この専門講座について
13,585 最近の表示

100%オンラインコース

自分のスケジュールですぐに学習を始めてください。

フレキシブルなスケジュール

柔軟性のある期限の設定および維持

上級レベル

約3か月で修了

推奨5時間/週

英語

字幕:英語

習得するスキル

R ProgrammingMarketing AnalyticsPresentationMarketing Performance Measurement And Management

100%オンラインコース

自分のスケジュールですぐに学習を始めてください。

フレキシブルなスケジュール

柔軟性のある期限の設定および維持

上級レベル

約3か月で修了

推奨5時間/週

英語

字幕:英語

専門講座のしくみ

コースを受講しましょう。

Coursera(コーセラ)の専門講座は、一連のコース群であり、技術を身に付ける手助けとなります。開始するには、専門講座に直接登録するか、コースを確認して受講したいコースを選択してください。専門講座の一部であるコースにサブスクライブすると、自動的にすべての専門講座にサブスクライブされます。1つのコースを修了するだけでも結構です。いつでも、学習を一時停止したり、サブスクリプションを終了することができます。コースの登録状況や進捗を追跡するには、受講生のダッシュボードにアクセスしてください。

実践型プロジェクト

すべての専門講座には、実践型プロジェクトが含まれています。専門講座を完了して修了証を獲得するには、成功裏にプロジェクトを終了させる必要があります。専門講座に実践型プロジェクトに関する別のコースが含まれている場合、専門講座を開始するには、それら他のコースをそれぞれ終了させる必要があります。

修了証を取得

すべてのコースを終了し、実践型プロジェクトを完了すると、修了証を獲得します。この修了証は、今後採用企業やあなたの職業ネットワークと共有できます。

how it works

この専門講座には4コースあります。

コース1

Foundations of strategic business analytics

4.4
436件の評価
99件のレビュー

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R. With this course, you’ll have a first overview on Strategic Business Analytics topics. We’ll discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc. We’ll cover many different data analytics techniques, each time explaining how to be relevant for your business. We’ll pay special attention to how you can produce convincing, actionable, and efficient insights. We'll also present you with different data analytics tools to be applied to different types of issues. By doing so, we’ll help you develop four sets of skills needed to leverage value from data: Analytics, IT, Business and Communication. By the end of this MOOC, you should be able to approach a business issue using Analytics by (1) qualifying the issue at hand in quantitative terms, (2) conducting relevant data analyses, and (3) presenting your conclusions and recommendations in a business-oriented, actionable and efficient way. Prerequisites : 1/ Be able to use R or to program 2/ To know the fundamentals of databases, data analysis (regression, classification, clustering) We give credit to Pauline Glikman, Albane Gaubert, Elias Abou Khalil-Lanvin (Students at ESSEC BUSINESS SCHOOL) for their contribution to this course design.

...
コース2

Foundations of marketing analytics

4.5
463件の評価
130件のレビュー

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role, in particular in marketing. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R. Business Analytics, Big Data and Data Science are very hot topics today, and for good reasons. Companies are sitting on a treasure trove of data, but usually lack the skills and people to analyze and exploit that data efficiently. Those companies who develop the skills and hire the right people to analyze and exploit that data will have a clear competitive advantage. It's especially true in one domain: marketing. About 90% of the data collected by companies today are related to customer actions and marketing activities.The domain of Marketing Analytics is absolutely huge, and may cover fancy topics such as text mining, social network analysis, sentiment analysis, real-time bidding, online campaign optimization, and so on. But at the heart of marketing lie a few basic questions that often remain unanswered: (1) who are my customers, (2) which customers should I target and spend most of my marketing budget on, and (3) what's the future value of my customers so I can concentrate on those who will be worth the most to the company in the future. That's exactly what this course will cover: segmentation is all about understanding your customers, scorings models are about targeting the right ones, and customer lifetime value is about anticipating their future value. These are the foundations of Marketing Analytics. And that's what you'll learn to do in this course.

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コース3

Case studies in business analytics with ACCENTURE

3.7
139件の評価
58件のレビュー

Who is this course for ? This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors. The objective is to give you an helicopter overview on what's happening in this field. You will see how the tools presented in the two previous courses of the Specialization are used in real life projects. We want to ignite your reflection process. Hence, you will best make use of the Accenture cases by watching first the MOOC and then investigate by yourself on the different concepts, industries, or challenges that are introduced during the videos. At the end of this course learners will be able to: - identify the possible applications of business analytics, - hence, reflect on the possible solutions and added-value applications that could be proposed for their capstone project. The cases will be presented by senior practitioners from Accenture with different backgrounds in term of industry, function, and country. Special attention will be paid to the "value case" of the issue raised to prepare you for the capstone project of the specialization. About Accenture Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With more than 358,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com.

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コース4

Capstone: Create Value from Open Data

3.6
24件の評価
8件のレビュー

The Capstone project is an individual assignment. Participants decide the theme they want to explore and define the issue they want to solve. Their “playing field” should provide data from various sectors (such as farming and nutrition, culture, economy and employment, Education & Research, International & Europe, Housing, Sustainable, Development & Energies, Health & Social, Society, Territories & Transport). Participants are encouraged to mix the different fields and leverage the existing information with other (properly sourced) open data sets. Deliverable 1 is the preliminary preparation and problem qualification step. The objectives is to define the what, why & how. What issue do we want to solve? Why does it promise value for public authorities, companies, citizens? How do we want to explore the provided data? For Deliverable 2, the participant needs to present the intermediary outputs and adjustments to the analysis framework. The objectives is to confirm the how and the relevancy of the first results. Finally, with Deliverable 3, the participant needs to present the final outputs and the value case. The objective is to confirm the why. Why will it create value for public authorities, companies, and citizens. Assessment and grading: the participants will present their results to their peers on a regular basis. An evaluation framework will be provided for the participants to assess the quality of each other’s deliverables.

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講師

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Nicolas Glady

Associate professor, at ESSEC Business School
Marketing Department
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Arnaud De Bruyn

Professor at ESSEC Business School
Marketing department

業界パートナー

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エセック・ビジネススクール(ESSEC Business School)について

For over a century, ESSEC has been developing a state-of-the-art educational program that gives the individual pride of place in its learning model, promoting the values of freedom, openness, innovation and responsibility. Preparing future managers to reconcile personal interests with collective responsibility, giving consideration to the common good in their decision-making, and weighing economic challenges against the social costs are some of the objectives ESSEC has set for itself. Its ultimate goal? To create a global world that has meaning for us all. ...

よくある質問

  • はい。まず始めに興味のあるコースカードをクリックして登録します。コースに登録して修了することによって、共有できる修了証を取得するか、無料でコースを聴講してコースの教材を確認することができます。専門講座の一部であるコースにサブスクライブすると、専門講座全体に自動的にサブスクライブされます。進捗を追跡するには、受講生のダッシュボードにアクセスしてください。

  • このコースは完全にオンラインで提供されているため、実際に教室に出席する必要はありません。Webまたはモバイル機器からいつでもどこからでも講義、学習用教材、課題にアクセスできます。

  • この専門講座では大学の単位は付与されませんが、一部の大学では専門講座修了証を単位として承認する場合があります。詳細については、大学にお問い合わせください。

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 5 months.

  • Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over. The final Capstone Project will be offered 3-4 times per year.

  • This Specialization is designed for graduate students and professional interested in practical applications of business analytics techniques and big data,­ with a good IT and statistical background. You’ll need a strong background in R and analytics to complete the coursework, and some experience with machine learning and SQL will also be useful.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • You’ll be a fully accomplished expert in big data management, with a robust understanding of how data can be used to leverage strategic value. You’ll be comfortable qualifying research objectives, combining and manipulating data sets, and interpreting them. You’ll be prepared to present your interpretations and value case to potential stakeholders successfully.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。