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Mettez en pratique vos compétences dans la console Google Cloud

Mohamed Amine Bennaji

Date d'abonnement : 2023

Ligue d'Or

7970 points
Introduction to Large Language Models Earned avr. 24, 2025 EDT
Introduction to Generative AI Earned jan. 8, 2024 EST
Modernizing Data Lakes and Data Warehouses with Google Cloud Earned déc. 15, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals Earned nov. 30, 2023 EST
Preparing for your Professional Data Engineer Journey Earned nov. 10, 2023 EST

This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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