My Experience: Udacity AI(Artificial Intelligence) for Trading Review 2021

Marcus udacity ai for trading review

In this Udacity AI for Trading Nanodegree review, I will talk about my experience with Udacity how this nanodegree helped me master AI algorithms for trading.

Rating: 4 out of 5.

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About me and my motivation

I have degrees in biomedical engineering and have experience in working with few medical device startups.

I was always interested and wanted to gain more knowledge in hardware and technologies.

That’s why I always wanted to improve my programming skills, especially with Artificial Intelligence and machine learning.

I enrolled in Udacity AI for trading Nanodegree for this purpose and it has opened the door for various different careers and freelancing paths for me.

In this Udacity Artificial Intelligence for Trading Review, I will take you through the entire structure and significance of this course if you are planning to make a career in trading. Keep reading!

There are plenty of Udacity reviews online, but not many written by students who have successfully completed the Course.
So If you feel the article is honestly written, please do enroll in Udacity through the links in the article, I can earn some affiliate. It can help me to keep running this blog. 🙏🙏

About Udacity’s AI for Trading Nanodegree

Udacity Aritificail Intelligence for trading

To craft this course, Udacity partnered with WorldQuant and other industry professionals having experience with firms like JPMorgan and Morgan Stanley. 

“WorldQuant is committed to bringing opportunity to talent globally. This Nanodegree program is like a laser, it focuses exactly on what you need today to succeed,”  Igor Tulchinsky, CEO of WorldQuant.

So, talking about this AI for Trading Nanodegree, for the quality of the content received from the course, the price is justifiable.

One thing I can vouch about this Nanodegree is the detailed feedback I got from the project reviewers.

Enrolling and starting this Nanodegree as a student seems to be a bit expensive but when you compare it with regular tuitions, you will find that the price is reasonable.

At this moment, I have a full-time job and I am very likely to take another course from them. 

Also Read: What is Udacity Nanodegree and is it worth it?

Cost and Duration of Artificial Intelligence for Trading Nanodegree

Cost: $399/month

Duration: 6 Months

You get 6 months‘ access to this course where you need to spend at least 10hrs/week to complete the course on time. 

In case you are unable to complete the course within 6 months and require more time, you can opt for monthly prices later. 

I suggest spending more time on the course, at least 15hrs/week so that you can utilize more time practicing. 

The course will test your mettle and dedication to the program but in the end, it will be worth it. 

You can sign up here.

Check this out -> Udacity Artificial Intelligence(AI) Nanodegree Review 2021: Expand Your Knowledge Of AI

What are the pre-requisites for the course?

This being an advanced course requires a proper understanding of Python that includes basic data structure and basic NumPy.

So brush up on your concepts on Python as it will be used heavily during the course. 

Further, one must be known to statistics, linear algebra, and calculus. 

Summing up, you should be good at following topics 

  1. Python (basic data structure and basic NumPy)

 2. Linear Algebra (Linear combination, linear independence Matrix, Eigenvectors)

 3. Calculus (Derivatives, Integrals)

4. Statistics (Mean, median, mode, variance, standard deviation, T-test, p-value, statistical significance)

If you want to revise your knowledge of statistics ad algebra, I suggest looking at these free courses

If you are new to Python, I recommend taking any of these free Python course 

Now, let explore the syllabus part of the course in this Udacity AI for trading review.

Syllabus of Udacity’s AI for Trading Nanodegree

AI for trading udacity

About the Course and syllabus of this Udacity AI for trading, NanodegreeI liked the syllabus and the lessons and projects’ design from an easy to advance one. 

Lesson 1: Basic Quantitative Trading

This lesson will teach you many of the financial and institutional basics required for quantitative finance. You will also learn basic data processing and momentum strategies. 

Project: Trading with Momentum

This Trading with Momentum project was mainly for Data Analysis and utilizing Pandas for finding different Alpha Signals. 

Lesson 2: Advanced Quantitative Trading

Again in this lesson you will learn about Data analysis but in more depth and more thoroughly. You will first hint at predictive modeling with some regression models.

You will be dealt with outliers and filtering, especially in stock data’s for example companies being removed from exchanges, holidays, etc.

Also Read: Review of Udacity’s Data scientist nanodegree

Project: Breakout Strategy

In this project, you will start getting some real work and understanding that is required to deal with outliers, specifically weekends and holidays.

You will be able to learn the basics of mean reversion and pairs trading strategy.

Lesson 3: Stocks, Indices, and ETFs

This lesson is about Stocks, indices, and ETFs, in this lesson you will learn some of the intricacies and different forms of funds in the market.

This lesson is prepared to show how large funds and institutions handle their risk or rewards and balance their portfolio to not only make money but also to prevent losses. 

Portfolio optimization is one of the most important topics relevant to it and you will learn it more thoroughly.

Project: Smart Beta and Portfolio Optimization

In this project, you will utilize a strategy that is used to optimize your portfolio consisting of multiple assets.

You will benchmark the portfolio to an index,  and update the weights of the portfolio continuing to optimize based on updated returns. 

Lesson 4: Factor Investing and Alpha Research

In this lesson, you will dive deeper and learn how to not only find factors in the market but also see how the factors affiliated with your portfolio can affect the risk and reward.

You can analyze both alpha and risk factors quantitatively and create a risk-mitigating portfolio, in which the sole factors affecting portfolio performance will be the alpha factors.

Project: Alpha Research and Factor Modeling

In this project, you will be doing alpha research and factor modeling. As stated above, you will perform an advanced portfolio optimization based on both the risk factors and the alpha factors.

Lesson 5: Sentiment Analysis with Natural Language Processing

In this lesson, I was working on a sentiment analysis program with some colleagues. This lesson was very interesting for me and was beneficial for my personal projects.

In this lesson, you will learn very powerful strategies for sentiment analysis and text processing from sites like Twitter, StockTwits, etc., and on company documents or filings.

Project: Sentiment Analysis using NLP

In this Sentiment Analysis using the NLP project, you will perform NLP analysis on a big company with 10-k filings.

After that, you will obtain alpha factors based on the sentiment of the documents themselves.

Lesson 6: Advanced Natural Language Processing with Deep Learning

This lesson is Built off of the last lessons and was the first real hint of deep learning. In this lesson,

I have done a nice deep dive into deep learning and neural networks and how sentiment analysis and NLP can be incredibly powerful utilizing these methods.

As someone new to applying and implementing deep learning, this was the most powerful lesson. I felt that they explained and provided methods that can be applied in many niches.

Also Read: Review of Deep Learning Nanodegree

Project: Deep Neural Network with News Data

In this project, you will be using Advanced NLP using deep learning on tweets to gage sentiment on a company.

This project was very similar to a personal project, as stated, so using neural networks in this sense was very beneficial in improving my skillset.

Lesson7: Combining Multiple Signals

From this lesson onwards you will start learning to bring everything together. It is the last step before getting into backtesting.

You will essentially utilize the strategies and methods from before to find enhanced alphas and trading signals, and truly optimize a portfolio in the most efficient ways possible.

Project: Combine Signals for Enhanced Alpha

In this project, you will have to combine different methods to enhance alphas and mitigate risk factors in your portfolio.

It is pretty realistic to methods that would be used to optimize your own portfolio. You will utilize random forests to find the best alphas.

Lesson8: Simulating Trades with Historical Data

In this last lesson, you will do the final step: backtesting. The concepts taught in this lesson are very helpful for the project mentioned before. It is the first real mention or lesson based on backtesting.

Backtesting is unbelievably important for testing algorithms. To be honest, I think that these lessons could have been taught more thoroughly.

Project: Backtesting

This project is designed by a real-world quant, made for the hardest, but a most realistic project.

This project combines everything you’ve learned to make a backtest that utilizes historical data to optimize your portfolio and provide analysis on how it is performing.

The overall projects in this Udacity AI for trading Nanodegree were challenging.

Since I was not from a software background, so learning and practicing machine learning and deep learning concepts in programming seemed daunting at the first sight. 

I definitely struggled through multiple projects involving various concepts, but there were some pretty helpful resources to figure it out, yet most of the materials were covered in the lessons themselves. Projects were one of the best ways to learn.

Project reviews were also very helpful. The format was a bit confusing at first, but once you realize how it works, they will give you meaningful feedback to complete those projects.

As a full-time college student (remote Bc of COVID), it wasn’t difficult for me to schedule time every day or week.

The timeline of this Udacity AI for trading Nanodegree seems a bit unnecessary because you are able to go at your own pace.

But for the sake of trying to help you spend the appropriate amount per course/per month, it may become a helpful tool for you to stay on track.

Also, see -> Udacity Artificial Intelligence Nanodegree Review

Hope you are finding this Udacity Artificial Intelligence for Trading Review valuable.

 

Udacity features 

Talking about the features of Udacity, well there were various useful features of the Nanodegree.

But I want to mention some specific of them in this review of Udacity’s AI for Trading Nanodegree.

Mentorship

Mentorship in any field or situation is extremely important and helpful as well. Due to some reasons, I did not use this feature, but in situations where one is trying to improve technical skills, this can be a very helpful and useful feature.

Projects

Realistic projects were extremely useful in understanding the concepts and implementing them, feedback on a personal project was also very helpful.

You are working on your own for the most part, so feedback on how you completed a project is very useful to learn or get other perspectives.

For me personally, not having a thorough background in programming, feedback at any level was very beneficial.

Well, I already have planned what to do after completing this AI for trading Nanodegree so I have never used the career services feature.

Pros of Udacity

Udacity is one of few sites or organizations I was able to find with difficult or advanced level engineering or programming courses with quality instructors, difficult projects, and mentorship with consistent feedback and help.

That’s the reason why I feel it is worth the money because it is truly an environment where you can learn and improve your skills at your own pace.

What I Don’t like In AI for Trading Nanodegree

However, my only criticisms would be better instructions of project formats and assignment formats.

This was my first time taking an online course like this, it took me a while to understand my first project along with the format of submissions, etc.

The other would be better guidance for courses one should pick based on skillset and experience.

I might have taken a lower-level course just to ensure my programming skills allowed for a more positive experience in this AI for trading Nanodegree.

Conclusion:

I definitely recommend this Udacity AI for trading Nanodegree to others. Hope you got an idea of this Nanodegree in this review.

I learned so much and really improved my skills along with career opportunities. Looking forward to taking another course or Nanodegree soon.

Courses are very dense, so if you aren’t going to be somewhat disciplined and consistent, may not be worth your money or time.

You have to be consistent and serious about learning and developing your skills before enrolling in any of their Nanodegree.

Marcus udacity ai for trading review

Marcus D’Aguiar

A highly motivated, hard-working, and creative biomedical engineer (degreed) who is driven to make the world of medicine and rehabilitation a more effective and advanced setting.

Visit my LinkedIn Profile.

Udacity Artificial Intelligence for Trading review

AI for Trading Nanadegree

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