データを活用したいPMの方々向けの講座です。PM職務でデータを活用する全プロセスが含まれた講座で、転職1日目の業務からプロジェクトの開始と終了まで、業務の流れを全て盛り込みました。データに基づいた思考から論理的思考、指標定義、ログ設計、実験設計、データ文化作りなどを全て扱い、考える力を養うためのデータ入門講座です。 PM向けに作成しましたが、データ分析家の方にも良い内容になるよう構成しました（実際に多くの分析家の方々にご受講いただいています）。 その他にも、マーケター、デザイナー、事業企画職の方々にも多くご受講いただいています。
データ基盤の業務プロセス
プロダクトデータ分析
実験設計(AB Test)
指標を定義する
データログ設計（データロギング）
ChatGPTを使った例
データ分析
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Q.この講義を聞く前に悩んでみると良いことは何ですか？
あなたが会社で経験している「問題」を定義し、問題を解決するために何が必要かを考えてください。必要なデータがあれば、このレッスンが役に立ちます。
Q.該当講義はPython、SQLのような技術的な内容も扱いますか？
いいえ。このレッスンは、データを活用する業務プロセスについて説明します。 Python、SQLなどの技術的な内容よりも、実際に業務を進める際に必要な問題定義能力と業務を進める過程について学習します。今後別途講義でBigQuery(SQL)講義を制作する予定です。
Q.データを初めて勉強するのに、難しくないでしょうか？
データを初めて勉強する人が受講するという仮定のもとで講義を作成しました。データを活用する観点であり講義を進めるため、講義から数式は出ません。できるだけ基本的な説明を盛り込んで、難しい部分があれば、いつでも質問してください！
✨受講前の注意事項
学習資料
選手の知識と注意事項
データに初めて触れた人も聞けるようにできるだけ説明を追加したので、必須選手の知識はありません。ただし、会社で解決したい問題が明確に存在すればさらに良いです。
講義の質問の回答は確認するたびに回答をいただく予定であり、悩み相談所を毎月運営して該当内容を更新する予定です（悩みを教えてくださる方の許可を得た後）また皆さんが共通して気になる内容があれば参考にしてお手伝いします。複数の質問をしていただければいいですね！ディスコードに入って質問するのも大好きです。
学んだ内容をブログにまとめたい場合は、私のウェブページと講義リンクを必ず明記してください。
ただし、講義の大部分を上げることは著作権関連の問題が存在する可能性があります。講義で必ず覚えたい核心と自分の考えを載せて文を書いてみることをお勧めします。
ソンポソン（Product Manager、エレガントな兄弟）
データベースの意思決定を今や阻止するようになったPMには、一幹の光になってくれる講義だと思います。 PMなら誰でも仕事をしながら体験される事例を通じて講義内容を働くときにどのように適用させることができるか確信がありました。離職をして新しい環境に適応しなければならないか、業務の範囲が広がったPMに、または今ちょうどPMになった方にはこの講義を通じてPMとしての問題定義と成果測定、実験設計など全般的な意思決定力を高め、プロイルカットになる秘法書になります。
ユン・ソクジンさん（Product Owner、LINER）
「PMのためのデータリテラシー」は、PMのデータ活用の目的から適用までを網羅する経験ベースのノウハウを提供します。置いておいて噛むほど内容の密度が高く、PMの様々な悩みを聞く講義です。 PMは絶えず変化する状況の中で、製品戦略を確立し、説得し、成功させる必要があります。 「PMのためのデータリテラシー」のレッスンを通じて、組織の成長を促進するPMに成長することを願っています。
조동민さん(Data Analyst, ネクソン)
<「あなたのペインポイント」とは何ですか？> AHA Moment。たくさん聞いた言葉です。しかし、実行するのは難しいです。なぜなら、AHA Momentを見つけるためにどんな基盤が整っていなければならないのか、誰とどのように話すべきかなどがよく分からないからです。本当のPain Pointは概念ではなく、概念を実行する「方法」にあると思います。そして、その「方法」に対して実質的な答えを与えることが本講義の強みといえます。
ファンテヨンさん（Product Analyst、ラポラプス）
関連部門（特に製品組織）と協業して成果を出した経験のあるカイルの経験と悩みが込められているのが、この講義の最大の利点です。製品チームと一緒に働きながら必要だと思っていた部分だけでなく、実際に発生する事例が適切に含まれているため、ジュニアPMや製品組織とコラボレーションするジュニアデータアナリストにぜひおすすめしてほしい講義です。
パク・ギョンホ（AI Research Scientist、ソカ）
「データ中心組織で効果的に働く」という言葉を一見すると簡単に見えますが、「よく」働くためには数多くの悩みと試行錯誤が必要です。単純な技術的能力を超えて、意思決定プロセス、組織文化設定、指標設定、分析まで、数多くのことを理解するプロセスが必要です。この講義は、データ中心の組織に入社/転職する前の方やデータに基づいて働きたいPM/POの方々に、上記の要素のすべての内容をお知らせする講義です。カイルと一緒に働きながら体で感じ、私がジュニアだった時代に経験した試行錯誤を減らすことができる内容がすべて含まれている講義です。データ中心の組織からビジネスインパクトに至る業務に必要な講義に強くお勧めします。
🌿そして講義の作成に役立ってくださった方
AC2とRET（Really Effective Teacher）のトレーニングで講義に役立つインスピレーションをたくさん得ました。講義制作時にフィードバックをいただいたキム・テフン様、パク・ジス様、ユ・ヒョンヨン様、ユン・ソクジン様、ソンポソン様、イ・ウンウォン様、イ・チャンヒョン様、チョン・ハリム様、チョン・ハリム様、チョン・ヘウォン様、チョ・ドンミン様、チョ・ソンミン様、ファン・テヨン様ありがとうございます。
学習対象は
誰でしょう？
データに関心があるPM
プロダクトデータ分析をしたい方
データリテラシー能力を求める方
全般的なデータ思考能力を備えた新人データアナリスト
データ文化を作っている方
12,854
受講生
396
受講レビュー
355
回答
4.9
講座評価
5
講座
9년차 데이터 과학자, 데이터 엔지니어, 머신러닝 엔지니어로 근무했으며, 쏘카와 타다에서 데이터 분석, 데이터 엔지니어링 개발, 머신러닝 알고리즘을 개발했습니다.
카일스쿨 유튜브에 데이터 커리어 관련 영상을 올리고 있으며, 어떻게 해야 강의를 수강하신 분들이 회사에서 일을 잘할 수 있을까?를 고민하며 자료를 만들고 있어요.
Google의 GDE(Cloud)로 활동하고 있어요.
카일스쿨 유튜브 : https://www.youtube.com/c/kyleschool
기술 블로그 : https://zzsza.github.io/
인스타그램 : https://www.instagram.com/data.scientist/
대표 컨텐츠 : https://github.com/Team-Neighborhood/I-want-to-study-Data-Science
데이터 과학자가 되기 위해 진행한 다양한 노력들 : https://zzsza.github.io/diary/2019/04/05/how-to-study-datascience/
全体
90件 ∙ (15時間 35分)
講座資料（こうぎしりょう）:
全体
128件
4.9
128件の受講レビュー
受講レビュー 1
∙
平均評価 5.0
5
The lecture content was very helpful to me, so I am leaving a detailed review in case it will be of some help to those who are considering taking the course :) [Background for taking the course] - I work at a digital marketing agency to help accurately measure and improve advertising performance by better utilizing Ad Tech and data. - However, since the team was newly formed and we were working without a mentor, the process for solving problems based on data was not well established, so I took the course to stabilize the team's work system. [How I took the course] - I thought it would be virtually impossible to complete the course with just my own will, so I gathered study members on Discord...! (There were more people like me than I thought, lol) - I recruited people with similar goals and wills and opened a study group, and operated it for the purposes of 1) completing the course, and 2) sharing each other's experiences. - There were often cases where the content I needed right away was covered in the course while I was working, so I put the course up and used it as a handbook while working. - I organized the newly learned information or the information I wanted to share with my team members into a document in Jira Confluence and shared it, and spread the knowledge within the team. [What improved after listening to the lecture] - Other existing data-related lectures seemed to deal with technical aspects, but rather than these technical aspects, I was able to build the soft skills that are most needed in the field. - Communication became clearer as I gave names to frameworks and methodologies that I had been practicing without even knowing the names. - In particular, the problem definition framework and data log design part were the parts that were closest to my domain, so I received a lot of help in this area. - As I learned about various methodologies that I had not known before, I was able to approach and solve problems in new ways. [Who would you recommend it to] - I think it would be more helpful to current employees than job seekers (there are so many moments where you really agree and sympathize while watching the lecture...) - I think it would also be of great help to marketers who communicate based on data (you can gain insight into how to utilize trackers such as GA or Appsflyer) - I also recommend it to everyone who wants to solve problems based on data. Fighting to you all!
Hello Edgar :) Thank you for such a sincere review! I think many people will be able to see if this review will help them. You did a great job gathering study members in Discord and sticking to it. I think you thought hard about what to do and put it into practice, so I want to cheer you on..! I wanted to help you do your work well right away, so I made the lecture focusing on that content. I made it for PMs with 2-3 years of experience, but it will also be helpful for those with 2-3 years of experience as marketers and data analysts (I think it might be less noticeable when I was a student, but I thought it might be okay to hear this kind of content as a student) Thank you so much for leaving a good review! I will also work harder..!
受講レビュー 1
∙
平均評価 5.0
5
I am currently working as a data analyst. As soon as I heard that Kyle's lecture was uploaded, I paid for it and quickly watched the interesting parts first. I think this lecture will be helpful not only for PMs but also for those in the data field. In particular, I think it would be good for those who are interested in the data literacy capacity and data culture of an organization.
Hello! :) Thank you so much for looking at the interesting parts and leaving a review! This is my first Inflearn review, so I was excited to see it. I really felt that an organization's data literacy and data culture are not completed in a day, and I felt that I need to talk to many people and implement various strategies for change in the process. From this perspective, I created it because I thought that if I shared the tacit knowledge that I know with many people, they would not have to go through my trial and error, so thank you so much for talking about it so well! Please let me know anytime if you need help :)
受講レビュー 1
∙
平均評価 5.0
5
Thank you so much, Kyle School!! I listened to everything except the parts I left to listen to when I actually encountered it. It's a great lecture that I can always refer to when I run into a problem. Thank you for making it! I keep recommending it to people around me. I'm always grateful for the sincere advice..!! https://sowhatmylifeismine.tistory.com/263 This is a summary of the parts I used while listening to the lecture! It's not enough, but I hope it will be of some help to others!
Hello Squirrel! Thank you for always asking me questions while taking the class! Thanks to you, I was able to get inspiration. If you read this class review, I think it would be good to read the blog too since you wrote a good blog review :) If you need help in the future, please let me know anytime-!
受講レビュー 2
∙
平均評価 5.0
5
These days, PM is a given, and I think the core competency of a data analyst is not simply the ability to use tools, but the ability to solve problems. I think this lecture has a great influence on developing the ability to solve service problems based on data, such as 'problem selection', 'setting key indicators', 'what data should I look at?'. I think it was really lucky to have found this lecture. Thank you!
Hello :) Thank you so much for saying that it was a good luck to find the lecture..! I hope we can talk together and develop problem-solving skills! :) Thank you for the course review!
受講レビュー 1
∙
平均評価 5.0
5
I really liked the lecture because it focused on how to solve problems and make decisions with data, rather than on data analysis skills. I really liked how the lecture was structured so that you could think and act based on situations that could actually happen through actual case studies, rather than just talking about ways of thinking or mindsets. Maybe that’s why I tried it out with my team members right away and got help. It was also really great that you could get 1:1 coaching from Kyle if you took more than 70% of the course. I hope that many people will learn data problem solving and decision-making processes through this lecture and become good workers at their companies. Thank you so much for creating such a great lecture.
Hello! I'm glad that I was able to encourage you to take action with your mindset, mindset, and case study! When I was making the lecture, I had the goal of "Let's make it so that those who listen to this lecture can actually take action!" Thank you for mentioning the coaching that is currently being offered to the first 100 people as an event! I hope those who have the opportunity will definitely try it out :)
￥15,575
知識共有者の他の講座を見てみましょう！
同じ分野の他の講座を見てみましょう！
