new courses: Python for Finance & Network Analysis in R

We just launched Intro to Finance in Python and Network Analysis in R! Learn how to make data-driven financial decision using Python. In Network Analysis, you'll learn how to work with and visualize network data. [DataCamp]( New Courses [ ]( [Play Now]( [ ]( Network Analysis in R Taught by James Curley, Associate Professor at UT Austin In this course you'll learn how to work with and visualize network data. You'll use the igraph package to create networks from edgelists and adjacency matrices. You'll also learn how to plot networks and their attributes. [Start Learning]( [Intro to Financial Concepts using Python]( ) Intro to Financial Concepts using Python Taught by Dakota Wixom, Quantitative Analyst and Founder of QuantCourse.com Understanding the basic principles of finance is essential for making important financial decisions ranging from taking out a student loan to constructing an investment portfolio. You'll come out of this course understanding the time value of money, how to compare potential projects and how to make rational, data-driven financial decisions. [Start Learning]( ) Network Analysis in R: What You'll Learn Chapter 1: [Introduction to networks]( In this chapter, you will be introduced to fundamental concepts in social network analysis. You will learn how to use the igraph R package to explore and analyze social network data as well as learning how to visualize networks. Chapter 2: [Identifying important vertices in a network]( In this chapter you will learn about directed networks. You will also learn how to identify key relationships between vertices in a network as well as how to use these relationships to identify important or influential vertices. Chapter 3: [Characterizing network structures]( This module will show how to characterize global network structures and sub-structures. It will also introduce generating random network graphs. Chapter 4: [Identifying special relationships]( This chapter will further explore the partitioning of networks into sub-networks and determining which vertices are more highly related to one another than others. You will also develop visualization methods by creating three-dimensional visualizations. [Play Now]( Intro to Financial Concepts using Python: What You'll Learn Chapter 1: [The Time Value of Money]( ) Learn about fundamental financial concepts like the time value of money, growth and rate of return, discount factors, depreciation, and inflation. Chapter 2: [Making Data-Driven Financial Decisions]( ) In this chapter, you will act as the CEO of a company, making important data-driven financial decisions about projects and financing using measures such as IRR and NPV. Chapter 3: [Simulating a Mortgage Loan]( ) You just got married, and you're looking for a new home in Hoboken, New Jersey. You will build a mortgage payment simulator to estimate your mortgage payments and analyze different possible economic scenarios. Chapter 4: [Budgeting Application]( ) You just got a new job as a data scientist in San Francisco, and you're looking for an apartment. In this chapter, you'll be building your own budgeting application to plan out your financial future. [Play Now]( ) [DataCamp] [DataCamp]( DataCamp Inc. | 350 Fifth Avenue | Suite 7730 | New York, NY 10118 [Facebook] [Facebook]( [Twitter] [Twitter]( [LinkedIn] [LinkedIn]( [YouTube] [YouTube]( [Unsubscribe](