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# Introduction to R for Finance

4.9+
11 reviews
Beginner

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

4 hours14 videos61 exercises

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## Course Description

In this finance-oriented introduction to R, you will learn essential data structures such as lists and data frames and have the chance to apply that knowledge to real-world financial examples. By the end of the course, you will be comfortable with the basics of manipulating your data to perform financial analysis in R.

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1. 1

### The Basics

Free

Get comfortable with the very basics of R and learn how to use it as a calculator. Also, create your first variables in R and explore some of the base data types such as numerics and characters.

Play Chapter Now
Welcome to Introduction to R for Finance!
50 xp
100 xp
Arithmetic in R (1)
100 xp
Arithmetic in R (2)
50 xp
Assignment and variables (1)
100 xp
Assignment and variables (2)
100 xp
Financial returns
50 xp
Financial returns (1)
100 xp
Financial returns (2)
100 xp
Basic data types
50 xp
Data type exploration
100 xp
What's that data type?
50 xp
2. 2

### Vectors and Matrices

In this chapter, you will learn all about vectors and matrices using historical stock prices for companies like Apple and IBM. You will then be able to feel confident creating, naming, manipulating, and selecting from vectors and matrices.

3. 3

### Data Frames

Arguably the most important data structure in R, the data frame is what most of your data will take the form of. It combines the structure of a matrix with the flexibility of having different types of data in each column.

4. 4

### Factors

Questions with answers that fall into a limited number of categories can be classified as factors. In this chapter, you will use bond credit ratings to learn all about creating, ordering, and subsetting factors.

5. 5

### Lists

Wouldn't it be nice if there was a way to hold related vectors, matrices, or data frames together in R? In this final chapter, you will explore lists and many of their interesting features by building a small portfolio of stocks.

### In the following Tracks

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#### Quantitative Analyst with R

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collaborators

Lore Dirick

Director of Data Science Education at Flatiron School

Lore is a data scientist with expertise in applied finance. She obtained her PhD in Business Economics and Statistics at KU Leuven, Belgium. During her PhD, she collaborated with several banks working on advanced methods for the analysis of credit risk data. Lore formerly worked as a Data Science Curriculum Lead at DataCamp, and is and is now Director of Data Science Education at Flatiron School, a coding school with branches in 8 cities and online programs.
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## Don’t just take our word for it

*4.9
from 11 reviews
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• Thashalak A.
7 days

Great course, Lore is a great instructor. Datacamp should keep her to be a main teacher.

• Lily T.
5 months

Well-structured course and easy to follow for beginners to familiarize with the terminologies but also w/ the science behind them.

• Alexander B.
7 months

Good content. Super teacher.

• Weixin W.
10 months

I liked the course. It gave me a chance to learn R from a different angle, especially in understanding some R programming concept.

• David E.

Lore is amazing and I have a mad crush on her. She explains things clearly without being pedantic and is always linking the skills being taught with the real-life applications.

"Great course, Lore is a great instructor. Datacamp should keep her to be a main teacher."

Thashalak A.

"Well-structured course and easy to follow for beginners to familiarize with the terminologies but also w/ the science behind them."

Lily T.

"Good content. Super teacher."

Alexander B.