Talentedge

Executive Development Program in Financial Analytics From Xlri

Available dates

Feb 2—20, 2020
20 daysModules info
Gurugram, India
USD 1600
USD 80 per day

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About the course

Build successful financial models using analytics

Every business in the industry is generating loads of financial data and they understand the significance of deriving logical inferences out of it to streamline their decision making process. Lately, accurate financial data analysis is not enough for a business to sail through. They need predictive insights which can improve their real time day to day decision making. Financial analytics helps in combining internal and external financial information by using social media and big data to provide predictive insights. Whether it is with respect to stock market prediction or customer profitability, finance analytics enables to provide a direction in predicting all.

Financial analytics course blends easy-to-use statistical tools with complex machine learning tools and algorithms to equip the participants with the requisite skill set in analyzing data. By the end of this course, the participants should be able to perform financial analysis using powerful tools like R and Python.

Pedagogy

The primary method of instruction will be through LIVE lectures that will be beamed online via Internet to student desktops/laptops or classrooms. The pedagogy will comprise lectures by XLRI faculty and will be taught with the help of presentations, exercises and general discussions. Being an applied course, most of the sessions will be conducted as a workshop. By the end of the course, the participants will be better able to use Python and R to build advanced financial models and perform exploratory and predictive analysis in Finance. All enrolled students will also be provided access to our SLIQ Cloud Campus through which students may access other learning aids, reference materials, assessments, projects and assignments as appropriate. Throughout the duration of the course, students will have the flexibility to reach out to the professors, real time during the class or offline via our SLIQ Cloud Campus to raise questions and clear doubts.

Assessment

A minimum of 70% attendance to the LIVE lectures is a prerequisite for the successful completion of this course. There are periodic evaluations built in throughout the duration of the course. These maybe in the form of a quiz, assignment, project or other objective/subjective assessments. The evaluations are designed to ensure continuous student engagement with the course and encourage learning. Participants who successfully complete the same along with the requisite attendance criteria, an end course assessment and project work will be awarded a certificate of completion by XLRI. Participants who are unable to clear the evaluation criteria but have the requisite attendance will be awarded a participation certificate by XLRI.

Pedagogy

The primary method of instruction will be through LIVE lectures that will be beamed online via Internet to student desktops/laptops or classrooms. The pedagogy will comprise lectures by XLRI faculty and will be taught with the help of presentations, exercises and general discussions. Being an applied course, most of the sessions will be conducted as a workshop. By the end of the course, the participants will be better able to use Python and R to build advanced financial models and perform exploratory and predictive analysis in Finance. All enrolled students will also be provided access to our SLIQ Cloud Campus through which students may access other learning aids, reference materials, assessments, projects and assignments as appropriate. Throughout the duration of the course, students will have the flexibility to reach out to the professors, real time during the class or offline via our SLIQ Cloud Campus to raise questions and clear doubts.

Syllabus

  • Quick introduction to R and Python
  • Understanding data in finance, sources of data
  • Cleaning and pre-processing financial data
  • Exploratory Data Analysis in Finance
  • Building Models using Accounting Data
  • Understanding stock price behaviour, time series analysis in finance
  • Understanding and valuing options
  • Forecasting stock prices using machine learning
  • Credit risk modeling
  • News analytics (accessing news using web scrapping) and sentiment analysis in finance

Who should attend

  • Finance professionals
  • Executives
  • Analysts

Trust the experts

Pitabas Mohanty

Prof. Pitabas Mohanty is a Fellow of the Indian Institute of Management, Bangalore. He was a Senior Visiting Scholar at Stern School of Business, New York University in 2009-10. A Gold Medalist in MA (Applied Economics), he is also a Chartered Financial Analyst and a cost accountant. He has got ...

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