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Coupon & course info

Course Name: Quant Trading using Machine Learning

Subtitle: A completely practical approach to applying Machine Learning techniques to Quant Trading

Instructor: Taught by Loony Corn, A 4-person team;ex-Google; Stanford, IIM Ahmedabad, IIT

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $20 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of July 11, 2016…

Students: 270 students enrolled

Ratings: 27 reviews

Rank: ranked #143a in Udemy Business Courses

Brief course description

Prerequisites: Working knowledge of Python is necessary if you want to run the source code that is provided. Basic knowledge of machine learning, especially ML classification techniques, would be helpful but it’s not mandatory.

Taught by a Stanford-educated, ex-Googler and an IIT, IIM – educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

This course takes a completely practical approach to applying Machine Learning techniques to Quant Trading

(Read more about this course on the official course page.)

Loony Corn bio

Loonycorn is us, Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh. Between the four of us, we have studied at Stanford, IIM Ahmedabad, the IITs and have spent years (decades, actually) working in tech, in the Bay Area, New York, Singapore and Bangalore.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 64 lessons

Duration: 11 hours of video

What you get: Develop Quant Trading models using advanced Machine Learning techniques

Target audience: Yep! Quant traders who have not used Machine learning techniques before to develop trading strategies

Requirements: Working knowledge of Python is necessary if you want to run the source code that is provided.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons