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The syllabus
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The syllabus
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Home
Udemy
Courses
Python for Finance Financial Analysis for Investing
Python for Finance: Financial Analysis for Investing
BY
Udemy
Brochure
Enquire
Online
₹ 449
3499
Quick Facts
particular
details
Medium of instructions
English
Mode of learning
Self study
Mode of Delivery
Video and Text Based
Course and certificate fees
Fees information
₹ 449
₹3,499
certificate availability
Yes
certificate providing authority
Udemy
The syllabus
Introduction
One Question
Get the most out of this course
Setup
Introduction
Download Anaconda (includes Python and Jupyter notebook)
Resources and setup environment in Jupyter notebook
Prompt rating
Jupyter Notebook guide
Introduction
Jupyter Notebook Cheat Sheet.
Jupyter Notebook: The Dashboard
Jupyter Notebook: Run and restart a Notebook
Jupyter Notebook: Copy and reorganize code
Jupyter Notebook: Comment and markdown
Jupyter Notebook: Tab + Tab + Shift & Tab
What did we learn?
Python Crash Course
Introduction
Variables and types
The print statement
Boolean expressions
If statements
Python lists
For-loops
While loops
Python Dictionaries (dict)
Other types
Functions
Lambda functions
Exercises
Solutions
New to Python? We have all been there
What did we learn?
Lemonade Stand
Introduction
Intrinsic Value
Introduction to the Lemonade Stand
The Lemonade Stand - the easy to understand example
Jupyter Notebook: The Lemonade Stand
Shares
Shares a story - Understand what they really are
Jupyter Notebook: Shares
Dividend
Dividend a story - an easy way to understand them
Jupyter Notebook: Dividend
What did we learn?
Pandas
Introduction
Introduction to Pandas - a small demonstration
Series
DataFrames - Part I
DataFrames - Part II
DataFrames - Part III
DataFrames - Part IV
DataFrames - Part V
Read and Write with Pandas - Part I
Read and Write with Pandas - Part II
Read and Write with Pandas - Part III
Merge - Join - Concatenate - Part I
Merge - Join - Concatenate - Part II
Transpose and clean data
Views
Useful methods to know
Apply - an awesome method to master
Exercises
Solutions
What did we learn?
Intrinsic Value
Introduction
Outcome of section
Understand Risk - Part I
Understand Risk - Part II
Understand Rik - Part III
Understand Risk - All put together
Evaluate Leadership
Debt-to-Equity ration - Evaluation
Jupyter Notebook: Debt-to-Equity ratio
Current ratio - Evaluation
Jupyter Notebook - Current ratio
Stable and predictable
Return of Investment (ROI) - Evaluation
Jupyter Notebook: Return of Investment
Revenue - Evaluation
Jupyter Notebook: Revenue
Earnings Per Share (EPS) - Evaluation
Jupyter Notebook: Earnings Per Share (EPS)
Book Value - Evaluation
Jupyter Notebook: Book Value
Free Cash Flow (FCF) - Evaluation
Jupyter Notebook: Free Cash Flow (FCF)
Combine All Data
Jupyter Notebook: Combine All Data
Calculate a Fair Price (Intrinsic Value)
Price-to-Earnings (PE) ratio
Jupyter Notebook: Price-to-Earnings (PE) ratio
Jupyter Notebook: Calculate a Fair Price (Intrinsic Value)
Compare it with Current Price
What did we learn?
Matplotlib
Introduction
Overview of section
Jupyter Notebook: Matplotlib basics
Jupyter Notebook: Work with Axis
Jupyter Notebook: Title and Labels
Jupyter Notebook: Matplotlib and Pandas
Jupyter Notebook: Pandas and data structures
Jupyter Notebook: Bar plots
Exercises
Solutions
What did we learn?
Visualization and Excel Export of Financial Data
Introduction
Matplotlib - Part I
Matplotlib - Part II
Export to Excel - Part I
Export to Excel - Part II
Export to Excel - Part III
What did we learn?
Data Sources
Introduction
What will we learn?
Pandas Datareader - Remote Data Access for Pandas
Jupyter Notebook: Pandas Datareader - Part I
Jupyter Notebook: Pandas Datareader - Part II
The Yahoo! Finance API - read Financial Statements
Jupyter Notebook: Yahoo! Finance - Financial Statements
Web Scraping
Jupyter Notebook: Web Scraping
Exercises
Solutions
What did we learn?
Time Series Data
Introduction
Rate of Return, Percentage Change, and Normalization
Jupyter Notebook: Rate of Return, Percentage Change, and Normalization
CAGR
Jupyter Notebook: CAGR
Jupyter Notebook: Multiple Time Frames
Case Study: DOW Theory
Jupyter Notebook: Case Study: DOW Theory
What did we learn?
Technical Indicators
Introduction
What is a Technical Indicator and Types of Indicators
Indicator: Moving Average
Jupyter Notebook: Simple Moving Average (MA)
Jupyter Notebook: Exponential Moving Average (EMA)
Indicator: MACD
Jupyter Notebook: MACD
Indicator: Stochastic Oscillator
Jupyter Notebook: Stochastic Oscillator
Jupyter Notebook: Exporting to Excel
Jupyter Notebook: Using our Excel Sheet
Exercises
Solutions
What did we learn?
NumPy
Introduction
Jupyter Notebook: Introduction to NumPy
Jupyter Notebook: Index, Slicing, and Views
Jupyter Notebook: DataFrames and Series with NumPy
Jupyter Notebook: Vectorization with NumPy
Jupyter Notebook: Matplotlib and NumPy
Jupyter Notebook: Dot product and Transpose
Exercises
Solutions
What did we learn?
Correlation and Linear Regression
Introduction
Adjusted Close
Volatility of a Stock
Jupyter Notebook: Volatility Calculations
Correlation Between Securities
Jupyter Notebook: Correlation Calculations
Linear Regression
Jupyter Notebook: Linear Regression
Beta
Jupyter Notebook: Beta Calculations
CAPM
Jupyter Notebook: CAPM Calculations
Exercises
Solutions
What did we learn?
Working with Portfolios and Monte Carlo Simulations
Introduction
Portfolios
Jupyter Notebook: Portfolio
Sharpe Ratio
Jupyter Notebook: Sharpe Ratio Calculations
Monte Carlo Simulations
Jupyter Notebook: Monte Carlo Simulations - Introduction
Jupyter Notebook: Portfolios and Monte Carlo Simulations
Jupyter Notebook: The Efficient Frontier
Exercises
Solutions
What did we learn?
Finish Line
Introduction
3 Books to Read
Goodbye
Articles
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