Learn the fundamentals of ML and how to apply it to the world of Finance – to help you both in your career, and with your investing!
Quantitative investment managers have been beating the market for decades using computers – with many getting more than double the average stock market return while taking on less risk.
We can teach you how to develop similar techniques so that you can fight back with your own algorithms.
Lumiwealth offers the best tech courses and is rated 4.8 out of 5!
We have helped thousands of students all over the world with our courses.
We’re always adding new material – and you’ll get lifetime access to the content!
After passing the course you will receive a certificate of completion that you can show to employers & clients.
Increase Your Salary
Create Projects You Can Use or Add to Your Resume
Make More Money From Your Investments
Level Up Your Skills
Get Started With Machine Learning For Free
Fill the form to receive access to a FREE LIVE CLASS on Machine Learning for Finance
We have several plans for our course each designed to fit your learning needs and style. Our classes are taught online live and one-on-one, or you can just get the videos only.
Whatever plan you choose, we are here to support you and make sure you are learning and achieving your goals.
Self-directed is a great way to get started on your learning with hours of engaging video lectures and reusable code.
Live learning is a fun way to learn allowing you to interact with other students and the instructor in real time fostering collaboration and discussion about the course material.
One-on-one learning is a great way to learn allowing you to go at your own pace with the instructor guiding you along the way.
Week 1: Student Introductions, Helpful Resources, Etc.
Week 2: Machine Learning Basics
Week 3: Deep Learning
Week 4: Optimizing Models
Week 1: Time Series Forecasting
Week 2: Building a Stock Forecasting Model
Week 1: Natural Language Processing
Week 2: Practical Stock Forecasting Model
Projects signal to employers that you know your stuff! You’ll build an impressive portfolio of projects that demonstrate your abilities.
The Live Classes plan includes the projects below, while the Project Help / Tutoring plan includes these and help with your own custom project.
Project 1: Forecasting Stock Prices Using Machine Learning
In this project, we will use the latest machine learning techniques to forecast a stock’s price 15 minutes into the future on a rolling basis. This technique can be applied for your trading to help you get better returns, and can also be used in many other finance applications such as forecasting revenue, profit, and other time-series data.
Project 2: Using Machine Learning to Trade on the News
For this project, you will pull data from a news source (e.g. Bloomberg, Twitter, Reddit, etc) and then train a machine-learning algorithm to read the news and suggest trades. Some examples of this could be breaking news, analyst recommendations, social media interest, and more, where your algorithm could react hundreds of times faster than a human being.
Greg is a Caltech and UC Berkeley alumni and SITN @Stanford.
In 2012, he founded the business analytics firm Percolata and raised ten million dollars from top-tier venture investors including Google Venture, Andreesen Horowitz, and Menlo Ventures.
At Percolata, Greg pioneered the use of machine learning to help clients like Uniqlo and 7-Eleven make smarter marketing decisions and optimize their operations.
Additionally, Greg founded Pika Group in 2020, a web3 startup that develops algorithms to help automate day trading.
He’s also on the Palo Alto City Council and a US Congressional Candidate
Get Started With Machine Learning For Free
Fill the form to receive access to a FREE LIVE CLASS on Machine Learning for Finance!
“I didn’t want to buy a course of just videos. I think having somebody to interact with, like you’ve been great both on Discord and chat… Then the class has been interactive but also you’ve hopped on a call and just helped me out which has been game changing. So that’s why I chose Lumiwealth, it was really because you guys offer that level of care.”
“There’s people coming from way different backgrounds, some people are day traders like me others are more in the field of finance, and so it was really cool to just meet everybody and interact.”
– Agim Salija
“The class has been great. It has done exactly what I sought out. I have learned techniques to help me assess the quality of trading strategies which I didn’t have before. Overall, it has boosted my ability to create a trading bot and more easily test strategies in a way that I wasn’t able to before.”
“For anyone who is looking to learn Python, Finance, and putting together the dots in order to create their own strategy or enter the job market, I think this would be a great course to take.”
– Rene Serulle
“Absolutely would recommend the classes. I went live with this trading bot a couple of weeks ago and right now I have almost made 80% of the money I spent on the course itself back from the bot itself. The trading strategies that I learned in the class paid for the class itself. I don’t think there is a better return on investment.”
“Learning from you was one of the biggest advantages. The depth of your experience you have and sharing that with all of us is amazing. To have that kind of person who’s willing to teach other people and help them enhance their lives is amazing.”
– Santayan Paul
“I liked the variety of things being covered the most during the classes, not only how to set up a bot and connect to a broker, but also CAGR, long-term economic data, and things that I wasn’t really thinking about. For example, how long term trends can affect short-term prices. I liked the overall breadth of the class and how it wasn’t just all about the algo trading portion of it; there was a lot of how and what too.”
“I would recommend Lumiwealth’s classes to anybody who wants to understand and take more control of their trading. To anyone who wants to learn about Python/technology and trading and how these two things interplay with each other.”
– Joel Brass