Course Summary
This course teaches the fundamentals of machine learning and how they can be applied to trading in financial markets. Students will learn how to build trading models, evaluate their performance, and implement them in real-world trading scenarios.Key Learning Points
- Apply machine learning techniques to trading in financial markets
- Build and evaluate trading models
- Implement trading models in real-world scenarios
Job Positions & Salaries of people who have taken this course might have
- Quantitative Analyst
- USA: $93,000
- India: ₹1,200,000
- Spain: €60,000
- Algorithmic Trader
- USA: $130,000
- India: ₹2,000,000
- Spain: €90,000
- Data Scientist - Finance
- USA: $120,000
- India: ₹1,800,000
- Spain: €75,000
Related Topics for further study
Learning Outcomes
- Understand the fundamentals of machine learning and its application in finance
- Build and evaluate trading models using machine learning techniques
- Implement trading models in real-world scenarios
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python programming
- Familiarity with financial markets and trading concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Python for Finance
- Data Science for Business
Related Education Paths
- Certified Financial Modeling & Valuation Analyst (FMVA)
- Certified Investment Banking Operations Professional (CIBOP)
Notable People in This Field
- Andrew Ng
- Nassim Nicholas Taleb
Related Books
Description
Implement machine learning based strategies to make trading decisions using real-world data.Requirements
- Students should have strong coding skills and some familiarity with equity markets. No finance or machine learning experience is assumed. Note that this course serves students focusing on computer science, as well as students in other majors such as industrial systems engineering, management, or math who have different experiences. All types of students are welcome! The ML topics might be "review" for CS students, while finance parts will be review for finance students. However, even if you have experience in these topics, you will find that we consider them in a different way than you might have seen before, in particular with an eye towards implementation for trading. Programming will primarily be in Python. We will make heavy use of numerical computing libraries like NumPy and Pandas. See the Technology Requirements for using Udacity.
Outline
- lesson 1 Manipulating Financial Data in Python lesson 2 Computational Investing lesson 3 Machine Learning Algorithms for Trading
Summary of User Reviews
This course is highly recommended for those interested in using machine learning for trading. Users praise its practical approach and its ability to teach complex concepts in a simple manner. The course has received high overall ratings from users.Key Aspect Users Liked About This Course
The practical application of machine learning in trading is a key aspect that many users found valuable.Pros from User Reviews
- The course provides practical examples and real-world applications of machine learning in trading.
- The course is well-structured and easy to follow, even for beginners.
- The instructors are knowledgeable and able to explain complex concepts in a simple manner.
- The course provides hands-on experience with popular programming languages used in trading, such as Python and R.
- The course provides a solid foundation for those interested in pursuing a career in machine learning for trading.
Cons from User Reviews
- Some users found the course to be too basic and not advanced enough.
- The course can be time-consuming, especially for those with limited programming experience.
- The course focuses heavily on theory, which may not be suitable for those looking for a more practical approach.
- Some users found the course to be too expensive compared to other similar courses available online.
- The course may not be suitable for those interested in using machine learning for trading in specific markets or industries.
Option selling trading as income source. Beginners friendly
- 3.7
-
![]()
![]()
![]()
![]()
![]()
Learn how to use option time decay in this strategy. 14 days live run with real profits included!! " Please watch promo-video, as it goes directly through the course!...
Il linguaggio naturale, dall'uomo alla macchina
- 0.0
-
![]()
![]()
![]()
![]()
![]()
II corso si prefigge di offrire una panoramica sulle tecnologie di trattamento automatico del linguaggio sia scritto che parlato con particolare attenzione alle tecnologie per il dialogo uomo-macchina....
Serverless Data Analysis with Big Query on Google's Cloud
- 0.0
-
![]()
![]()
![]()
![]()
![]()
The Third Course in a Series for Attaining the Google Certified Data Engineer Note: This is not a programmers course on BigQuery....
Remote Sensing Image Acquisition, Analysis and Applications
- 4.5
-
![]()
![]()
![]()
![]()
![]()
Welcome to Remote Sensing Image Acquisition, Analysis and Applications, in which we explore the nature of imaging the earth's surface from space or from airborne vehicles....
