Launching into Machine Learning 日本語版 from Coursera

What's inside

Syllabus

はじめに

このモジュールでは、コースの概要とその目標を説明します。

データについて知る: 探索的データ分析によるデータ品質の改善

このモジュールでは、探索的データ分析を実行することで、データの品質を向上させる方法と、データを探索する方法について紹介します。機械学習におけるデータ整理の重要性について説明し、データ品質にどのように影響するかを説明します。たとえば、欠損値があると結果に歪みが生じる可能性があります。また、データ探索の重要性についても学びます。データを整理したら、データセットに対して探索的データ分析を実行しましょう。

機械学習の実践

このモジュールでは、ML 担当者としての成長を加速できるように、機械学習の主要なタイプを紹介します。

Vertex AI を使用した AutoML モデルのトレーニング

このモジュールでは、Vertex AI を使用した AutoML モデルのトレーニングについて紹介します。

BigQuery の機械学習: データが存在する ML モデルの開発

このモジュールでは、BigQuery ML とその機能を紹介します。

最適化

このモジュールでは、ML モデルを最適化する方法を説明します。

一般化とサンプリング

次に、かなり変わった質問にお答えいただきます。最も正確な ML モデルが適切な選択モデルではないのは、どのような場合ですか？最適化に関する最後のモジュールで示唆したとおり、モデルのトレーニングデータセットの損失指標が 0 だからといって、実際の環境の新しいデータでうまく機能するわけではありません。再現可能なトレーニング、評価、テストデータセットを作成し、パフォーマンスベンチマークを確立する方法を学習します。

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

業界で標準となっている x を探求します

機械学習の主要なタイプを紹介し、ML 担当者としての成長を加速させます

データの品質を向上させる方法や探索的データ分析を実行する方法について説明します

コードを 1 行も記述せずに ML モデルを構築、トレーニング、デプロイする方法について説明します

ML モデルを最適化する方法について説明します

BigQuery ML とその機能を紹介し、データが存在する ML モデルの開発を可能にします

Reviews summary

Intro to ml for beginners

This course serves as a comprehensive introduction to machine learning concepts for complete beginners. Despite some outdated course materials, students enjoyed the accessible explanations and found the content engaging.

Provides hands-on experience with Big Query.

"Big QueryのHands Onができることがメリットかと思います。"

Great for those new to machine learning.

"初心者でも何とか。自身のいかに勉強不足か分かったので、引き続き学習していきたい"

Course information may be out of date.

"The reason why we couldn't make 5 stars is that the explanation of the lab is old."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Launching into Machine Learning 日本語版 with these activities:

コース資料の整理と注釈付け

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コース資料を整理することで、効率的な学習を確保しましょう。

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講義資料、課題、試験を整理する。
重要なポイントに注釈やメモを追加する。

Vertex AI での AutoML モデルのトレーニングのチュートリアル

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Vertex AI を使用して AutoML モデルを構築する方法について詳しく学びましょう。

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Vertex AI のドキュメントを研究する。
AutoML モデルをトレーニングするためのサンプルコードを見つける。
自分のデータセットを使用して AutoML モデルをトレーニングする。

BigQuery 機械学習の練習問題を解く

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BigQuery 機械学習の機能を強化しましょう。

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BigQuery ML のドキュメントを調べる。
BigQuery ML を使用したサンプルクエリを練習する。
自分のデータセットを使用して BigQuery ML モデルを作成する。

Two other activities

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一般化とサンプリングに関する課題のグループディスカッションに参加する

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他の学習者と協力して、一般化とサンプリングの概念を強化しましょう。

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一般化とサンプリングに関するオンラインのディスカッションフォーラムを見つける。
他の学習者と議論し、考えを共有する。

機械学習コンテストに参加する

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実際のプロジェクトで機械学習のスキルを試し、磨きましょう。

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機械学習のコンテストやハッカソンを見つける。
チームに参加するか、自分一人で参加する。
機械学習モデルを作成して提出する。

Career center

Learners who complete Launching into Machine Learning 日本語版 will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use their expertise in statistics, machine learning, artificial intelligence, data visualization, and programming to extract insights from data. If you want to be a Data Scientist, taking this course will help build a foundation that will allow you to succeed in this role. You will find the hands-on information provided on AutoML and BigQuery particularly valuable.

See salaries and explore the career path for Data Scientist

Data Analyst

Responding to business needs by translating data into meaningful insights, Data Analysts use statistics, data discovery tools, and machine learning to inform effective decision-making. Taking this course will equip you to use these tools effectively. You will find the information in the syllabus on data analysis and data quality to be particularly useful.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians collect, analyze, interpret, and present data to inform decision-making. This course will introduce you to the essential principles of statistics and data analysis, including key topics such as data quality, hypothesis testing, and predictive modeling. You will find the material on data visualization particularly useful in your role as a statistician.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts use math, programming, statistics, and machine learning to analyze and model financial data. As a Quant, this course will help build a foundation in the statistics and programming skills necessary for your success. You will especially appreciate the information provided on data analysis and model optimization.

See salaries and explore the career path for Quantitative Analyst

Machine Learning Engineer

Machine Learning Engineers use their knowledge of programming, mathematics, and statistics to design, build, and maintain machine learning models. This course will introduce you to the essential concepts of machine learning, and help you develop the skills necessary to succeed in this role. You will find the syllabus's content on optimization and model evaluation to be especially helpful.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers use computer science principles to design, build, and maintain software systems. While coding is your primary responsibility, you will also work with data scientists and data engineers to gather data requirements, develop algorithms, and implement machine learning models. This course will help to teach you the basics of machine learning, and you will find yourself referring to the content on data analysis and model deployment as needed.

See salaries and explore the career path for Software Engineer

Business Analyst

Business Analysts bridge the gap between technical and business teams, working collaboratively to define business needs and create solutions that drive organizational success. This course will help you develop foundational insights into the process of converting data into meaningful and actionable business applications.

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Data Engineer

Data Engineers are responsible for designing, building, and maintaining data pipelines and infrastructure. This course will help you bridge any existing gaps in your foundational knowledge of machine learning. You will find the information provided on data quality and data analysis to be of particular value.

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Product Manager

Product Managers are responsible for the strategic vision, feature definition, roadmap creation, and marketing of a product. Data is continuously surfacing more insights that drive product strategy; therefore, a practical understanding of machine learning is increasingly more critical for success in this role. This course will teach you the basics of machine learning that will allow you to work with your technical team to develop and launch new products.

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Financial Analyst

Financial Analysts use data to make investment recommendations and inform financial decisions. This course may help you build foundational principles of statistics and data analysis, which will enhance your ability to interpret financial data and apply machine learning to your work.

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Operations Research Analyst

Operations Research Analysts use analytical methods and algorithms to solve complex problems and improve decision-making in organizations. This course may be helpful to you in developing foundational principles of statistics and data analysis, which may supplement your prior coursework or provide a solid overview as you enter the field.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course may be helpful to you as it will teach you basic principles of statistics and data analysis, which will supplement your prior coursework or provide a solid overview as you enter the field.

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Market Researcher

Market Researchers gather and analyze data to understand market trends and consumer behavior. This course may be useful to you as it will teach you basic data analysis skills and introduce you to the principles of machine learning that are increasingly used in the field.

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Consultant

Consultants provide expert advice and guidance to businesses and organizations. Increasingly, data science and machine learning are playing a larger role in consulting, so foundational knowledge in these areas is becoming increasingly valuable. This course will introduce you to these concepts and teach you practical skills that you can apply to your work as a consultant.

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Program Manager

Program Managers are responsible for planning, organizing, and executing projects. This course may be useful to you as it will provide you with a high-level understanding of data science and machine learning, concepts that are increasingly used in project management.

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