Foundations of ML and AI for Financial Professionals

Foundations of ML and AI for Financial Professionals
NEW COURSE! Financial firms are using artificial intelligence (AI) and machine learning (ML) to augment traditional investment decision making. In this course, we aim to bring clarity to how AI and machine learning are revolutionizing financial services. We will provide an intuitive understanding to machine learning with just enough mathematics and basic statistics. Python knowledge required. A FREE tutorial on Python is available on-demand. Participants who want additional training in Python can enroll in the 6-hour online Python class hosted by QuantUniversity on May 2nd 2020 and May 9th 2020.
 

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Note: You will leave PRMIA.org and be taken to our training partner's registration site. 

Agenda

Course Experts

CRL Credits


Presented By:
Sri Krishnamurthy, CFA, CAP
Founder, QuantUniversity.com


Lesson Length:
90-minute lessons & labs
8 lessons/one per week


Time: Self-paced


Course Dates:
May 12 - June 30, 2020
Instructor Access concludes July 7, 2020



PRMIA Special Pricing:
Receive a $100 discount at check-out use code: PRMIADISCOUNT100


Prerequisite: Basic Python skills
A FREE tutorial on Python is available on-demand. Participants who want additional training in Python can enroll in the 6-hour online Python class hosted by QuantUniversity on May 2, and May 9, 2020.

 

About This Course
 

MEET OUR TRAINING PARTNER 

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


EXCLUSIVE PRMIA NETWORK DISCOUNT
PRMIA has partnered with QuantUniversity to offer a $100 discount for registrations to this course. To avail this discount, please use code: PRMIADISCOUNT100 when registering for the course or the bundled Python course: https://mlinfinance.splashthat.com/

Prerequisite


This course will include labs and case studies using the QuSandbox. Participants are expected to have fundamental knowledge of Python. A FREE tutorial on Python is available here.

Need additional Python training?
Participants who want additional training in Python can enroll in the 6-hour online Python class hosted by QuantUniversity on May 2, and May 9, 2020.  For an additional $100, you can add this to your course purchase at check-out.
 

COURSE DESCRIPTION

Lecture & hands-on lab work!
The use of data science and machine learning in the investment industry is increasing. Financial firms are using artificial intelligence (AI) and machine learning to augment traditional investment decision making. In this course, we aim to bring clarity on how AI and machine learning are revolutionizing financial services. We will introduce key concepts, and through examples and case studies we will illustrate the role of machine learning, data science techniques, and AI in the investment industry. Rather than just showing how to write code or run experiments in Python, we will provide an intuitive understanding to machine learning with just enough mathematics and basic statistics.

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

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. 


 
Agenda
 Lesson/Week   Topic
 Lesson 1
 May 12, 2020

  Machine Learning and AI: An Intuitive Introduction
  • Machine Learning and Statistics
  • A Tour of ML and AI Methods
  • Key Drivers Influencing the Adoption of ML and AI
  • Key Applications
  • Key Players
 Lesson 2 
 May 19, 2020

  Exploratory Data Analysis
  • Exploring and Visualizing Large Datasets
 Lesson 3 
 May 26, 2020

  Core Methods and Applications
  • Dimension Reduction and Visualizing Datasets Using PCA, T-SNE
 Lesson 4 
 June 2, 2020
   Case Study + Lab
  • Segmentation Analysis for Equities
  • Using K-means for Automatic Clustering of Stocks
 Lesson 5 
  June 9, 2020
   Core Methods and Applications 
  • How Does Supervised ML Work?
  • Evaluating ML Algorithms
 Lesson 6 
  June 16, 2020
   Case Study + Lab 
  • Machine Learning for Credit
  • Predicting Interest Rates and Credit Risk Using Alternative Datasets
 Lesson 7
 June 23, 2020
   Working with Text 
  • Making Sense of Text and Natural Language Processing
  • Sentiment Analysis
 Lesson 8
 June 30, 2020
   Frontier Topics 
  • Key Issues in Adopting AI and AL into Investment Workflows
  • How ML and AI Will Change the Investment Industry
  • Frontier Topics


Who Should Attend
  • 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


About Our Experts

  
  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.

 
QuantUniversity  is a quantitative analytics and machine learning advisory based in Boston, Massachusetts. QuantUniversity runs various data science and machine learning workshops in Boston, New York, Chicago, San Francisco and online.  


Continued Risk Learning Credits: 14

PRMIA Continued Risk Learning (CRL) programs provide you with the opportunity to formally recognize your professional development, documenting your evolution as a risk professional. Employers can see that you are not static, making you a highly valued, dynamic, and desirable employee. The CRL program is open to all Contributing, Sustaining, and Risk Leader members, providing a convenient and easily accessible way to submit, manage, track and document your activities online through the PRMIA CRL Center. To request CRL credits, please email learning@prmia.org.

Registration
 Membership Type: Public Fee
Course/Bundle
ML/AI Course Only

 Use discount code ==>>  PRMIADISCOUNT100
 Sustaining, Corporate, and RIM Members $599/$699  $499
 Contributing Member $599/$699  $499
 Network Member $599/$699  $499

If this is your first time accessing the PRMIA website you will need to create a short user profile to register. Save on registration by becoming a member.

 

Register Now

 Note: You will leave PRMIA.org and be taken to our training partner's registration site. 
Need support?  Contact QuantUniversity at info@qusandbox.com

QUANTUNIVERSITY REGISTRATION POLICIES

This course is being delivered by a PRMIA Training Partner, QuantUniversity. All registrations, payments, and course operations will be managed exclusively by QuantUniversity. When registering for the course, you will leave PRMIA.org and use QuantUniversity's registration system, proprietary learning management system, and QuSandbox for labs. Questions and requests should be directed to QuantUniversity at info@qusandbox.com.

Cancellations received up to one week from the course start date (May 5, 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.  In the event sufficient registrations are not received, PRMIA and/or QuantUniversity reserve the right to cancel this course one week prior to the start date. Full refunds will be issued if cancelled by the training partner. 

 
When
5/12/2020 - 6/30/2020
Where
Virtual Training
 

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