Workshop for CFA Society Poland members only and special guests. A workshop is a part of 2020 CFA Society Poland Annual Conference. Registration via www.cfasummit.pl.
Before workshop: a 10-minute welcome speech by Professor Krzysztof Jajuga, President of CFA Society Poland
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. In this series, we will provide an intuitive understanding to machine learning with just enough mathematics and basic statistics.
You will learn:
- 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
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
Session 1. Machine Learning and AI: An intuitive Introduction (1.5 hours)
1. Machine Learning vs Statistics: How has the world changed?
2. A tour of Machine Learning and AI methods
a. Supervised Learning Vs Unsupervised Learning
b. Deep Learning
c. Reinforcement Learning
4. Key drivers influencing the adoption of Machine Learning and AI
a. Big Data, Hardware, Fintech, AI/ML, Alternative Data
5. Key applications
a. Credit risk, Personalization, Predicting risk, Portfolio optimization and selection
6. Key players
a. Technology companies, Data vendors, Banks, Fintech startups
7. Case studies in Machine Learning
a. Machine Learning in Trading & Investment Management
Session 2. Core Methods and Applications (1.5 hours)
1. How does Unsupervised machine learning work?
2. How does Supervised machine learning work?
a. Cross sectional data
b. Time series analysis
c. Regression, Random Forests and Neural Networks
2. How will Machine Learning and AI change the investment industry?
3. Frontier topics
a. Anomaly detection
b. Natural Language Processing
c. Reinforcement learning
d. Risk in Machine Learning and AI
e. Model governance, Interpretability and Model Management
3. Case studies:
a. Predicting interest rates and credit risk using Alternative data sets.
b. Analyzing Earning calls from EDGAR using Natural Language Processing Techniques
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 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.
22 PAŹDZIERNIK 2020 | CZWARTEK
ONLINE AS A PART OF 2020 CFA SOCIETY POLAND ANNUAL CONFERENCE