Sara El-Ateif
Menjadi anggota sejak 2018
Bronze League
6494 poin
Agen dan Kasus Penggunaan Enterprise
Earned Feb 19, 2026 EST
Dasar-Dasar Agen
Earned Feb 19, 2026 EST
Pengantar Agen AI
Earned Feb 19, 2026 EST
Pengantar Responsible AI
Earned Mei 18, 2024 EDT
Pengantar Model Bahasa Besar
Earned Mei 18, 2024 EDT
Pengantar AI Generatif
Earned Mei 18, 2024 EDT
Penjelajah AI Generatif - Agent Platform
Earned Mei 10, 2024 EDT
Generative AI Explorer
Earned Mei 10, 2024 EDT
How Google Does Machine Learning
Earned Mei 24, 2023 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned Mei 23, 2023 EDT
Women's Month Speedrun
Earned Mar 13, 2020 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned Mar 13, 2020 EDT
Scientific Data Processing
Earned Mar 12, 2020 EDT
Cloud Hero Speedrun: IoT & Big Data
Earned Agu 23, 2019 EDT
[DEPRECATED] Data Engineering
Earned Mei 18, 2018 EDT
Dasar pengukuran: Data, ML, AI
Earned Mei 13, 2018 EDT
Dasar-Dasar Google Cloud
Earned Mei 4, 2018 EDT
Mempelajari cara agen AI mendorong dampak bisnis. Selanjutnya, Anda akan mempelajari cara Gemini Enterprise mengefektifkan Anda dalam membangun dan mengorkestrasi agen yang tepat, mulai dari solusi tanpa coding hingga solusi dengan coding tingkat tinggi.
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Kursus ini memperkenalkan dasar-dasar agen AI serta mengeksplorasi bagaimana agen memberikan nilai tambah di dunia nyata. Kursus ini memberikan fondasi bagi developer, arsitek, dan pengambil keputusan teknis yang ingin memahami sistem AI melalui sudut pandang perilaku otonom yang berorientasi pada sasaran.
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Mendapatkan gambaran konseptual tentang Agen AI. Anda akan mempelajari arsitektur teknis, yakni model, alat, dan orkestrasi, yang memungkinkan agen untuk belajar, merencanakan, dan mencapai sasaran atas nama Anda.
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Ini adalah kursus pengantar pembelajaran mikro yang dimaksudkan untuk menjelaskan responsible AI, alasan pentingnya responsible AI, dan cara Google mengimplementasikan responsible AI dalam produknya. Kursus ini juga memperkenalkan 7 prinsip AI Google.
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Ini adalah kursus pengantar pembelajaran mikro yang membahas definisi model bahasa besar (LLM), kasus penggunaannya, dan cara menggunakan prompt tuning untuk meningkatkan performa LLM. Kursus ini juga membahas beberapa alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.
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Ini adalah kursus pengantar pembelajaran mikro yang bertujuan untuk mendefinisikan AI Generatif, cara penggunaannya, dan perbedaannya dari metode machine learning konvensional. Kursus ini juga membahas beberapa Alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.
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Kursus Penjelajah AI Generatif - Agent Platform adalah sekumpulan lab yang membahas cara menggunakan AI Generatif di Google Cloud. Melalui lab ini, Anda akan mempelajari cara menggunakan model Gemini di Agent Platform. Anda juga akan mempelajari apa itu desain perintah, praktik terbaik desain perintah, serta cara menggunakan desain perintah untuk pencarian ide, klasifikasi teks, ekstraksi teks, peringkasan teks, dan lainnya. Anda juga akan mempelajari cara menyesuaikan model dasar dengan melatihnya melalui pelatihan kustom di Agent Platform dan men-deploy-nya ke endpoint di Agent Platform.
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Welcome Gamers! Create and test a prompt, create a conversation, and explore the prompt gallery, all while having fun! Explore Generative AI Studio in Vertex AI. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models.
The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
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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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Welcome, gamers! Here is a game for celebrating Women's Month! Hope you have with Big Data and Machine Learning! You will compete to see who can finish the game with the most points. Speed is important, and so is accuracy! Start taking the game labs to score points. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with the lab to get the maximum points. You can take each lab up to 5 times.
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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.
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Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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In today's game, you will explore the overlap between IoT and big data, while continuing to make progress on the Data Engineering quest. Start by familiarizing yourself with key IoT concepts then challenge yourself to build an IoT Analytics Pipeline. Put GCP to the test and explore key solutions to common use cases and gain hands-on experience with IoT data at scale, ETL processing and more, plus score points and compete with other players in today's game.
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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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Big data, machine learning, dan kecerdasan buatan menjadi topik komputasi yang populer saat ini, tetapi bidang tersebut sangat terspesialisasi dan materi pengantarnya sulit diperoleh. Untungnya, Google Cloud menyediakan layanan yang mudah digunakan dalam bidang tersebut, dan melalui kursus tingkat pengantar ini, Anda dapat mengambil langkah pertama dengan alat seperti BigQuery, Cloud Speech API, dan Video Intelligence.
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Dalam kursus tingkat pemula ini, Anda akan mendapatkan praktik langsung dengan alat dan layanan dasar Google Cloud. Video opsional disediakan untuk memberikan konteks dan ulasan lebih lanjut mengenai konsep-konsep yang dibahas dalam lab ini. Dasar-Dasar Google Cloud adalah kursus pertama yang direkomendasikan bagi peserta kursus Google Cloud— Anda bisa mengikutinya dengan pengetahuan yang minim atau tanpa pengetahuan sama sekali tentang cloud, dan mendapatkan pengalaman praktis yang dapat diterapkan pada project Google Cloud pertama Anda setelah menyelesaikan kursus ini. Mulai dari menulis perintah Cloud Shell dan men-deploy virtual machine pertama Anda, hingga menjalankan aplikasi di Kubernetes Engine atau dengan load balancing, Dasar-Dasar Google Cloud merupakan pengantar utama untuk fitur dasar platform ini.
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