* Important Information

This course is being delivered by a PRMIA Learning Partner, QuantUniversity. All registrations, payments, and course operations will be managed exclusively by QuantUniversity. When registering for the course, you will be leave PRMIA.org and use QuantUniversity's registration system, proprietary learning management system, and QuSandbox for labs. 

EXCLUSIVE PRMIA NETWORK DISCOUNT:
PRMIA has partnered with QuantUniversity to offer a $100 discount (Regular fee $599) for registrations to this course. To avail this discount, please use code: PRMIADISCOUNT100 when registering for the course here: https://mlinfinance.splashthat.com/

QuantUniversity cancellation policy:  Cancellations received up to one week from the course start date (March 17, 2020) will receive a full refund less a $100 processing fee.  After this date, refunds or credits will not be issued; the registrant forfeits full payment. This cancellation policy supersedes PRMIA's posted cancellation policy.

COURSE DESCRIPTION

Lecture & hands-on lab work!

Learning Objectives

Upon completion of this course, you will be able to:

• Describe the role of Machine Learning and AI in financial services
• Describe when ML and AI techniques are used
• List the key machine learning methodologies
• Choose an algorithm for a specific goal
• Participate in case studies with fully functional code

Prerequisite

This course will include labs and case studies using the QuSandbox. Participants are expected to have fundamental knowledge of Python. A complimentary, basic introduction to Python is posted on https://mlinfinance.splashthat.com/.
 
Additional fee based training options, schedule for February 15, in Python will be posted on the course registration site.

How It Works

This course is delivered by QuantUniversity. Shortly before the course start date, registrants are provided with login credentials and a link to the course lecture and labs. Each Tuesday a lesson is launched. Although this is a self-paced course, we highly recommend you attend weekly classes and participate in labs during the week scheduled to get the most out of the course and support from the faculty. 

• Machine Learning and Statistics
• A Tour of ML and AI Methods
• Key Drivers Influencing the Adoption of ML and AI
• Key Applications
• Key Players

• Exploring and Visualizing Large Dataets

• Dimention Reduction and Visualizing Datasets Using PCA, T-SNE

• Segmentation Analysis for Equities
• Using K-means for Automatic Clustering of Stocks

• How Does Supervised ML Work?
• Evaluating ML Algorithms

• Machine Learning for Credit
• Predicting Interest Rates and Credit Risk Using Alternative Datasets

• Making Sense of Text and Natural Language Processing
• Sentiment Analysis

• Key Issues in Adopting AI and AL into Investment Workflows
• How ML an AI Will Change the Investment Industry
• Frontier Topics

• Fundamental and quantitative analysts, risk and investment professionals, portfolio managers new to data science and machine learning
• Financial professionals new to data-driven methodologies
• Machine learning enthusiasts interested in use cases in Fintech and financial organizations

Sri Krishnamurthy, CFA, CAP is the founder of QuantUniversity.com, a data and Quantitative Analysis Company, and the creator of the Analytics Certificate program and Fintech Certificate program. Sri has more than 15 years of experience in analytics, quantitative analysis, statistical modeling and designing large-scale applications. Prior to starting QuantUniversity, Sri worked at Citigroup, Endeca, MathWorks, and with more than 25 customers in the financial services and energy industries. He has trained more than 1,000 students in quantitative methods, analytics, and big data in the industry and at Babson College, Northeastern University, and Hult International Business School. Sri earned an MS in Computer Systems Engineering, an MS in Computer Science, both from Northeastern University, and an MBA with a focus on Investments from Babson College.