Financial Data Analytics & Machine Learning
| Total Duration | Certification Validity | Course Type |
|---|---|---|
| 6 Months | No Expiry Date | Online Interactive |
For further information, contact
Mr. Gajendra: +91 8454881917
Ms. Divya: +91 8976415049
Email: skanade@nse.co.in
The course blends finance, statistics, and analytics to equip the participants with the required skill sets in analyzing financial data. Participants will learn why, when, and how to apply statistical models on financial data to take real time day to day decisions in financial markets. By the end of this course, the participants should be able to build and use successful models using analytics in domains like accounting, trading, forecasting, risk management, portfolio management etc.
Introduction to Programming and Tools
Data Preparation
Data Visualization
Data Analysis & Statistics
Building Credit Risk Models
Time Series Analysis
Technical Analysis & Algorithmic Trading
Portfolio Analytics
Machine Learning Fundamentals
Building Stock Prices Forecasting Models using Machine Learning
6 Months of Immersive learning from experienced faculty/ professionals of XLRI & other Institutions/ firms
Industry aligned curriculum to teach intersection across finance, analytics and technology
Class discussions, cases, hands-on projects, interactive & engaging sessions to clear doubts
D2D Live interactive classes on Weekends
Certificate issued by XLRI & NSE Academy
For Indian Participants – Graduates from a recognized University (UGC/AICTE/DEC/AIU/State Government) in any discipline with Mathematics/Statistics up to 10+2 level.
For International Participants – Graduation or equivalent degree from any recognized University or Institution from their respective country.
Proficiency in English, spoken & written is mandatory. Deep interest and basics understanding of finance.
Strategic Decision-Making: Develop a data-driven mindset to make informed strategic decisions in complex financial scenarios.
Advanced Analytical Skills: Acquire proficiency in advanced financial modeling, time series analysis, and risk management strategies to enhance analytical capabilities.
Programming Proficiency: Develop strong programming skills in Python and R, thereby empowering participants to manipulate and analyze financial data effectively.
Networking: Connect with fellow professionals and potential collaborators, to expand your professional network.
Real-World Application: Apply acquired skills to manage real-world financial challenges through a comprehensive capstone project and gain practical experience for immediate implementation.
Updated on: 22/04/2024
