전문분야 소개

This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.

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100% 온라인 강좌

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
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탄력적인 일정

유연한 마감을 설정하고 유지 관리합니다.
Beginner Level

초급 단계

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완료하는 데 약 4개월 필요

권장 5시간/주
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English

자막: English, Spanish, Chinese (Simplified), Mongolian

배울 내용

  • Check
    Explain how data is used for recruiting and performance evaluation
  • Check
    Model supply and demand for various business scenarios
  • Check
    Solve business problems with data-driven decision-making
  • Check
    Understand the tools used to predict customer behavior

귀하가 습득할 기술

Customer AnalyticsAnalyticsBusiness AnalyticsDecision Tree
Globe

100% 온라인 강좌

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
Calendar

탄력적인 일정

유연한 마감을 설정하고 유지 관리합니다.
Beginner Level

초급 단계

Clock

완료하는 데 약 4개월 필요

권장 5시간/주
Comment Dots

English

자막: English, Spanish, Chinese (Simplified), Mongolian

전문 분야 이용 방법

강좌 수강

Coursera 전문 분야는 기술을 완벽하게 습득하는 데 도움이 되는 일련의 강좌입니다. 시작하려면 전문 분야에 직접 등록하거나 강좌를 둘러보고 원하는 강좌를 선택하세요. 하나의 전문 분야에 속하는 강좌에 등록하면 해당 전문 분야 전체에 자동으로 등록됩니다. 단 하나의 강좌만 수료해도 됩니다. — 학습을 일시 중지하거나 언제든 구독을 종료할 수 있습니다. 학습자 대시보드를 방문하여 강좌 등록 상태와 진도를 추적해 보세요.

실습 프로젝트

모든 전문 분야에는 실습 프로젝트가 포함되어 있습니다. 전문 분야를 완료하고 수료증을 받으려면 프로젝트를 성공적으로 마쳐야 합니다. 전문 분야에 별도의 실습 프로젝트 강좌가 포함되어 있는 경우 각 강좌를 완료해야 프로젝트를 시작할 수 있습니다.

수료증 취득

모든 강좌를 마치고 실습 프로젝트를 완료하면 취업할 때나 전문가 네트워크에 진입할 때 제시할 수 있는 수료증을 취득할 수 있습니다.

how it works

이 전문분야에는 5개의 강좌가 있습니다.

1강좌

Customer Analytics

4.5
4,758개의 평가
1,068개의 리뷰
Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics. Course Learning Outcomes: After completing the course learners will be able to... Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions Describe the main tools used to predict customer behavior and identify the appropriate uses for each tool Communicate key ideas about customer analytics and how the field informs business decisions Communicate the history of customer analytics and latest best practices at top firms...
2강좌

Operations Analytics

4.7
2,471개의 평가
488개의 리뷰
This course is designed to impact the way you think about transforming data into better decisions. Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. The course on operations analytics, taught by three of Wharton’s leading experts, focuses on how the data can be used to profitably match supply with demand in various business settings. In this course, you will learn how to model future demand uncertainties, how to predict the outcomes of competing policy choices and how to choose the best course of action in the face of risk. The course will introduce frameworks and ideas that provide insights into a spectrum of real-world business challenges, will teach you methods and software available for tackling these challenges quantitatively as well as the issues involved in gathering the relevant data. This course is appropriate for beginners and business professionals with no prior analytics experience....
3강좌

People Analytics

4.5
2,340개의 평가
416개의 리뷰
People analytics is a data-driven approach to managing people at work. For the first time in history, business leaders can make decisions about their people based on deep analysis of data rather than the traditional methods of personal relationships, decision making based on experience, and risk avoidance. In this brand new course, three of Wharton’s top professors, all pioneers in the field of people analytics, will explore the state-of-the-art techniques used to recruit and retain great people, and demonstrate how these techniques are used at cutting-edge companies. They’ll explain how data and sophisticated analysis is brought to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job design, compensation, and collaboration. This course is an introduction to the theory of people analytics, and is not intended to prepare learners to perform complex talent management data analysis. By the end of this course, you’ll understand how and when hard data is used to make soft-skill decisions about hiring and talent development, so that you can position yourself as a strategic partner in your company’s talent management decisions. This course is intended to introduced you to Organizations flourish when the people who work in them flourish. Analytics can help make both happen. This course in People Analytics is designed to help you flourish in your career, too....
4강좌

Accounting Analytics

4.5
1,500개의 평가
272개의 리뷰
Accounting Analytics explores how financial statement data and non-financial metrics can be linked to financial performance.  In this course, taught by Wharton’s acclaimed accounting professors, you’ll learn how data is used to assess what drives financial performance and to forecast future financial scenarios. While many accounting and financial organizations deliver data, accounting analytics deploys that data to deliver insight, and this course will explore the many areas in which accounting data provides insight into other business areas including consumer behavior predictions, corporate strategy, risk management, optimization, and more. By the end of this course, you’ll understand how financial data and non-financial data interact to forecast events, optimize operations, and determine strategy. This course has been designed to help you make better business decisions about the emerging roles of accounting analytics, so that you can apply what you’ve learned to make your own business decisions and create strategy using financial data. ...

강사

Noah Gans

Anheuser-Busch Professor of Management Science, Professor of Operations, Information and Decisions
The Wharton School

Ron Berman

Assistant Professor of Marketing
The Wharton School

Senthil Veeraraghavan

Associate Professor of Operations, Information and Decisions
The Wharton School

Peter Fader

Professor of Marketing and Co-Director of the Wharton Customer Analytics Initiative
The Wharton School

Eric Bradlow

Professor of Marketing, Statistics, and Education, Chairperson, Wharton Marketing Department, Vice Dean and Director, Wharton Doctoral Program, Co-Director, Wharton Customer Analytics Initiative
The Wharton School

Matthew Bidwell

Associate Professor of Management
The Wharton School

Martine Haas

Associate Professor of Management
The Wharton School

Wharton Teaching Staff

Educators
The Wharton School

Cade Massey

Practice Professor
The Wharton School

Sergei Savin

Associate Professor of Operations, Information and Decisions
The Wharton School

Brian J Bushee

The Geoffrey T. Boisi Professor
Accounting

Christopher D. Ittner

EY Professor of Accounting
Accounting

Raghu Iyengar

Associate Professor of Marketing
The Wharton School

University of Pennsylvania 정보

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

자주 묻는 질문

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in about 5-6 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.

  • 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 gain a deeper understanding of how big data and analytics are used in four key areas: marketing (customer analytics), human resources and talent management (people analytics), operations, and finance. You can use this knowledge to create new business strategies using data, participate in conversations about analytics, transition to a new career, or improve your own business. You will also have a strong foundation for further study related to analytics and big data.

  • You will need a full-featured version of Microsoft Excel for some assignments. You should also have a working knowledge of Excel’s basic functions.

  • No previous knowledge or experience in business or analytics is required. This Specialization is designed for anyone interested in understanding how decisions are made using big data.

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