Data Science for Finance Boot Camp
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 participants will 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 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.
WHAT THIS COURSE OFFERS
- Hands-on Python programming experience
- Understanding of the advantages of data science and specific analytical methods in finance
- Experience in using Python to apply data analysis techniques and machine learning methods to solve complex finance problems
- Understanding of effective evaluation and data visualization techniques
- Course notes, certificate of completion for professional development requirements, and post-seminar support
- An engaging and practical training approach with one qualified instructor with relevant technical, business, and educational experiences.
*Please note that based on availability, David Haber or Neal Kumar will teach this course*
David Haber – Lead Instructor
David has led programming workshops at the undergraduate and graduate levels, at blue chip companies, and world renowned management consulting firms. He is a lead software engineer at an investor-backed and award-winning health-tech startup in London where he works on machine learning and iOS development. Previously, David worked on optimizing large-scale payment processing systems at Deutsche Bank in Singapore. David holds a Computer Science degree (First-Class Honors) from Imperial College London (UK) where he focused on statistical machine learning. He presented his work at international conferences and won several awards for his work. During his studies, he also served as a teaching assistant at Imperial College where he helped undergraduate students master fundamental computer science concepts.
Neal Kumar – Lead Instructor
Neal is currently a trainer with a top three global financial training company. As a senior trainer, he teaches financial modeling and valuation at the undergraduate, graduate, and corporate levels. Neal has consistently received top reviews from attendees. In addition to leading trainings, he created two new courses that were used to teach thousands of university and corporate students around the world. Prior to joining the financial training company, Neal was a Teach For America (TFA) Teacher in St. Louis (USA). As a TFA Teacher, he taught secondary mathematics in St. Louis Public Schools. Neal received the highest TFA designation - “Significant Gains” - for the academic gains that he made with his students. He credits much of his teaching success to the data mining principles he applied to student data to drive his decision making and teaching strategies. Prior to joining Teach For America, Neal was an investment banker with JPMorgan and Houlihan Lokey. Neal holds an MBA from London Business School (UK) and a BBA in Finance from the University of Notre Dame (USA). He is also a CFA Charterholder.
For more information, please visit www.importclasses.com
$1100 (Members) | $1400 (Non-Member)
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We accept the following:
If you prefer to pay by check please register online and select "purchase order" as your payment option and enter your last name as the purchase order number.
Mail check to:
CFA Society of Los Angeles, 520 S. Grand Ave, Suite 655, Los Angeles CA 90071.
*Credit card payments will only be accepted through the secure online registration, and not by phone or email.
Enrollee cancellations must be made in writing and received at least 5 business days before the first day of class. All cancellations will incur a $30.00 processing fee. If enrollment is canceled after the 5-day deadline, a 50% cancellation fee will be charged.
Rama Malladi, CFA