Start Date: August 22, 2022
Two Options: LIVE Virtual Training or Online
Live class time: Aug 22 -9:30 AM - 4:00 PM EDT
Online course: Self-paced
Presented by: Sri Krishnamurthy, CFA, CAP, QuantUniversity
| About This Course |
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The use of AI and machine learning in finance has grown significantly in the last few years. As more and more AI and ML applications are being deployed in enterprises, concerns are growing about the increased complexity of models, the growing ecosystem of untested frameworks and products, potential for AI accidents, model and reputational risk. As the debate about explainability, fairness, bias, and privacy grows, there is increased attention to understanding how the models work and whether the models are designed and thoroughly tested to address potential issues.
The area "Algorithmic auditing" is fast emerging and becoming an important aspect in the adoption of machine learning and AI products in the enterprise. Companies are now incorporating formal ethics reviews, model validation exercises, internal and external algorithmic auditing to ensure that the adoption of AI is transparent and has gone through thorough vetting and formal validation processes. However, the area is new and organizations are realizing there is an implementation gap on how Algorithmic auditing best practices can be adopted within an organization.
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| Who Should Attend |
• Risk professionals
• Model Validators
• Model Auditors
• Data Scientists and ML engineers and Software engineers involved in ML and AI deployment
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| About Our Expert |
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Sri is the founder of QuantUniversity, a data and quantitative analysis company. He has more than 15 years experience in analytics, quantitative analysis, statistical modeling and software development. He is a quantitative specialist with significant experience in designing data mining and analytic systems for some of the world’s largest asset management and financial companies
Sri has worked at MathWorks as a Computational Finance Consultant where he worked with more than 25 customers providing asset management, energy analytics, risk management and trading solutions. Prior to that, Sri was a consultant at Endeca (now Oracle) in their Analytics Group and at Citigroup in their Fixed-Income Group building large-scale analytical and trading systems.He is a Charted Financial Analyst and a Certified Analytics Professional.
He is an active member of the Boston Security Analysts society and QWAFAFEW.
Sri is the creator of the Fintech Certificate Program & Analytics Certificate Program and teaches graduate courses in Quantitative methods, Data science and Analytics and Big Data at Babson College, Northeastern University and Hult International Business School.
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| Continued Risk Learning Credits: 5 |
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 [email protected].
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| By clicking Register Now, you will be taken to our training partner's registration site where you can choose your preferred learning option (Live Virtual or Online). |
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| Live Virtual Training: PRMIA Members -- USE DISCOUNT CODE PRMIA100 |
$ 799.00 |
| Live Virtual Training: Regular Price |
$ 899.00 |
| Online: PRMIA Members -- USE DISCOUNT CODE PRMIA100 |
$ 599.00 |
| Online: Regular Price |
$ 699.00 |
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Register Now
Note: You will leave PRMIA.org and be taken to our training partner's registration site.
Need support? Contact QuantUniversity at [email protected]
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 www.qu.academy for labs. Questions and requests should be directed to QuantUniversity at [email protected].