The role of an Analyst is dynamic, complex, and driven by a variety of skills. These skills range from a basic understanding of financial statement data and non-financial metrics that can be linked to financial performance, to a deeper dive into business and financial modeling. Analysts also utilize spreadsheet models, modeling techniques, and common investment analysis application as part of their toolkit to make informed financial decisions and investments. This multifaceted specialization will equip a learner who might be interested in entering the dynamic world of data and business analysis, and/or is interested gaining deeper technical knowledge in Finance and Quantitative Modeling. Starting from the fundamentals of quantitative modeling, you will learn how to put data to work by using spreadsheets and leverage spreadsheets as a powerful, accessible data analysis tool. You will also be introduced to the world of corporate finance, and gain a better understanding of finance fundamentals, including a variety of real-world situations spanning personal finance, corporate decision-making and financial intermediation.
Ce que vous allez apprendre
Harness the power of spreadsheets to map and predict data
Create your own quantitative models
Read income and cash flow statements
Compétences que vous acquerrez
Les étudiants prenant part à ce Specialization sont
- Financial Analysts
- Chief Financial Officers (CFOs)
- Financial Advisors
- Risk Managers
- Traders
Comment fonctionne la Spécialisation
Suivez les cours
Une Spécialisation Coursera est une série de cours axés sur la maîtrise d'une compétence. Pour commencer, inscrivez-vous directement à la Spécialisation ou passez en revue ses cours et choisissez celui par lequel vous souhaitez commencer. Lorsque vous vous abonnez à un cours faisant partie d'une Spécialisation, vous êtes automatiquement abonné(e) à la Spécialisation complète. Il est possible de terminer seulement un cours : vous pouvez suspendre votre formation ou résilier votre abonnement à tout moment. Rendez-vous sur votre tableau de bord d'étudiant pour suivre vos inscriptions aux cours et vos progrès.
Projet pratique
Chaque Spécialisation inclut un projet pratique. Vous devez réussir le(s) projet(s) pour terminer la Spécialisation et obtenir votre Certificat. Si la Spécialisation inclut un cours dédié au projet pratique, vous devrez terminer tous les autres cours avant de pouvoir le commencer.
Obtenir un Certificat
Lorsque vous aurez terminé tous les cours et le projet pratique, vous obtiendrez un Certificat que vous pourrez partager avec des employeurs éventuels et votre réseau professionnel.
Cette Spécialisation compte 4 cours
Fundamentals of Quantitative Modeling
How can you put data to work for you? Specifically, how can numbers in a spreadsheet tell us about present and past business activities, and how can we use them to forecast the future? The answer is in building quantitative models, and this course is designed to help you understand the fundamentals of this critical, foundational, business skill. Through a series of short lectures, demonstrations, and assignments, you’ll learn the key ideas and process of quantitative modeling so that you can begin to create your own models for your own business or enterprise. By the end of this course, you will have seen a variety of practical commonly used quantitative models as well as the building blocks that will allow you to start structuring your own models. These building blocks will be put to use in the other courses in this Specialization.
Introduction to Spreadsheets and Models
The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have the know-how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future. Through short, easy-to-follow demonstrations, you’ll learn how to use Excel or Sheets so that you can begin to build models and decision trees in future courses in this Specialization. Basic familiarity with, and access to, Excel or Sheets is required.
Financial Acumen for Non-Financial Managers
In this course, you’ll explore how financial statement data and non-financial metrics can be linked to financial performance. Professors Rick Lambert and Chris Ittner of the Wharton School have designed this course to help you gain a practical understanding of how data is used to assess what drives financial performance and forecast future financial scenarios. You’ll learn more about the frameworks of financial reporting, income statements, and cash reporting, and apply different approaches to analyzing financial performance using real-life examples to see the concepts in action. By the end of this course, you’ll have honed your skills in understanding how financial data and non-financial data interact to forecast events and be able to determine the best financial strategy for your organization.
Introduction to Corporate Finance
This course provides a brief introduction to the fundamentals of finance, emphasizing their application to a wide variety of real-world situations spanning personal finance, corporate decision-making, and financial intermediation. Key concepts and applications include: time value of money, risk-return tradeoff, cost of capital, interest rates, retirement savings, mortgage financing, auto leasing, capital budgeting, asset valuation, discounted cash flow (DCF) analysis, net present value, internal rate of return, hurdle rate, payback period.
Enseignants
Richard Waterman
Professor of Statistics
Don Huesman
Managing Director, Wharton Online
Richard Lambert
Professor of Accounting
Christopher D. Ittner
EY Professor of Accounting
Michael R Roberts
William H. Lawrence Professor of Finance, the Wharton School, University of PennsylvaniaÀ propos de Université de Pennsylvanie
Foire Aux Questions
Quelle est la politique de remboursement ?
Puis-je m'inscrire à un seul cours ?
Oui ! Pour commencer, cliquez sur la carte du cours qui vous intéresse et inscrivez-vous. Vous pouvez vous inscrire et terminer le cours pour obtenir un Certificat partageable, ou vous pouvez accéder au cours en auditeur libre afin d'en visualiser gratuitement le contenu. Si vous vous abonnez à un cours faisant partie d'une Spécialisation, vous êtes automatiquement abonné(e) à la Spécialisation complète. Visitez votre tableau de bord d'étudiant(e) pour suivre vos progrès.
Une aide financière est-elle possible ?
Puis-je suivre le cours gratuitement ?
Ce cours est-il vraiment accessible en ligne à 100 % ? Dois-je assister à certaines activités en personne ?
Ce cours est entièrement en ligne : vous n'avez donc pas besoin de vous présenter physiquement dans une salle de classe. Vous pouvez accéder à vos vidéos de cours, lectures et devoirs en tout temps et en tout lieu, par l'intermédiaire du Web ou de votre appareil mobile.
Quelle est la durée nécessaire pour terminer la Spécialisation ?
Time to completion will vary based on your schedule, but we anticipate most learners being able to finish the material in 4 months.
What background knowledge is necessary?
No specific background is required—this Specialization is ideal for learners who might be interested in entering the dynamic world of data and business analysis, and/or is interested gaining deeper technical knowledge in Finance and Quantitative Modeling
Do I need to take the courses in a specific order?
No, you can take the courses in this Specialization in any order.
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
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.
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.
