Introduction to Data Science for Finance
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OCT
13
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An Education Committee Sponsored Event
Overview
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 the these data assets to solve some of the industry’s toughest problems.
This one-day, 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.
WHAT THIS COURSE OFFERS
Overview
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 the these data assets to solve some of the industry’s toughest problems.This one-day, 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.
WHAT THIS COURSE OFFERS
- An 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
- Overview of popular Python libraries
- Course notes, certificate of completion, and post-seminar email support for 1 year
- An engaging and practical training approach with a qualified instructor with relevant technical, business, and educational experiences
This course is relevant for professionals who want to gain a hands-on introduction to essential data science methods that are utilized in finance and fintech.
Prerequisites:
Please note that you must have introductory Python programming skills before the start of this data science workshop. Cognitir offers an online Introduction to Python course, but this specific Python course is not required for this data science course; any introductory Python course will suffice."
Attendees may use a PC or Mac to access slides and other resources we provide for the class.
Course Curriculum and Contact Information
| Early Registration Fees (until October 1st) $415(Members) | $515 (Non-Member) |
| Registration Fees $515(Members) | $615(Non-Member) |
Payment Information
We accept the following:
If you prefer to pay by check please email info@cfala.org and request to pay by check. Your registration will be completed manually and you will receive an email confirmation.
Mail Check To:
We accept the following:
If you prefer to pay by check please email info@cfala.org and request to pay by check. Your registration will be completed manually and you will receive an email confirmation.
Mail Check To:
CFA Society of Los Angeles
13400 Riverside Drive, Ste. 215
Sherman Oaks, CA 91423
*Credit card payments will only be accepted through the secure online registration, and not by phone or email.
Cancellations
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.
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.
Chair:
Rama Malladi, CFA
Rama Malladi, CFA
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As a participant in the CFA Institute Approved-Provider Program, the CFA Society of Los Angeles has determined that this program qualifies for 7 credit hours. If you are a CFA Institute member, CE credit for your participation in this program will be automatically recorded in your CE Diary. |
