Artificial intelligence (AI) has become increasingly popular in the world of trading and investment, as it’s been proven to be a highly accurate tool for making decisions quickly and efficiently. With its growing power, AI is becoming increasingly important for traders who want to make their businesses more efficient and profitable.
However, there is a lot of confusion about what AI actually is and the role it plays in the world of trading. Read on to find out which industries are going to benefit most from the rise of AI, as well as how to make the most of this technology.
In this Nanodegree program, Become proficient in the basics of quantitative analysis, including data processing, signal generation, and portfolio construction. Practice using Python to analyze historical stock price data, develop trading strategies, and create a multi-factor model with optimization.
Udacity is an educational organization providing a huge library of open online courses. It was founded by Sebastian Thrun, David Stavens, and Mike Sokolsky. Udacity was started with free computer science classes in 2011 through Stanford University. At Udacity, they provide various kinds of courses such as free courses and courses that come with online certifications such as Nanodegree Programs.
Some of the unique features you will find at Udacity cannot be found anywhere else. These unique features are what actually make Udacity one of the very best platforms by which you can enroll in an online course.
- Real-world projects from top industry experts
With real-world projects and engaging content created in collaboration with top-tier firms, you’ll master the IT skills that employers demand.
- Technical Support by mentors at Udacity
The Smart and knowledgeable mentors at Udacity will guide your learning and are always available to answer your questions, help you and keep you on track
- Career services
You’ll have access to GitHub portfolio reviews and LinkedIn profile optimization to help you develop your career and obtain a high-paying position.
- Learn with your own freedom
Create a learning plan that matches your busy schedule. Learn at your own speed and on your own timetable to achieve your specific goals.
Class content – Real-world projects, Project reviews, and Project feedback from experienced reviewers
Student services – Technical mentor support, Student Community
Career services – Github review, Linkedin profile optimization
Meet Your Instructors
- Cindy Lin – Curriculum Lead
- Arpan Chakraborty – Instructor
- Elizabeth Otto Hamel – Instructor
- Eddy Shyu – Instructor
- Brok Bucholtz – Instructor
- Parnian Barekatain – Instructor
- Juan Delgado – Content Developer
- Luis Serrano – Instructor
- Cezanne Camacho – Curriculum Lead
- Mat Leonard – Instructor
You should have some experience with Python programming, be well-versed in linear algebra and calculus, and be knowledgeable about statistics.
Now let’s come to the most important part of the course which is the course itself and what you get in it when you enroll in this course. This Course has a total of eight sections each explaining some important topics related to the course and providing with you learning points and real-world projects at the end. Let’s take a deep dive into the sections -:
Basic Quantitative Trading
In this section, Master how markets operate and discover how to create signals with stock data with market mechanics information. Work on your first momentum-trading strategy in the course of your first undertaking.
In this project, Implement momentum trading to determine its ability to bring in money. You will be utilizing historical data from a particular financial market, generating a trading strategy based on a momentum indicator, then computing your signal. You will next estimate the projected returns of the signal before you create a statistical evaluation.
Advanced Quantitative Trading
In this section, Discover a quantitative workflow for signal generation, and then apply advanced quantitative methods commonly used in trading.
In this project, You will code the evaluation for a device jam session. An algorithm will use statistical tests to evaluate normality and to find alpha. You will also have a consider the results that noiseless data might have on your trading signal and identify if the outliers could be a reliable trading signal. You will have to determine what constitutes a reliable trading signal and what doesn’t.
Stocks, Indices, and ETFs
In this section, Discover the concepts of portfolio optimization, and portfolio construction by various types of stocks, including market indices, vanilla ETFs, and Smart Beta ETFs.
In this project, You will set up two portfolios using smart beta methodologies and optimization. You will determine the tracking errors of these portfolios by calculating the tracking error. You will also calculate the turnover of your portfolio and find the best time to initiate an overall rebalance. You will disclose portfolio weights based on fundamental data and quadratic programming.
Factor Investing and Alpha Research
In this section, Establish an alpha or beta score, in addition to risk metrics, to develop a portfolio.
In this project, Evaluate a number of alpha factors and develop multiple strategies for minimizing the risk of your portfolio. You’ll develop a sophisticated portfolio optimization problem by using constraints, such as risk models, leverage, market neutrality, and limits on factor exposures.
Sentiment Analysis with Natural Language Processing
In this section, Learn the basics of text analysis, and utilize corporate filings to generate sentiment-based trading signals.
In the project, Utilize whatever you have newly learned in Natural Language Processing, including cleaning data, text processing, feature extraction, and modeling, in order to work with corporate 10Q and 10K filings. You’ll then use bag-of-words and TF-IDF to come up with company-specific sentiments. Then, you’ll come up with trading strategies, measure their performance, and adjust your trading strategies as needed.
Advanced Natural Language Processing with Deep Learning
In this section, Use deep-learning algorithms for quantitative data analysis and apply recurrent neural networks and long short-term memory to make trading signals.
In this project, Deep neural networks can process and interpret news data. Identify different ways of embedding words into vectors and experiment with training LSTM networks for classifying sentiments. take full advantage of backtests and apply the models that support generating signals for news.
Combining Multiple Signals
In this section, Gather, choose, and combine various factors you have generated through both traditional and nontraditional means.
In this project, Select a model for a large data set that includes market data, fundamental data, and alternative data to create and validate a model for the S&P 500 and its constituents’ stocks. You will then carefully test your model, looking for signs of overfitting. Rank and select stocks to create a long-short portfolio using the predicted probability of success.
Simulating Trades with Historical Data
In this section, Learn to refine trading signals by running thorough backtests. Track your P&L as your algorithm makes and sells trades.
In the project, Construct an OHLC data feed and a backtesting framework. You will learn about various visualization techniques for backtesting. You will construct trading strategies using various parameters such as trade days, take profit levels, stop loss levels, etc. You will then optimize the parameters and evaluate the performance by analyzing the results of your backtesting.
According to the Program, the course is expected to be completed within approximately 6 months if you devote a minimum of 10 hours per week to the course. As we mentioned above, they have a self-paced learning environment, so you can attend at your discretion and at your pace.
If you take more than 6 months to finish the course, you have to take the monthly pay-as-you-go plan and pay extra which will increase your overall cost of the course.
Now let’s talk about the cost of the course which is an important part of whether you will buy or not buy the course. In this course, Either you will pay for monthly access or you can also choose a 6-Months access plan.
If you choose the monthly pay-as-you-go option you will pay $399 per month and there is another option that you can choose which comes with exclusive discounts which is a 6 months plan that you need to pay upfront and costs you around $2034 which comes with exclusive discounts making it cheaper than the monthly plan and also recommended by Udacity.
If you pay upfront for the 6 months’ access you can save up to 15% + 70% exclusive discounts which you cannot if you take the monthly plan. If you need more time after 6 months, you can switch to a monthly access plan but it will increase the overall cost of the course.
Udacity will give you personalized Discounts if you answer 2 questions and pay upfront rather than a pay-as-you-go plan. You will get a promo code with a 70% Discount on your course by just answering 2 simple questions.
While looking at ratings and reviews of this course, One has to say that this course is very popular among the students with an overall rating of 4.6 out of 5 stars, and many good quality reviews are given by already enrolled students in the courses. Some of the reviews are -:
“I loved the program. The first 3 projects were very basic, but everything after project 4 was great. You get introduced to alpha research, portfolio optimization and backtesting. In some of the projects you use Zipline, Quantopian’s open source library. While of course, it’s not expected for them to provide trading strategies to you, the applications of AI to trading seem relevant. You use neural networks, NLP, and random forests, among other models, in ways that are appliable to real trading research.”-Eduardo P.
“I received a lot of great advice from Udacity reviewers which I haven’t arranged a time to continue to organize project portfolio video demo with the reviews. And I should write each project a readme to demonstrate what I know and speak for each project, I work through. It matched my need in the part of the healing of my heart and soul like a puppy, sleep, meditation and Godzilla and the machine learning section give me a lot of lift. It’s about Thanksgiving, I want to tell Udacity thank you for guiding me to enroll this Nanodegree program :D! It is super worth this journey. I have a great life during this Nanodegree program.”– Hsin-Wen C.
Artificial intelligence is one of the most in-demand skills in the job market today. A recent study by Indeed found that the number of AI job postings grew 74% since 2015. The average salary for an AI developer is $114,000, which is significantly higher than the median salary for all occupations of $53,490.
AI developers are in high demand because they possess a rare combination of technical and soft skills. They must not only be able to write code and develop algorithms, but also have the ability to think creatively and solve problems.
This is overall a good course created by experts at Udacity and also the features and offers provided by Udacity make this course a very good Nanodegree program. Also, You should also check other courses which you can take right after this course as those courses are made with help of top tech companies, they are of high quality and make you more knowledgeable about your field. If you are interested in other Udacity courses, please check out all courses on our website.
The course also has easy to follow a curriculum that includes everything to build your foundation. And also every section at the end includes a real-world project that will give you practical experience and make you job-ready.
One thing you should keep an eye on is your timing, try to complete your course in the estimated time provided by the course, or else you have to pay more for extra months which will increase your overall cost of the course.
If you think that the Udacity AI for Trading Nanodegree Program is right for you, Udacity is the perfect place for you to take the course and land your dream job.