Smart Analytics, Machine Learning, and AI on GCP 日本語版

Google Cloud via Coursera

Go to Course: https://www.coursera.org/learn/smart-analytics-machine-learning-ai-gcp-jp

Introduction

### Course Review: Smart Analytics, Machine Learning, and AI on GCP (日本語版) In today's data-driven world, the integration of machine learning and AI into corporate data pipelines is no longer a luxury—it's a necessity. The online course **"Smart Analytics, Machine Learning, and AI on GCP (日本語版)"** offered on Coursera provides learners with a comprehensive understanding of how to implement machine learning on the Google Cloud Platform (GCP) tailored for Japanese speakers. This course is perfect for professionals looking to enhance their analytical capabilities and harness the power of AI. #### Course Overview The course focuses on enabling participants to extract meaningful insights from data effectively through various approaches to machine learning. It covers a range of methodologies based on the level of customization required, offering insights into Google Cloud's AutoML for minimal customization needs, as well as more customizable solutions like AI Platform Notebooks and BigQuery Machine Learning for those with advanced requirements. Additionally, it delves into using Kubeflow for deploying machine learning solutions at scale. Hands-on experience is emphasized through the use of Qwiklabs, where participants can actively build and experiment with machine learning models within the Google Cloud environment. #### Course Syllabus Breakdown 1. **Introduction** - Overview of the course and agenda setting to prepare learners for what to expect. 2. **Overview of Analytics and AI** - Insight into the types of machine learning available on Google Cloud, providing a foundational understanding of the landscape. 3. **Pre-built ML Model APIs for Unstructured Data** - Practical guidance on utilizing pre-built machine learning model APIs aimed at handling unstructured data, which is prevalent in many business scenarios. 4. **Big Data Analysis Using Notebooks** - Exploration of notebooks as a tool for big data analysis, fostering skills in managing and interpreting large datasets effectively. 5. **Production ML Pipelines using Kubeflow** - This module focuses on crafting custom ML models and introduces Kubeflow and AI Hub as powerful platforms for deploying scalable ML pipelines. 6. **Building Custom Models with BigQuery ML Using SQL** - Participants learn to leverage SQL for constructing custom machine learning models within BigQuery, merging familiarity with SQL and machine learning techniques. 7. **Building Custom Models with AutoML** - Engaging participants in the process of building custom models through AutoML, showcasing how to automate model training and deployment. 8. **Conclusion** - A recap of the course content to reinforce learning and ensure participants leave with a solid understanding of key concepts. #### Why You Should Take This Course The **"Smart Analytics, Machine Learning, and AI on GCP"** course is particularly beneficial for data analysts, software developers, and business professionals looking to deepen their understanding of machine learning in a cloud environment. Here are several reasons to consider enrolling: - **Tailored for Japanese Speakers**: The course offers content in Japanese, making it accessible for native speakers and those more comfortable with the language. - **Hands-On Learning**: The incorporation of Qwiklabs allows for practical application of concepts learned in real environments, facilitating better retention and understanding. - **Diverse Learning Paths**: Whether you need simple automation or robust custom ML models, this course covers a breadth of topics that cater to various skill levels and business needs. - **Industry-Relevant Skills**: Gaining proficiency in using Google Cloud’s tools for machine learning will provide an edge in today’s job market, where cloud competency and data analytics are highly sought after. #### Conclusion If you’re looking to leverage machine learning and AI within your organization and want to build your expertise using Google Cloud Platform, the **"Smart Analytics, Machine Learning, and AI on GCP (日本語版)"** course is highly recommended. The structured approach, combined with comprehensive topics and hands-on experience, will equip you with the necessary skills to transform your data into actionable insights and drive your organization forward in the digital age. Enroll now and start your journey towards becoming proficient in smart analytics and machine learning!

Syllabus

はじめに

このモジュールでは、コースおよびアジェンダについて紹介します

分析と AI の概要

このモジュールでは、Google Cloud で利用可能な ML の種類について説明します

非構造化データ用の事前構築済み ML モデル API

このモジュールでは、非構造化データ用の事前構築済み ML モデル API の使用方法について説明します

Notebooks を使用したビッグデータ分析

このモジュールでは、Notebooks の使用方法について説明します

Kubeflow を使用した本番環境の ML パイプライン

このモジュールでは、カスタム ML モデルの構築について説明し、Kubeflow および AI Hub について紹介します

BigQuery ML で SQL を使用したカスタムモデルの構築

このモジュールでは、BigQuery ML について説明します

AutoML を使用したカスタムモデルの構築

AutoML を使用したカスタムモデルの構築

Module 7: まとめ

このモジュールでは、コースで扱ったトピックについて復習します