Applied Quantitative Finance and Machine Learning

Harvard Extension School

CSCI E-278

Section 1

CRN 26782

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This course is about how to lift the veil of an insider's industry. Students learn how quantitative finance is applied in practice and utilized by the world's largest investment banks, asset management firms, hedge funds, pension plans, and insurance companies. All these repeatedly and consistently generate billions in profits. This course covers the four major pillars of quantitative finance: data management and analytics, quantitative investment strategies, portfolio management, and risk management. We address cutting-edge machine learning and artificial intelligence (AI) techniques in quantitative finance and describe essential industry domain knowledge and techniques which help students to enter the field of quantitative finance or advance in their current role.

Instructor Info

Moustapha Mark Antonio Awada, PhD

Head of Research and Data Science, Digital Data Design Institute, Harvard University


Meeting Info

T 5:10pm - 7:10pm (1/27 - 5/17)

Participation Option: Online Asynchronous or Online Synchronous

In online asynchronous courses, you are not required to attend class at a particular time. Instead you can complete the course work on your own schedule each week.

Deadlines

Last day to register: January 23, 2025

Prerequisites

CSCI E-101 and the ability to code in Python and/or R.

Notes

This course meets via web conference. Students may attend at the scheduled meeting time or watch recorded sessions asynchronously. Recorded sessions are typically available within a few hours of the end of class and no later than the following business day.

Syllabus

All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
35736 1 Online Asynchronous, Online Synchronous Moustapha Awada Field not found in response. TTh 6:30pm - 9:30pm
Jun 24 to Aug 9
26782 1 Online Asynchronous, Online Synchronous Moustapha Awada Open T 5:10pm - 7:10pm
Jan 27 to May 17