Introduction to Data Science and Python for Finance
January 15-16: 9:00a-5:00p
The amount of data available to organizations and individuals is unprecedented. Financial services sectors, including securities & investment services and banking, have the most digital data stored per firm on average. Finance companies that want to maximize use of this available data require professionals who have a keen understanding of data science and know how to use it to solve meaningful business challenges.
This two-day, hands-on course provides a structured teaching environment where attendees learn the Python programming language as a powerful tool to conduct robust data analyses on finance-related data sets. At the end of the workshop, course participants will have applied the Python programming language and essential data analysis techniques to practical programming exercises to gain experience solving challenging finance-related problems.
Specific area in finance where data science skills acquired from this course can be effectively applied include: sentiment analysis, advanced time series analysis, risk management, real-time pricing and economic data analysis, customer segmentation analysis, and machine learning algorithm creation for financial technologies.
No prior programming experience required.
Learning Objectives:
Learn basic foundations in programming and data science
Receive an overview of state-of-the-art data science and machine learning methods
Discover how finance professionals can use data science to solve real-world problems
Understand the advantages of data science and specific analytical methods
Obtain hands-on Python programming experience
Understand effective data visualization techniques using Python
Ability to hit the ground running with executing core data tasks by the end of the course
Who Should Attend?
- Investment professionals
- Quantitative traders
- Event-driven fund managers
- PE/VC investors
- Traditional asset managers
- Fintech entrepreneurs and/or product managers
- FP&A and strategy professionals at corporations
- PE portfolio company operators
- Private wealth managers
- Economists
- IT and tech professionals at financial institutions
- Management consultants
Please Note: Participants will need to bring a laptop with them to the course.
