Introduction To Data Science & Python for Finance (Session 2)
This is a Virtual Instructor - Led Training (VILT)
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. As a result, financial companies have been on an innovation and technology push to create new, disruptive technologies that can maximize use of these data assets to solve some of the industry’s toughest problems.
This is a one day course, split over two sessions of 3.5 hours on June 16th and June 18th. This hands-on course provides a structured teaching environment where students learn classic data science methods, which are used as the bases for many financial technologies. At the end of the workshop, course participants will have applied the Python programming language and essential data science techniques to solve complex finance problems.
Specific areas in finance where the 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.
- Overview of data science methods relevant to finance and fintech
- Explanation of the hype around data science, machine learning & big data
- Hands-on Python programming experience
- Understanding of effective data visualization techniques using Python
- Course notes, certificate of completion, and post-seminar email support for 3 months
- An engaging and practical training approach with a qualified instructor with relevant technical, business, and educational experiences
Who Should Attend: This course is relevant for students and professionals who want to gain a hands-on introduction to essential data science methods that are utilized in finance and fintech.
Prerequsities: You must have taken Cognitir's Introduction to Python for Business and Finance course before attending this workshop. Alternatively, you can take a free online Python course offered by a third party to get up to speed. Cognitir will provide a link to this prerequisite course.
Yu is currently a Masters in Computer Science student at Syracuse University and a data scientist at Operam, a marketing technology firm, where he focuses on building AI-driven products for the entertainment industry. He has helped build machine learning attrition models, financial data ETL pipelines, and natural language processing features for technology startups, financial services companies, and large multinationals. Yu has also worked developing server-side data engineering technologies with Python, Java, and Node.JS for a variety of organizations.
After graduating college, Yu taught at a Boston-based high school as a teacher, science department chair, and athletic director. He received his BA from the University of Pennsylvania and his MBA from UCLA Anderson, where he served as President of the Strategy & Operations Management Association.
Click here for more information on Introduction To Data Science & Python course curriculum
This Virtual Course is Instructed by our training partner, Cognitir