Financial Engineering and Artificial Intelligence in Python — 90% OFF Discount Coupon

Financial Analysis, Time Series Analysis, Portfolio Optimization, CAPM, Algorithmic Trading, Q-Learning, and MORE!

★4.8 out of 5
12,186 students
Created by Lazy Programmer Team, Lazy Programmer Inc.
English
Updated December 2025

Quick Facts — Course Summary

Here's a quick overview of everything you need to know about Financial Engineering and Artificial Intelligence in Python before you enroll:

•Course Name: Financial Engineering and Artificial Intelligence in Python
•Platform: Udemy
•Instructor: Lazy Programmer Team, Lazy Programmer Inc.
•Coupon Last Verified: December 28, 2025
•Level: All Levels
•Topic: Development
•Subtopic: Financial Analysis
•Total Time: 22h 30m of video content
•Language: English
•Access Type: Unlimited lifetime access + updates
•Certificate: Included upon completion from Udemy
•Main Skills: Forecasting stock prices and stock returns · Time series analysis · Holt-Winters exponential smoothing model
•Requirements: Decent Python coding skills · Numpy, Matplotlib, Pandas, and Scipy (I teach this for free! My gift to the community)
•Current Price: $10.99 (was $109.99). You save $99.00 with 90% discount.
•How to Apply: Click the coupon button to activate your discount automatically
💡
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Skills You'll Master

By the end of Financial Engineering and Artificial Intelligence in Python, you'll have these practical skills:

✓Forecasting stock prices and stock returns.
✓Time series analysis.
✓Holt-Winters exponential smoothing model.
✓ARIMA.
✓Efficient Market Hypothesis.
✓Random Walk Hypothesis.
✓Exploratory data analysis.
✓Alpha and Beta.
✓Distributions and correlations of stock returns.
✓Modern portfolio theory.
✓Mean-Variance Optimization.
✓Efficient frontier, Sharpe ratio, Tangency portfolio.
✓CAPM (Capital Asset Pricing Model).
✓Q-Learning for Algorithmic Trading.

What You Need Before Starting

Before enrolling in Financial Engineering and Artificial Intelligence in Python, make sure you have:

•Decent Python coding skills
•Numpy, Matplotlib, Pandas, and Scipy (I teach this for free! My gift to the community)
•Matrix arithmetic
•Probability

About This Udemy Course

The following is the full official course description for Financial Engineering and Artificial Intelligence in Python as published on Udemy by instructor Lazy Programmer Team, Lazy Programmer Inc.:

Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering?
Today, you can stop imagining, and start doing.
This course will teach you the core fundamentals of financial engineering, with a machine learning twist.
We will cover must-know topics in financial engineering, such as:
  • Exploratory data analysis, significance testing, correlations, alpha and beta
  • Time series analysis, simple moving average, exponentially-weighted moving average
  • Holt-Winters exponential smoothing model
  • ARIMA and SARIMA
  • Efficient Market Hypothesis
  • Random Walk Hypothesis
  • Time series forecasting ("stock price prediction")
  • Modern portfolio theory
  • Efficient frontier / Markowitz bullet
  • Mean-variance optimization
  • Maximizing the Sharpe ratio
  • Convex optimization with Linear Programming and Quadratic Programming
  • Capital Asset Pricing Model (CAPM)
  • Algorithmic trading (VIP only)
  • Statistical Factor Models (VIP only)
  • Regime Detection with Hidden Markov Models (VIP only)
In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as:
  • Regression models
  • Classification models
  • Unsupervised learning
  • Reinforcement learning and Q-learning
***VIP-only sections (get it while it lasts!) ***
  • Algorithmic trading (trend-following, machine learning, and Q-learning-based strategies)
  • Statistical factor models
  • Regime detection and modeling volatility clustering with HMMs
We will learn about the greatest flub made in the past decade by marketers posing as "machine learning experts" who promise to teach unsuspecting students how to "predict stock prices with LSTMs". You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense. It is a lesson in how not to apply AI in finance.
As the author of ~30 courses in machine learning, deep learning, data science, and artificial intelligence, I couldn't help but wander into the vast and complex world of financial engineering.
This course is for anyone who loves finance or artificial intelligence, and especially if you love both!
Whether you are a student, a professional, or someone who wants to advance their career - this course is for you.
Thanks for reading, I will see you in class!
Suggested Prerequisites:
  • Matrix arithmetic
  • Probability
  • Decent Python coding skills
  • Numpy, Matplotlib, Scipy, and Pandas (I teach this for free, no excuses!)
WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:
  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)
UNIQUE FEATURES
  • Every line of code explained in detail - email me any time if you disagree
  • No wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratch
  • Not afraid of university-level math - get important details about algorithms that other courses leave out

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Is the Financial Engineering and Artificial Intelligence in Python Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.•Last updated: December 28, 2025.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Financial Engineering and Artificial Intelligence in Python is a high-value resource for learners seeking to build skills inDevelopment. Taught by Lazy Programmer Team, Lazy Programmer Inc. on Udemy, the 22h 30m course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 90%, from $109.99 to $10.99, removing the primary financial barrier to enrollment.

✓What We Like (Pros)

  • Verified 90% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.8 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 12,186 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in Financial Engineering and Artificial Intelligence in Python:

  • The depth of Development coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing
✓

Course Rating Summary

Financial Engineering and Artificial Intelligence in Python Course holds an aggregate rating of 4.8 out of 5 based on 12,186 student reviews on Udemy.

4.8
★★★★★
12,186 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy.

Instructor Profile

The following section provides background information on Lazy Programmer Team, Lazy Programmer Inc., the instructor responsible for creating and maintaining Financial Engineering and Artificial Intelligence in Python on Udemy.

Financial Engineering and Artificial Intelligence in Python is taught by Lazy Programmer Team, Lazy Programmer Inc., a Udemy instructor specializing in Development. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

•Instructor Name: Lazy Programmer Team, Lazy Programmer Inc.
•Subject Area: Development
•Teaching Approach: Practical, project-based instruction focused on real-world application of Development skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about Financial Engineering and Artificial Intelligence in Python, its coupon code, pricing, and enrollment process.

About the Author

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Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

⭐4.8/5 Rating
✓Trusted by 10K+ Students

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