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Complete Python and Machine Learning in Financial Analysis (Udemy.com)

Using Python, Machine Learning, and Deep Learning in Financial Analysis with step-by-step coding (with all codes)

4.5
580 reviews

Created by: S. Emadedin Hashemi

Last updated February 2026

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What you will learn

  • You will be able to use the functions provided to download financial data from a number of sources and preprocess it for further analysis
  • You will be able to draw some insights into patterns emerging from a selection of the most commonly used metrics (such as MACD and RSI)
  • Introduces the basics of time series modeling. Then, we look at exponential smoothing methods and ARIMA class models.
  • shows you how to estimate various factor models in Python. one ,three-, four-, and five-factor models.
  • Introduces you to the concept of volatility forecasting using (G)ARCH class models, how to choose the best-fitting model, and how to interpret your results.
  • Introduces concept of Monte Carlo simulations and use them for simulating stock prices, the valuation of European/American options and calculating the VaR.

How it compares

Against the other 388 rated Udemy courses in Python on CourseDuck:

  • Rating4.5 out of 5higher than 52% of them
  • Reviews580#231 of 389 by number of reviews
  • Length20.3 hourslonger than 77% of them
  • Last updatedFebruary 2026more recently than 81% of them

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Course Description

In this course, you will become familiar with a variety of up-to-date financial analysis content, as well as algorithms techniques of machine learning in the Python environment, where you can perform highly specialized financial analysis. You will get acquainted with technical and fundamental analysis and you will use different tools for your analysis. You will learn the Python environment completely. You will also learn deep learning algorithms and artificial neural networks that can greatly enhance your financial analysis skills and expertise.

This tutorial begins by exploring various ways of downloading financial data and preparing it for modeling. We check the basic statistical properties of asset prices and returns, and investigate the existence of so-called stylized facts. We then calculate popular indicators used in technical analysis (such as Bollinger Bands, Moving Average Convergence Divergence (MACD), and Relative Strength Index (RSI)) and backtest automatic trading strategies built on their basis.

The next section introduces time series analysis and explores popular models such as exponential smoothing, AutoRegressive Integrated Moving Average (ARIMA), and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (including multivariate specifications). We also introduce you to factor models, including the famous Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model. We end this section by demonstrating different ways to optimize asset allocation, and we use Monte Carlo simulations for tasks such as calculating the price of American options or estimating the Value at Risk (VaR).

In the last part of the course, we carry out an entire data science project in the financial domain. We approach credit card fraud/default problems using advanced classifiers such as random forest, XGBoost, LightGBM, stacked models, and many more. We also tune the hyperparameters of the models (including Bayesian optimization) and handle class imbalance. We conclude the book by demonstrating how deep learning (using PyTorch) can solve numerous financial problems.
Read More All Levels All Levels product length iconTime: 20.3h

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Instructor Details

S. Emadedin Hashemi

S. Emadedin Hashemi is an instructor and researcher in the fields of Artificial Intelligence, Data Science, and Data Analytics. He has academic teaching experience at the university level and a strong professional background across various industries, where he has led and contributed to multiple real-world AI projects. His work is driven by a practical, problem-oriented approach, focusing on translating complex AI and data-driven concepts into effective solutions for business and industry applications.

As a Udemy instructor, he has taught over 100,000 students worldwide through carefully designed courses that emphasize deep understanding, hands-on skills, and real project readiness. Alongside teaching, he actively publishes academic research and continues his scholarly work in artificial intelligence and data science, maintaining a strong connection between theory, practice, and continuous learning.

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Reviews

4.5

580 ratings on Udemy

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By Mata Saldon on 8/27/2023

I like this course because it is complete and perfect. I suggest that you definitely get it. Python coding is very simple and understandable. You can also learn to use machine learning and deep learning.

By Callum Thomas Hurd on 8/26/2023

although there is a lot of content, there was quite a lot of redoing the same parts, and the actual speed the videos should be watched at is 1.5x speed as they have been slowed to increase the length of the course. the actual content the course covers is informative and it is quite frankly what it says on the tin, however it could have been half the length

By Somsak on 8/19/2023

Data analysis with machine learning, this is the best gift to me. I use this course to analyze the market situation and predict it. I have also learned Python at the same time. This course is a masterpiece.

By Elika moora on 5/28/2023

I have recently started working in financial and trading markets. I use this course a lot. I use its prediction methods. It is a very good and scientific course. In addition, I am well trained in the Python programming language.

By Emmie Hewitte on 4/22/2023

The best course for financial analysis with Python. It draws all the indicators with Python and teaches you how to analyze and predict your financial issues. I like this course

By Jennifer Herring on 11/6/2022

The topics are complete and learning is step by step. I suggest you provide it in other related courses. Today, financial analysis is very important for people who have financial transactions and investments. In this course, I learned financial analysis using various tools. Thank you.

By Daniel on 8/27/2022

Many topics are taught with examples. People who didn't suggest it didn't watch it all the way through. The further it goes, the more interesting it becomes and you learn more topics. I'm glad I found this course and I'm using it.

By Adriano on 8/26/2022

I suggest you buy this course! It is very comprehensive and you will learn a lot from it. All the files are at your disposal, which you can use in your personal projects.

By Michael on 8/26/2022

If you work in financial matters, be sure to buy this course. It teaches all the tools and indicators needed for financial analysis. I have reviewed many courses for financial analysis, this is one of the best.

By Ariel Gimenez on 3/18/2022

The codes provided do not work and there is lack of description about the steps to install some of the libraries. The codes used are not well described and it's hard to follow them.

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Overall Score : 90 / 100

Complete Python and Machine Learning in Financial Analysis
Visit course on Udemy Write a review
  • Video Duration: icon 20.3h
  • Price: $64.99
  • Provider: icon Udemy
  • Updated: icon February 2026
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
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