Course Financial Analytics in R

Learn how to speak the language (and do the math!) of corporate finance to pitch your next great business idea.

DescriptionChaptersExercisesInstructor

This online course about Financial Analytics in R covers a key part of what a future data analyst would require.

This course is an introduction to the world of finance where cash is king and time is money. In this course, you will learn how to use R to quantify the value of projects, opportunities, and actions and drive decision-making. Students will use the R language to explore cashflow statements, compute profitability metrics, apply decision rules, and compare alternatives. You will end this case-motivated course with an understanding of key financial concepts and the skills needed to conceptualize an communicate the value of you or your teams’ projects in a corporate setting.

Enroll now in this Financial Analytics in R course, and don’t miss the opportunity of learning with the best, as Emily Riederer is. With 59 enriching exercises, 17 videos, and an estimated time of 4 hours to successfully end up the course, you will become one of the best.

Chapter 1: Cash is King (Intro to Valuations)
Introducing the motivation for and basic concepts of discounted cashflow valuations analysis.
Chapter 2: Time is Money (Key Financial Concepts)
An overview of time-value of money and related concepts.
Chapter 3: Prioritizing Profitability (Financial Metrics)
Understanding different ways to summarize cashflow output.
Chapter 4: Understanding Outcomes
Piecing it altogether with sensitivty and scenario analysis.
Chapter 5:
Financial Analytics in R. Learn how to speak the language (and do the math!) of corporate finance to pitch your next great business idea.

Emily Riederer

Analytics Manager

Emily Riederer is an Analytics Manager at Capital One. She is passionate about incorporating coding best practices and reproducible methods into standard business analysis workflows. Previously, she studied at the University of North Carolina at Chapel Hill where she worked in a healthcare operations research group. You can find her on Twitter at @emilyriederer.

Collaborators

#R #Python #MachineLearning #BigData #DataAnalysis