Query a billion rows of data in seconds using BigQuery
→Demo: Train a custom vision model using AutoML Vision

Quality Process

SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach

Teaching Methods Used

Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
Guided Labs — Guided practical exercises on software, hardware, or technical environments.
Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).

Evaluation and Monitoring System

The achievement of training objectives is evaluated at multiple levels to ensure quality:

Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.