Trần Hoàng Kim Long
Menjadi anggota sejak 2019
Gold League
9180 poin
Mengimplementasikan Cloud Load Balancing untuk Compute Engine
Earned Mei 21, 2023 EDT
Machine Learning in the Enterprise
Earned Okt 10, 2022 EDT
Creating New BigQuery Datasets and Visualizing Insights
Earned Okt 10, 2022 EDT
DEPRECATED Applied Data: Blockchain
Earned Okt 9, 2022 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned Okt 9, 2022 EDT
Build a Certification Study Guide: PDE Exam Prep
Earned Okt 9, 2022 EDT
Menyiapkan Data untuk Dasbor dan Laporan Looker
Earned Okt 8, 2022 EDT
Mengotomatiskan Pengambilan Data Berskala Besar dengan Document AI
Earned Okt 5, 2022 EDT
Menyiapkan Data untuk ML API di Google Cloud
Earned Okt 4, 2022 EDT
Memigrasikan Data MySQL ke Cloud SQL Menggunakan Database Migration Service
Earned Sep 30, 2022 EDT
Membangun dan Men-Deploy Solusi Machine Learning di Vertex AI
Earned Sep 30, 2022 EDT
Membuat Model ML dengan BigQuery ML
Earned Sep 25, 2022 EDT
Rekayasa Data untuk Pembuatan Model Prediktif dengan BigQuery ML
Earned Sep 24, 2022 EDT
[DEPRECATED] Data Engineering
Earned Sep 23, 2022 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine
Earned Sep 17, 2022 EDT
Selesaikan badge keahlian pengantar Mengimplementasikan Cloud Load Balancing untuk Compute Engine untuk menunjukkan keterampilan dalam hal berikut: membuat dan men-deploy virtual machine di Compute Engine serta mengonfigurasi load balancer aplikasi dan jaringan.
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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing.
The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources.
Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you.
After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.
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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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Selesaikan badge keahlian pengantar Menyiapkan Data untuk Dasbor dan Laporan Looker untuk menunjukkan keterampilan dalam hal berikut: memfilter, mengurutkan, dan melakukan pivot pada data; menggabungkan hasil dari sejumlah Eksplorasi Looker; serta menggunakan fungsi dan operator untuk membangun dasbor dan laporan Looker untuk analisis dan visualisasi data.
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Dapatkan badge keahlian pengantar dengan menyelesaikan kursus Mengotomatiskan Pengambilan Data Berskala Besar dengan Document AI. Dalam kursus ini, Anda akan mempelajari cara mengekstrak, memproses, dan mengambil data menggunakan Document AI.
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Selesaikan badge keahlian pengantar Menyiapkan Data untuk ML API di Google Cloud untuk menunjukkan keterampilan Anda dalam hal berikut: menghapus data dengan Dataprep by Trifacta, menjalankan pipeline data di Dataflow, membuat cluster dan menjalankan tugas Apache Spark di Managed Service for Apache Spark, dan memanggil beberapa ML API, termasuk Cloud Natural Language API, Google Cloud Speech-to-Text API, dan Video Intelligence API.
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Selesaikan kursus badge keahlian pengantar Memigrasikan Data MySQL ke Cloud SQL Menggunakan Database Migration Service untuk menunjukkan keterampilan dalam hal berikut: memigrasikan data MySQL ke Cloud SQL menggunakan berbagai jenis tugas dan opsi konektivitas yang tersedia dalam Database Migration Service dan memigrasikan data pengguna MySQL saat menjalankan tugas Database Migration Service.
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Dapatkan badge keahlian tingkat menengah dengan menyelesaikan kursus Membangun dan Men-Deploy Solusi Machine Learning di Vertex AI, tempat Anda akan belajar cara menggunakan platform Vertex AI Google Cloud, AutoML, dan layanan pelatihan kustom untuk melatih, mengevaluasi, menyesuaikan, menjelaskan, serta men-deploy model machine learning. Kursus badge keahlian ini diperuntukkan bagi Data Scientist dan Engineer Machine Learning profesional. Badge keahlian adalah badge digital eksklusif yang diberikan oleh Google Cloud sebagai pengakuan atas kemahiran Anda dalam menggunakan produk dan layanan Google Cloud serta menguji kemampuan Anda dalam menerapkan pengetahuan di lingkungan praktis yang interaktif. Selesaikan Badge keahlian ini, dan challenge lab penilaian akhir, untuk menerima badge digital yang dapat Anda bagikan ke jaringan Anda.
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Selesaikan badge keahlian tingkat menengah Membuat Model ML dengan BigQuery ML untuk menunjukkan keterampilan dalam hal berikut: membuat dan mengevaluasi model machine learning dengan BigQuery ML untuk membuat prediksi data.
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Selesaikan badge keahlian tingkat menengah Rekayasa Data untuk Pembuatan Model Prediktif dengan BigQuery ML untuk menunjukkan keterampilan Anda dalam hal berikut: membangun pipeline transformasi data ke BigQuery dengan Dataprep by Trifacta; menggunakan Cloud Storage, Dataflow, dan BigQuery untuk membangun alur kerja ekstrak, transformasi, dan pemuatan (ETL); serta membangun model machine learning menggunakan BigQuery ML.
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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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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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