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Python for Finance
Section 01: Introduction
Course Overview (4:22)
Why Python for Finance? (8:01)
Why Spyder for Python? (4:16)
Environment Setup
Feedback 01 | Python for Finance
Section 02: Python Basics
Python Introduction (2:38)
Data Types (8:54)
Functions (4:15)
Conditions Loops (6:57)
Python Assignment
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Section 03: Numpy
What is Numpy? (2:38)
How To Install Python Libraries? (3:23)
Arrays (4:26)
Indexing and Operations (6:40)
Numpy Assignment
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Section 04: Pandas Data Handling
What is Pandas? (4:50)
Series (3:38)
Dataframe (5:13)
Moving Average (5:14)
Pandas Assignment
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Section 05: Matplotlib Visual Analysis
What is Matplotlib? (3:09)
Types of Plots (3:30)
Creating Plots for Python - Part 1 (5:37)
Creating Plots for Python - Part 2 (6:54)
Matplotlib Assignment
Seaborn (3:04)
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Section 06: Scikit-learn Prediction
What is Scikit-learn? (2:26)
Types of Models (3:27)
Prediction Models (3:07)
What is Regression in Finance? (2:22)
Linear Regression (2:33)
Prediction - Data Preprocessing (4:47)
Prediction - Regression (4:56)
Scikit-learn Assignment
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Section 07: S&P-500 Price Prediction
Overview (2:55)
S&P 500 Stock Price Prediction
Data Processing (2:01)
Prediction Part 1 (3:45)
Prediction Part 2 (2:40)
Project Solution
Feedback 07 | Python for Finance
Section 08: Risk Analysis of Credit Card Defaulter
Introduction (3:16)
Risk Analysis of Credit Card Defaulter
Data Processing (3:36)
Prediction (5:24)
Credit Card Defaulter Project Solution
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Section 09: Bonus Resources
Applications in Industry (4:03)
Guide to Resources (2:27)
Tutorial Links
Dataset Links
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Section 10: Conclusion
Conclusion (2:06)
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