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
- 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
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.