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Python for Finance Course

3 Mins read
Python for Finance Courses

Python is gaining its popularity over all the other programming languages. The aspiring learners are gradually seen to incline towards learning Python. The reason for this change is that Python has the best quality of readability. It resembles the known language of English and that is why easy to catch up, unlike other languages that are difficult to learn. If you are willing to learn Python for Finance to build your portfolio, then here is the list of Best Python for Finance Courses for Beginners to Expert levels.

A python is a form of scripting language. It will automate all of your tasks. It is very important to learn a programing language so that it is helpful in managing the Finances. Thus some of the Python Courses are well curated to provide help in Financial matters.

Top 5 Python for Finance Courses

Below given are the 4 best Python Courses for Finance:

1. Python for Finance Course by Yoda Learning Solutions

It is the best course to date and that is why I have kept it in the top of my list. This course is curated and designed for all those who have a Finance background and need to learn coding to make their life easier by automating certain tasks. The following are the topics that are covered in this course:

  • Basics of Python programming
  • Use of Numpy for arrays and statistics
  • Pandas for data handling and preprocessing
  • Matplotlib to create beautiful visualizations of your data
  • Prediction on your data using Scikit-learn
  • Implementing whatever you have learned in 2 Finance Projects

Where is Python used in the Finance Industry

Duration: 4 weeks, 3-4 hours/week

Rating: 4.5 out of 5

You can Sign up Here

2. Python for Finance Investments Fundamentals by Udemy

This is one of the best sellers and popular courses in Finance professionals. It is a well-constructed course for all who want to learn the programming using Python and conduct the financial analysis using Python.  It covers all the following topics:

  • Learn basic code in Python
  • Conditional statements, functions, sequences, and loops
  • Scientific packages, like NumPy
  • Data analysis toolkit, Pandas
  • Get a job as a data scientist with Python
  • Carry out in-depth investment analysis
  • Build investment portfolios
  • Calculate the risk and return of individual securities
  • Calculate risk and return of investment portfolios
  • Use univariate and multivariate regression analysis
  • Capital Asset Pricing Model
  • Compare securities in terms of their Sharpe ratio
  • Perform Monte Carlo simulations
  • Black Scholes formula

Duration: 9-10 hours

Rating: 4.5 out of 5

You can Sign up Here

3. Introduction to Python for Finance by DataCamp

This course especially focuses on the basic python for financial analysis. The course structure follows the basics of Python and then gradually moves to the topics that are important for financial analysts. The following are the topics included in this course:

  • Basic of Python
  • Variables and Datatypes in Python
  • Creating lists
  • Slicing, Indexing, nested lists
  • StockUp, subset lists
  • List method & functions
  • Finding Stocks with Maximum price
  • Calculating Array Stacks
  • Using Arrays for Analysis
  • Visualization in Python
  • Importing Matplotlib & polyplot
  • Scatterplots, Histograms
  • Visual Applications in Finance

Duration: 8-9 hours

Rating: 4.5 out of 5

You can Sign up Here

4. Python for Statistics & Financial Analysis by Coursera

This course is best for gaining skills like statistical analysis, Financial analysis, Financial Data Analysis, Python Programing and data visualization. In short this is a full packed version of learning Python. The following topics you will be learning in this course:

  • Module Introduction
  • Packages for Data Analysis
  • Importing data
  • Basics of Dataframe
  • Generate new variables in Dataframe
  • Trading Strategy
  • Outcomes and Random Variables
  • Frequency and Distributions
  • Models of Distribution
  • Population and Sample
  • Variation of Sample
  • Confidence Interval
  • Hypothesis Testing
  • Association of random variables
  • Simple linear regression model
  • Diagnostic of linear regression model
  • Multiple linear regression model
  • Evaluate the strategy

Duration: 4 weeks, 3-4 hours/week

Rating: 4.5 out of 5

You can Sign up Here


The above given is the detailed explanation of the courses offered by different online portals. You can choose which course suited best for you by looking at the topics covered by each and every course. It is time to learn Python.

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