QUANTUNIVERSITY in Partnership with PRMIA
Presents
foundations of machine learning and AI for financial professionals
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, 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.
You will learn:
- Role of Machine Learning and AI in Financial services
- When do we use Machine learning and AI techniques?
- What are the key machine learning methodologies?
- How do you choose an algorithm for a specific goal?
- Practical Case studies with fully functional code
Delivery:
- Course duration: 1.5 hours/session
- Number of sessions: 8
- Case study + Labs using the QuSandbox
- March 17th – May 5th 2020
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
Prerequisites:
This course incorporates hands-on labs and case studies. Participants are expected to have fundamental knowledge of Python.
Pre-class reading will be sent to all registered participants.
Additional Python resources:
- A FREE tutorial on Python is available here
- Participants who want additional training in Python can enroll in the 6-hour online Python class hosted by QuantUniversity on March 7th 2020 and March 14th 2020.
Details will be posted here soon.
Machine Learning and AI: An intuitive Introduction
- Machine Learning vs Statistics: How has the world changed?
- A tour of Machine Learning and AI methods
- Supervised Learning Vs Unsupervised Learning
- Deep Learning
- Reinforcement Learning
- Key drivers influencing the adoption of Machine Learning and AI
- Big Data, Hardware, Fintech, AI, Alternative Data
- Key applications
- Credit risk, Personalization, Predicting risk, Portfolio optimization and selection
- Key players
- Technology companies, Data vendors, Banks, Fintech startups
Course instructor:
Sri Krishnamurthy, CFA
Chief Data Scientist, QuantUniversity
Sri Krishnamurthy is the founder of www.quantuniversity.com, a data and Quantitative Analysis Company and the creator of the Analytics Certificate program and Fintech Certificate program. Sri has more than two decades of experience in analytics, quantitative analysis, statistical modeling and designing large-scale applications.
Prior to starting QuantUniversity, Sri has worked at Citigroup, Endeca, MathWorks and with more than 25 customers in the financial services and energy industries. He has trained more than 1000 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 and another MS in Computer Science, both from Northeastern University and an MBA with a focus on Investments from Babson College.
QuantUniversity (www.quantuniversity.com) 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. The company offers an Analytics Certificate Program and the Fintech Certificate program along with multiple workshops in its Explore-Experience-Excel series. Contact us at info@qusandbox.com
The Professional Risk Managers International Association (PRMIA) is a professional organization focused on the "promotion of sound risk management standards and practices globally", and "the integration of practice and theory".It provides certification and credentialing for professional risk managers, as well as other educational programs and resources.
Past Attendees of QuantUniversity workshops include Assette, Baruch College, Bentley College, Bloomberg, BNY Mellon, Boston University, Datacamp, Fidelity, Ford, Goldman Sachs, IBM, J.P. Morgan Chase, MathWorks, Matrix IFS, MIT Lincoln Labs, Morgan Stanley, Nataxis Global, Northeastern University, NYU, Pan Agora, Philips Health, Stevens Institute, T.D. Securities and many more..
