The ‘Python for Finance: Investment Fundamentals and Data Analytics Course’ is a beginner-friendly program that covers the basics of Python, financial calculations & investment portfolios. The course covers the practical skills that are required in the field of finance, including the stock market, calculations of risk and returns, the Black-Scholes formula, and more.

The course follows a practical approach, the students will learn the theoretical concepts before putting them into practice. The course is usually available for INR 5,200 on Udemy but students can click on the link and get the ‘Python for Finance: Investment Fundamentals and Data Analytics Course’ for INR 649.

Who all can opt for this course?

  • Aspiring Data Scientists
  • Aspiring Programmers
  • Those with an interest in investments and finance
  • Programmers who want to focus on the financial industry
  • Anyone who wishes to learn how to code and put their knowledge to use
  • Graduates and professionals in finance who need to use their Python skills more effectively

Course Highlights

Key HighlightsDetails
Registration LinkApply Now!
PriceINR 649 (INR 5,20088% off
Duration09 hours
Student Enrollment1,23,968 students
Instructor365 Careers
Topics CoveredPython programming, Python variables, data types, basic Python syntax, conditional statements, functions, etc.
Course LevelBeginner
Total Student Reviews25,811

Learning Outcomes

  • Learn Python coding
  • Learn how to the loops, functions, sequences, and conditional statements available in Python
  • Learn how to use NumPy
  • Know how to use the Pandas data analysis toolbox
  • Learn how to use Matplotlib to plot graphs
  • Use Python to do practical tasks
  • Get a job as a data scientist who can work with Python
  • Do a thorough investment analysis
  • Build investment portfolios
  • Determine the return and risk of investment portfolios
  • Know the best practices to follow while working with financial data
  • Employ regression analysis with one and more variables
  • Using the Black Scholes method to price options will teach you how to do it

Course Content

S.No.Module (Duration)Topics
1.Welcome! Course Introduction (08 minutes)What Does the Course Cover?
Download Useful Resources – Exercises and Solutions
2.Introduction to programming with Python (33 minutes)Programming Explained in 5 Minutes
Programming Explained in 5 Minutes
Why Python?
Why Python?
Why Jupyter?
Why Jupyter?
Installing Python and Jupyter
Jupyter’s Interface – the Dashboard
Jupyter’s Interface – Prerequisites for Coding
Jupyter’s Interface
Python 2 vs Python 3: What’s the Difference?
3.Python Variables and Data Types (14 minutes)Variables
Numbers and Boolean Values
Numbers and Boolean Values
4.Basic Python Syntax (11 minutes)Arithmetic Operators
Arithmetic Operators
The Double Equality Sign
The Double Equality Sign
Reassign Values
Reassign values
Add Comments
Add Comments
Line Continuation
Indexing Elements
Indexing Elements
Structure Your Code with Indentation
Structure Your Code with Indentation
5.Python Operators Continued (07 minutes)Comparison Operators
Comparison Operators
Logical and Identity Operators
Logical and Identity Operators
6.Conditional Statements (13 minutes)Introduction to the IF statement
Introduction to the IF statement
Add an ELSE statement
Else if, for Brief – ELIF
A Note on Boolean Values
A Note on Boolean Values
7.Python Functions (18 minutes)Defining a Function in Python
Creating a Function with a Parameter
Another Way to Define a Function
Another Way to Define a Function
Using a Function in another Function
Combining Conditional Statements and Functions
Creating Functions Containing a Few Arguments
Notable Built-in Functions in Python
8.Python Sequences (19 minutes)Lists
Using Methods
Using Methods
List Slicing
9.Using Iterations in Python (17 minutes)For Loops
For Loops
While Loops and Incrementing
Create Lists with the range() Function
Create Lists with the range() Function
Use Conditional Statements and Loops Together
All In – Conditional Statements, Functions, and Loops
Iterating over Dictionaries
10.Advanced Python tools (01 hour 04 minutes)Object Oriented Programming
Object Oriented Programming – Quiz
Modules and Packages
Modules – Quiz
The Standard Library
The Standard Library – Quiz
Importing Modules
Importing Modules – Quiz
Must-have packages for Finance and Data Science
Must-have packages – Quiz
Working with arrays
Generating Random Numbers
A Note on Using Financial Data in Python
Sources of Financial Data
Accessing the Notebook Files
Importing and Organizing Data in Python – part I
Importing and Organizing Data in Python – part II.A
Importing and Organizing Data in Python – part II.B
Importing and Organizing Data in Python – part III
Changing the Index of Your Time-Series Data
Restarting the Jupyter Kernel
11.PART II FINANCE: Calculating and Comparing Rates of Return in Python (42 minutes)Considering both risk and return
Risk and return – Quiz
What are we going to see next?
Calculating a security’s rate of return
Calculating a security’s rate of return
Calculating a Security’s Rate of Return in Python – Simple Returns – Part I
Calculating a Security’s Rate of Return in Python – Simple Returns – Part II
Calculating a Security’s Return in Python – Logarithmic Returns
What is a portfolio of securities and how to calculate its rate of return
What is a portfolio of securities and how to calculate its rate of return – Quiz
Calculating a Portfolio of Securities’ Rate of Return
Popular stock indices that can help us understand financial markets
Which of the following is not an index? – Quiz
Calculating the Indices’ Rate of Return
12.PART II Finance: Measuring Investment Risk (41 minutes)How do we measure a security’s risk?
Which of the following sentences is true? – Quiz
Calculating a Security’s Risk in Python
The benefits of portfolio diversification
Investing in stocks – Quiz
Calculating the covariance between securities
Covariance – Quiz
Measuring the correlation between stocks
Correlation – Quiz
Calculating Covariance and Correlation
Considering the risk of multiple securities in a portfolio
Calculating Portfolio Risk
Understanding Systematic vs. Idiosyncratic risk
Diversifiable Risk – Quiz
Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio
13.PART II Finance – Using Regressions for Financial Analysis (21 minutes)The fundamentals of simple regression analysis
Regressions – Quiz
Running a Regression in Python
Are all regressions created equal? Learning how to distinguish good regressions
Regressions – Quiz
Computing Alpha, Beta, and R Squared in Python
14.PART II Finance – Markowitz Portfolio Optimization (19 minutes)Markowitz Portfolio Theory – One of the main pillars of modern Finance
Markowitz – Quiz
Obtaining the Efficient Frontier in Python – Part I
Obtaining the Efficient Frontier in Python – Part II
Obtaining the Efficient Frontier in Python – Part III
15.Part II Finance – The Capital Asset Pricing Model (27 minutes)The intuition behind the Capital Asset Pricing Model (CAPM)
CAPM – Quiz
Understanding and calculating a security’s Beta
Beta – Quiz
Calculating the Beta of a Stock
The CAPM formula
CAPM – Quiz
Calculating the Expected Return of a Stock (CAPM)
Introducing the Sharpe ratio and how to put it into practice
Sharpe ratios – Quiz
Obtaining the Sharpe ratio in Python
Measuring alpha and verifying how good (or bad) a portfolio manager is doing
Alpha – Quiz
16.Part II Finance: Multivariate regression analysis (12 minutes)Multivariate regression analysis – a valuable tool for finance practitioners
Multivariate Regressions – Quiz
Running a multivariate regression in Python
17.PART II Finance – Monte Carlo simulations as a decision-making tool (56 minutes)The essence of Monte Carlo simulations
Monte Carlo – Quiz
Monte Carlo applied in a Corporate Finance context
Monte Carlo in Corporate Finance – Quiz
Monte Carlo: Predicting Gross Profit – Part I
Monte Carlo: Predicting Gross Profit – Part II
Forecasting Stock Prices with a Monte Carlo Simulation
Monte Carlo Simulations – Quiz
Monte Carlo: Forecasting Stock Prices – Part I
Monte Carlo: Forecasting Stock Prices – Part II
Monte Carlo: Forecasting Stock Prices – Part III
An Introduction to Derivative Contracts
Derivatives – Quiz
The Black Scholes Formula for Option Pricing
Monte Carlo: Black-Scholes-Merton
Using Monte Carlo with Black-Scholes-Merton – Quiz
Monte Carlo: Euler Discretization – Part I
Monte Carlo: Euler Discretization – Part II
18.APPENDIX – pandas Fundamentals (58 minutes)pandas Series – Introduction
pandas – Working with Methods – Part I
pandas – Working with Methods – Part II
pandas – Using Parameters and Arguments
pandas Series – .unique() and .nunique()
pandas Series – .sort_values()
pandas DataFrames – Introduction – Part I
pandas DataFrames – Introduction – Part II
pandas DataFrames – Common Attributes
pandas DataFrames – Data Selection
pandas DataFrames – Data Selection with .iloc[]
pandas DataFrames – Data Selection with .loc[]
19.APPENDIX – Technical Analysis (36 minutes)Technical Analysis – Principles, Applications, Assumptions
Charts Used in Technical Analysis
Other Tools Used in Technical Analysis
Trend, Support and Resistance Lines
Common Chart Patterns
Price Indicators
Momentum Oscillators
Non-price Based Indicators
Technical Analysis – Cycles
Intermarket Analysis
20.BONUS LECTURE (36 seconds)Bonus Lecture: Next Steps

Resources Required

The program requires Anaconda software. The instructor will teach how to install it.

Featured Review

Pedro Carlos Rosa Bom (5/5): It is without a doubt an excellent course, but some aspects have changed over the years. I believe the platform should notify users of these changes. For example, some codes no longer work.


  • Ritwik Dhande (5/5): This is one of the best course for computer science students who want to switch their career in a finance field
  • David N Ngana (5/5): The perfect course to become a Data Analyst in Finance Field.
  • Keng-Wei Hsu (5/5): This course is excellent!! It is recommended to those who don’t have any Python experience.
  • Soh Say Kiong (4/5): Best take away for me in this section is applying Monte Carlo Simulation to for stock call options pricing.


  • Nilaj Chakrabarty (1/5): The material is widely variable in terms of difficulty, the quizzes are basically worthless and the exercise notebooks are too simplistic.
  • April G (1/5): There were changes made to the API’s used in this course that not makes this course outdated.
  • Paul Mrockowski (2/5): Quizzes are worthless: one question, usually so basic that doesn’t prove knowledge or lack of knowledge of anything.
  • Jitendra Tolani (2/5): Highly disappointed, if something so crucial to the course in not being addressed, why did I pay the money for it?

About the Author

The course is created by 365 careers. 365 careers are top-rated instructors on Udemy with an average 4.6 instructor rating and 6,60,994 reviews on Udemy. They have taught 22,95,331 students so far.

  • On Udemy, 365 Careers is the top-selling provider of courses in business, finance, and data science.
  • In 210 different countries, more than 2,000,000 students have taken the company’s courses.
  • Individuals who have finished 365 Careers training now work at renowned companies like Apple, PayPal, and Citibank.
  • In Udemy right now, 365 focuses on the following subjects: Finance, Data Science, Business Strategy, Office Productivity, and Business Blockchain.
  • Every one of our courses is pre-scripted, practical, laser-focused, interesting, and tested in real-world situations.
  • By selecting 365 Careers, you can be certain that you will learn from seasoned professionals who are passionate about sharing their knowledge and will help you go from a beginner to a pro in the shortest amount of time.
  • The courses offered by 365 Careers are the ideal place to start whether you want to work as a financial analyst, data scientist, business analyst, data analyst, business intelligence analyst, business executive, finance manager, FP&A analyst, investment banker, or entrepreneur.

Comparison Table

ParametersPython for Finance: Investment Fundamentals & Data AnalyticsIntroduction to Finance, Accounting, Modeling and ValuationThe Complete Financial Analyst Training & Investing Course
OffersINR 649 (INR 5,20088% offINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% off
Duration9 hours4.5 hours23.5 hours
Rating4.5/54.5 /54.6 /5
Student Enrollments1,23,961189,894247,283
Instructors365 CareersChris HarounChris Haroun
Register HereApply Now!Apply Now!Apply Now!

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