Petr Klimeš
Menjadi anggota sejak 2026
Silver League
11202 poin
Security Command Center: Vulnerabilities and Misconfigurations
Earned Nov 3, 2026 EST
Google Threat Intelligence
Earned Nov 3, 2026 EST
Machine Learning Operations (MLOps) untuk AI Generatif
Earned Nov 3, 2026 EST
Introduction Google Security Operations (SOAR)
Earned Nov 3, 2026 EST
Introduction to Google Security Operations (SIEM)
Earned Nov 3, 2026 EST
Menambahkan Kemampuan Agen dengan Alat
Earned Nov 3, 2026 EST
Machine Learning Operations (MLOps): Getting Started
Earned Nov 3, 2026 EST
Machine Learning Operations (MLOps) dengan Vertex AI: Evaluasi Model
Earned Nov 3, 2026 EST
Google Security Operations - Deep Dive
Earned Nov 3, 2026 EST
Google DeepMind : 08 Capstone: Develop Your Model for Real-World Impact
Earned Nov 3, 2026 EST
Orchestrate Workflows with the Data Agent Kit
Earned Nov 3, 2026 EST
Customer Experience Agent Studio: Design and Test Solutions
Earned Nov 3, 2026 EST
Google Cloud Agent Governance and Security
Earned Nov 3, 2026 EST
Innovating with Data and Google Cloud
Earned Nov 3, 2026 EST
Google DeepMind: 01 Build Your Own Small Language Model
Earned Nov 3, 2026 EST
Google DeepMind: 02 Represent Your Language Data
Earned Nov 3, 2026 EST
Google DeepMind: 03 Design And Train Neural Networks
Earned Nov 3, 2026 EST
Google DeepMind: 04 Discover The Transformer Architecture
Earned Nov 3, 2026 EST
Google DeepMind: 07 Accelerate Your Model
Earned Nov 3, 2026 EST
Google DeepMind: 05 Fine-Tune Your Model
Earned Nov 3, 2026 EST
Mengelola Memori dan Status Agen
Earned Nov 3, 2026 EST
Add Agent Guardrails with Callbacks
Earned Nov 3, 2026 EST
Build a Certification Study Guide: PCA Exam Prep
Earned Nov 3, 2026 EST
Men-deploy Agen Pertama Anda
Earned Nov 3, 2026 EST
Coordinate Multiple Agents
Earned Nov 3, 2026 EST
Agent Assist dan Kapabilitas AI Generatifnya
Earned Nov 3, 2026 EST
Membuat Agen dengan Playbook Generatif
Earned Nov 3, 2026 EST
AI Boost Bites: Membuat Game Arcade Retro Anda Sendiri
Earned Okt 16, 2026 EDT
AI Boost Bites: Menjadi "DJ Suasana"
Earned Okt 16, 2026 EDT
AI Boost Bites: Membuat Laporan Evaluasi Performa Kampus Terbaik Anda
Earned Okt 16, 2026 EDT
AI Boost Bites: Visual Kampanye Sekali Klik
Earned Okt 16, 2026 EDT
AI Boost Bites: Dari Sketsa Sederhana Menjadi Aplikasi Fungsional
Earned Okt 16, 2026 EDT
AI Boost Bites: Notes to Sheets with Gemini
Earned Okt 16, 2026 EDT
AI Boost Bites: Tips Kalender Gemini di Gmail
Earned Okt 16, 2026 EDT
AI Boost Bites: Build Slides Fast with Gemini
Earned Okt 16, 2026 EDT
AI Boost Bites: Talk to Your Data in Sheets
Earned Okt 16, 2026 EDT
AI Boost Bites: AI Magic in a Sheets Cell
Earned Okt 16, 2026 EDT
AI Boost Bites: Spreadsheet & Skrip Tanpa Coding
Earned Okt 16, 2026 EDT
AI Boost Bites: Mengotomatiskan tugas dengan Gemini dan Apps Script
Earned Okt 16, 2026 EDT
AI Boost Bites: Advanced Analysis in Sheets
Earned Okt 16, 2026 EDT
Membuat Aplikasi Gemini Enterprise Pertama Anda
Earned Okt 16, 2026 EDT
Agen dan Kasus Penggunaan Enterprise
Earned Okt 16, 2026 EDT
Dasar-Dasar Agen
Earned Okt 16, 2026 EDT
Pengantar AI Generatif
Earned Okt 15, 2026 EDT
Learn how to use Security Command Center (SCC) to triage vulnerabilities and misconfigurations identified by platform security detectors.
Pelajari lebih lanjut
Google Threat Intelligence memberikan visibilitas terhadap ancaman yang tak tertandingi dengan menghadirkan kecerdasan ancaman yang mendetail secara tepat waktu kepada tim keamanan di seluruh dunia. Kursus ini membahas berbagai kemampuan Google Threat Intelligence dan cara penggunaan umum produk ini oleh organisasi untuk memitigasi ancaman secara proaktif.
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Kursus ini dikhususkan untuk membekali Anda dengan pengetahuan dan alat yang diperlukan guna mengungkap tantangan unik yang dihadapi oleh tim MLOps saat men-deploy dan mengelola model AI Generatif, serta mengeksplorasi cara Vertex AI memberdayakan tim AI dalam menyederhanakan proses MLOps dan mencapai keberhasilan dalam project AI Generatif.
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This course introduces the SOAR component of Google SecOps, guiding learners through setup, response automation, and reporting. With demos, hands-on examples, and quizzes, participants will learn how to simplify investigations and make day-to-day security operations more efficient. The course is designed around short videos, averaging about five minutes each, divided into granular topics to support different learning styles and fit into the time learners have available.
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This course provides a comprehensive, end-to-end exploration of Google SecOps SIEM, guiding learners from foundational concepts to advanced investigation and detection engineering. Participants will gain hands-on experience with data ingestion, normalization, RBAC configuration, searching, and dashboarding using both legacy and native capabilities. Through structured modules, demos, and curated examples, the course emphasizes real-world investigation workflows, UDM-based analytics, and YARA-L rule development. By the end of the course, learners will be equipped to operationalize SIEM effectively within their environment and build scalable processes for detection, investigation, and reporting.
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Anda telah membangun agen dengan konfigurasi lanjutan. Sekarang, berikan agen itu kemampuan dunia nyata. Lengkapi agen dengan alat yang memungkinkannya menelusuri web, mengeksekusi kode, membuat kueri database, dan menjalankan tindakan kustom.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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Kursus ini membekali para praktisi machine learning dengan alat, teknik, dan praktik terbaik penting untuk mengevaluasi model AI generatif dan prediktif. Evaluasi model adalah disiplin ilmu yang sangat penting untuk memastikan sistem ML memberikan hasil yang andal, akurat, dan berperforma tinggi dalam produksi.
Peserta akan mendapatkan pemahaman yang mendalam mengenai berbagai metrik evaluasi, metodologi, dan penerapannya yang sesuai di berbagai jenis model dan tugas. Kursus ini akan berfokus pada tantangan unik yang dibuat oleh model AI generatif dan memberikan strategi untuk mengatasinya secara efektif. Dengan memanfaatkan platform Vertex AI di Google Cloud, para peserta akan belajar cara mengimplementasikan proses evaluasi yang kuat untuk melakukan pemilihan, pengoptimalan, dan pemantauan berkelanjutan pada model.
Pelajari lebih lanjut
Take these next steps to learn more about the Google Security Operations Platform. Build on fundamental knowledge to go deeper on customization and tuning.
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In this Google DeepMind course, you will complete a capstone project that brings together the technical knowledge, ethical awareness, and creative problem-solving skills that you have developed throughout the Google DeepMind: AI Research Foundations curriculum. You will apply what you have learned to a problem of your choosing. You will first plan your project to ensure that you are clear on your project aims and intended impact. You will then collect and prepare data for your model. Finally, you will implement a full fine-tuning workflow using Gemma 3 with low-rank adaptation (LoRA) and evaluate its performance. You will receive guidance, but the emphasis will be on adaptation and experimentation - skills that are essential for applied AI research.
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This course brings AI-driven, natural-language data engineering into the IDE and CLI workflows you already use. Built on the Agent Development Kit (ADK), the Data Agent Kit connects to a wide array of Google Cloud services, including BigQuery, Spanner, BigLake, Dataproc, and Managed Airflow. By using it, you can collapse days of pipeline scaffolding, data build tool (dbt) authoring, and orchestration wiring into prompt-driven sessions.
As an intermediate-to-advanced practitioner, you will learn to build a data agent with the Agent Development Kit (ADK). You'll wire up the Model Context Protocol (MCP) layer, and use your agent to explore catalogs, transform data, train models, and orchestrate scheduled pipelines on Google Cloud.
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In this advanced course, you will design, evaluate, deploy, and monitor production-ready AI agents using Customer Experience Agent Studio (CX Agent Studio).
You will apply deterministic design principles, test agents with simulations, and build low-latency voice experiences with Native Audio. You will accelerate development using the CX Agent Studio Model Context Protocol (MCP) server and enterprise connectors. Then, evaluate agent performance with golden test cases and the AI-assisted quality hill climbing process. Finally, deploy your agents across web and telephony channels, configure human escalation, and monitor live conversations using Quality AI in CX Insights.
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As enterprise teams transition to autonomous AI agents, security evolves toward proactive, identity-centric protection. In this course, you will implement a zero-trust security architecture for Cymbal Banking's underwriting platform using the Gemini Enterprise Agent Platform. By deploying a regional Egress Agent Gateway, configuring Model Armor and Semantic Governance (SGP) safety templates, assigning cryptographic SPIFFE identities to agent runtimes, and declaring a VPC-SC perimeter in Terraform, you will protect database boundaries and manage tools with production-grade governance.
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Cloud technology on its own only provides a fraction of the true value to a business; When combined with data–lots and lots of it–it has the power to truly unlock value and create new experiences for customers.
In this course, you'll learn what data is, historical ways companies have used it to make decisions, and why it is so critical for machine learning. This course also introduces learners to technical concepts such as structured and unstructured data. database, data warehouse, and data lakes. It then covers the most common and fastest growing Google Cloud products around data.
Pelajari lebih lanjut
In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
Pelajari lebih lanjut
In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
Pelajari lebih lanjut
In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
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In this Google DeepMind course you will discover the mechanisms of the transformer architecture. You will investigate how transformer language models process prompts to make context-sensitive next-token predictions. Through practical activities you will explore the attention mechanism, visualize attention weights, and encounter advanced concepts like masked attention and multi-head attention. You will also learn other techniques that are necessary to build neural networks that are well-suited to be used as language models. Finally, through activities on values, stakeholder mapping and community engagement, you will practice concrete tools for ensuring AI projects are developed with communities, not just for them.
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Train more powerful models with a single GPU. In this course, you will learn how hardware can speed up model training and the key considerations when training models on a GPU. First, you will learn how to estimate the number of computations and the amount of computer memory required to train large neural networks. You will then discover techniques for reducing the computing and memory requirements when training a model. Techniques which you will apply for fine-tuning a Gemma model with 4 billion parameters. Finally, you will consider the potential environmental impacts of machine learning, with a focus on where questions of energy, water, and e-waste intersect with justice and equity.
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Unleash the power of language models with fine-tuning. In this course, you will learn how to adjust a pre-trained model to a specific task. You will start with full-parameter fine-tuning using a small language model. To tune larger models like Gemma, you will learn parameter-efficient techniques with a focus on LoRA. Finally, you will be briefly introduced to reinforcement learning as an alternative to supervised fine-tuning (SFT). You will also explore how AI is imagined and made sense of in cultural contexts. You will consider why responsible AI is not just about technical safety but also about building governance systems that reflect community values and protect the public interest.
Pelajari lebih lanjut
Anda telah membangun agen LLM dasar yang merespons kueri. Sekarang, mari kita jadikan agen itu stateful. Menggunakan status sesi untuk membangun agen yang mempertahankan konteks, mengingat preferensi pengguna, dan memberikan pengalaman yang dipersonalisasi. Mengubah agen dari pemberi respons stateless menjadi asisten cerdas.
Mempelajari konten lain dalam program Gemini Enterprise Agent Ready (GEAR).
Bergabung dengan forum komunitas untuk bertanya dan berdiskusi
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You’ve built capable agents with powerful tools—now ensure they operate safely and reliably. Use callbacks as observation points and control mechanisms. Monitor what’s happening, validate inputs and outputs, implement guardrails, and gain confidence that your agents behave in production.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Architect 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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Kursus ini mengajarkan cara men-deploy agen ADK ke Vertex AI Agent Engine dan Cloud Run, dengan memori lintas sesi opsional melalui Memory Bank.
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Learn to coordinate multiple specialized agents working together. This lesson teaches you when to use multi-agent systems, how to orchestrate agents with workflow patterns, and how agents communicate through shared state. By the end, you’ll build a complete multi-agent application.
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Manfaatkan keefektifan AI generatif untuk membuat agen otomatis yang cerdas. Setelah menyelesaikan kursus ini, Anda akan siap mengembangkan agen penyimpanan data yang dapat langsung menjawab pertanyaan kompleks dengan mengekstrak dan menyintesis informasi secara otomatis dari situs, dokumen, atau data terstruktur Anda. Ucapkan selamat tinggal pada FAQ statis—agen baru Anda akan memberikan jawaban yang dinamis dan akurat, serta menampilkan URL sumber aslinya. Agen ini bisa melakukan semuanya dengan penyiapan yang sederhana dan cepat.
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Dalam kursus ini, Anda akan mempelajari cara membangun pengalaman percakapan untuk Conversational Agents menggunakan Playbook Generatif. Anda akan memulai dengan pengantar playbook dan mempelajari cara menyiapkan playbook pertama Anda. Anda juga akan mempelajari pentingnya pengujian, serta pertimbangan produksi utama seperti batas kuota dan integrasi. Kursus ini diakhiri dengan studi kasus yang menunjukkan cara menggunakan playbook untuk panduan generatif.
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Video ini membahas cara menggunakan perintah sederhana di Gemini Canvas untuk membuat, menyesuaikan, dan membagikan game Anda sendiri, seperti Tic-Tac-Toe.
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Video ini membahas cara menggunakan perintah teks sederhana di Gemini Canvas untuk membuat synthesizer musik yang sepenuhnya interaktif dengan kontrol kustom dan keyboard yang dapat dimainkan.
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Video ini membahas cara menggunakan Deep Research Gemini dengan perintah kreatif untuk mengubah informasi kompleks menjadi analisis yang menyenangkan dan dipersonalisasi, seperti laporan evaluasi performa olahraga dan bagan perbandingan.
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Video ini membahas cara menggunakan menu Buat di Gemini Canvas untuk mengubah teks panjang menjadi aset visual seperti infografis dan halaman web secara instan.
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Video ini membahas cara menggunakan Gemini Canvas untuk mengubah gambar sederhana aplikasi menjadi prototipe fungsional menggunakan teknik yang disebut "vibe coding".
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In this video, you'll learn to use Gemini in Google Sheets to automatically generate organized trackers from unstructured data. You'll learn how to write a prompt that references other Google Drive files using the "@" symbol. You'll also see how Gemini builds a fully formatted, color-coded table with drop-down menus based on the data in your notes, saving you significant manual effort.
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Video ini membahas cara menggunakan Gemini di Gmail untuk mengelola Google Kalender Anda dengan menanyakan jadwal Anda di panel samping dan menggunakan fitur sekali klik "tambahkan ke kalender" untuk acara yang terdeteksi di email.
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In this video, you'll learn to use Gemini in Google Slides to build polished presentations efficiently. You'll see how to create slides by referencing content directly from your Google Drive files using the "@" symbol. You'll also learn to generate custom, professional images from a simple text prompt to visually enhance your presentation.
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In this video, you'll learn to use the "Ask Gemini" feature in Google Sheets to manage your data with natural language. You'll see how to ask Gemini to create dropdowns, highlight sales data, create a pivot table, filter by month, and sort by revenue.
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In this video, you'll learn to use the =AI() function in Google Sheets to automate your work. You'll see how to generate text like slogans, summarize paragraphs of customer feedback, and categorize data by classifying inquiries and analyzing sentiment.
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Video ini akan membahas cara memanfaatkan kemampuan AI canggih Gemini di Google Spreadsheet untuk mengambil data dan menghasilkan insight dengan mudah dalam hitungan menit, semuanya tanpa memerlukan latar belakang teknis atau coding sekalipun.
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Video ini membahas cara menggunakan Gemini dan Apps Script untuk mengotomatiskan tugas manual di Google Workspace. Anda akan mempelajari cara meminta kepada Gemini untuk membuat kode Apps Script yang secara otomatis membuat draf pengingat email di Google Spreadsheet untuk tugas yang belum ditandai sebagai 'Selesai'. Otomatiskan alur kerja Anda tanpa perlu keahlian teknis yang mendalam, sehingga Anda memiliki lebih banyak waktu untuk melakukan pekerjaan yang lebih penting dan menghilangkan tindak lanjut manual.
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In this video, you'll learn to use Gemini in Google Sheets for advanced data analysis. You'll learn how to create data visualizations, like a scatter plot, using a simple prompt. You'll also learn how to ask Gemini to analyze your data for strategic insights and recommendations, such as how to save money.
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Buat aplikasi Gemini Enterprise pertama Anda! Hubungkan beragam sumber data ke aplikasi Anda untuk membangun mesin telusur dan mesin analisis terpadu yang andal. Kuasai kemampuan tingkat lanjut seperti agen Deep Research, pencarian ide multi-agen, dan NotebookLM untuk analisis terfokus.
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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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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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