Chrissy Flicker
Menjadi anggota sejak 2021
Bronze League
22240 poin
Menjadi anggota sejak 2021
This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search. You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.
Unlock the power of Google Cloud's cutting-edge Vertex AI Gemini API to craft innovative multimodal applications. This hands-on course delves into the integration of the Vertex AI SDK for Python, guiding you through the generation of sophisticated responses powered by the Gemini Pro and Gemini Pro Vision models. Get ready to build, deploy, and harness the transformative capabilities of multimodal AI within your own projects. Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.
Get hands-on with the Gemini Pro and Gemini Pro Vision models through our new labs. This course gives you a unique chance to explore these powerful AI tools while our training content is still in development. Learn to interact with the models using the Vertex AI Gemini API and cURL commands, and help us create the best possible learning experience around this technology. Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used) Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities. This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
Menjelajahi teknologi, alat, dan aplikasi penelusuran yang didukung AI dalam kursus ini. Mempelajari penelusuran semantik dengan memanfaatkan embedding vektor, penelusuran campuran yang menggabungkan pendekatan semantik dan kata kunci, serta Retrieval-Augmented Generation (RAG) yang meminimalkan halusinasi AI sebagai agen AI yang di-grounding. Mendapatkan pengalaman praktis dengan Vertex AI Vector Search untuk membangun mesin telusur yang cerdas.
Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop more customized customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to more advanced and customized handling for virtual agent conversations that need to look up and convey dynamic data, and methods available to you for testing your virtual agent and logs which can be useful for understanding issues that arise. This is an intermediate course, intended for learners with the following type of role: Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.
Welcome to "Virtual Agent Development in Dialogflow CX for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX.
Earn a skill badge by completing the Create Conversational AI Agents with Dialogflow CX quest, where you will learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR features. 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.
Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.
Complete the intermediate Manage Data Models in Looker skill badge to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies. 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 course, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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.
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.
This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
Kursus Penjelajah AI Generatif - Vertex AI adalah sekumpulan lab yang membahas cara menggunakan AI Generatif di Google Cloud. Melalui lab ini, Anda akan mempelajari cara menggunakan model dalam rangkaian Vertex AI PaLM API, termasuk text-bison, chat-bison, dan textembedding-gecko. Anda juga akan mempelajari desain perintah, praktik terbaik, serta cara menggunakannya untuk pencarian ide, klasifikasi teks, ekstraksi teks, peringkasan teks, dan banyak lagi. Anda juga akan mempelajari cara menyesuaikan model dasar dengan melatihnya melalui pelatihan kustom Vertex AI dan men-deploy-nya ke endpoint Vertex AI.
This quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.
Kursus ini memperkenalkan Vertex AI Studio, sebuah alat untuk berinteraksi dengan model AI generatif, membuat prototipe ide bisnis, dan meluncurkannya ke dalam produksi. Melalui kasus penggunaan yang imersif, pelajaran menarik, dan lab interaktif, Anda akan menjelajahi siklus proses dari perintah ke produk dan mempelajari cara memanfaatkan Vertex AI Studio untuk aplikasi multimodal Gemini, desain perintah, rekayasa perintah, dan tuning model. Tujuan kursus ini adalah agar Anda dapat memanfaatkan potensi AI generatif dalam project Anda dengan Vertex AI Studio.
Kursus ini memberi Anda sinopsis tentang arsitektur encoder-decoder, yang merupakan arsitektur machine learning yang canggih dan umum untuk tugas urutan-ke-urutan seperti terjemahan mesin, ringkasan teks, dan tanya jawab. Anda akan belajar tentang komponen utama arsitektur encoder-decoder serta cara melatih dan menyalurkan model ini. Dalam panduan lab yang sesuai, Anda akan membuat kode pada penerapan simpel arsitektur encoder-decoder di TensorFlow untuk pembuatan puisi dari awal.
Dapatkan badge keahlian dengan menyelesaikan kursus Introduction to Generative AI, Introduction to Large Language Models, dan Introduction to Responsible AI. Dengan berhasil menyelesaikan kuis akhir, Anda membuktikan pemahaman Anda tentang konsep dasar AI generatif. Badge keahlian adalah badge digital yang diberikan oleh Google Cloud sebagai pengakuan atas pengetahuan Anda tentang produk dan layanan Google Cloud. Pamerkan badge keahlian Anda dengan menampilkan profil Anda kepada publik dan menambahkannya ke profil media sosial Anda.
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.
Kursus ini menjelaskan cara membuat model keterangan gambar menggunakan deep learning. Anda akan belajar tentang berbagai komponen model keterangan gambar, seperti encoder dan decoder, serta cara melatih dan mengevaluasi model. Pada akhir kursus ini, Anda akan dapat membuat model keterangan gambar Anda sendiri dan menggunakannya untuk menghasilkan teks bagi gambar.
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
Kursus ini memperkenalkan model difusi, yaitu kelompok model machine learning yang belakangan ini menunjukkan potensinya dalam ranah pembuatan gambar. Model difusi mengambil inspirasi dari fisika, khususnya termodinamika. Dalam beberapa tahun terakhir, model difusi menjadi populer baik di dunia industri maupun penelitian. Model difusi mendasari banyak alat dan model pembuatan gambar yang canggih di Google Cloud. Kursus ini memperkenalkan Anda pada teori yang melandasi model difusi dan cara melatih serta men-deploy-nya di Vertex AI.
Kursus ini memperkenalkan Anda pada arsitektur Transformer dan model Representasi Encoder Dua Arah dari Transformer (Bidirectional Encoder Representations from Transformers atau BERT). Anda akan belajar tentang komponen utama arsitektur Transformer, seperti mekanisme self-attention, dan cara penggunaannya untuk membangun model BERT. Anda juga akan belajar tentang berbagai tugas yang dapat memanfaatkan BERT, seperti klasifikasi teks, menjawab pertanyaan, dan inferensi natural language. Kursus ini diperkirakan memakan waktu sekitar 45 menit untuk menyelesaikannya.
Dalam kursus ini Anda akan diperkenalkan dengan mekanisme atensi, yakni teknik efektif yang membuat jaringan neural berfokus pada bagian tertentu urutan input. Anda akan mempelajari cara kerja atensi, cara penggunaannya untuk meningkatkan performa berbagai tugas machine learning, termasuk terjemahan mesin, peringkasan teks, dan menjawab pertanyaan.
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.
Ini adalah kursus pengantar pembelajaran mikro yang bertujuan untuk mendefinisikan AI Generatif, cara penggunaannya, dan perbedaannya dari metode machine learning konvensional. Kursus ini juga mencakup Alat-alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.
Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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. 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 praktik yang interaktif. Selesaikan kursus badge keahlian ini dan challenge lab penilaian akhir untuk menerima badge keahlian yang dapat Anda bagikan ke jaringan Anda.
Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.