Data Science for Finance Professionals

Data Science for Finance professionals with specialization in international Business analytics

Eligible Graduates: BCOM-MCOM/MBA finance /BA economics /BBA Finance

Master Data Science, language of the era and apply it to finance by joining the #1 ranked Professional Certificate Program in Data Science for finance professional with this comprehensive course. The course is conducted in collaboration with top worlds universities by top world faculties and professions.

This course features a mix of live classes, self-paced videos, hands-on projects, and business cases from leaders of the industry including BlackRock, Vanguard, Fidelity, State Street Global Advisors, and J.P Morgan Asset Management.

Duration : 60 Hours

Live Virtual and Self-paced Instructor Led Learning Formats

Guaranteed Job Assistance | Career coaching | Mock interviews

Unlimited access to the world Largest Biggest Widest Data Science Digital Library

Who should Join

This is the right course for you if you are:

  • Ambitious professional or graduates that want to expand your knowledge in Finance or in Data science and progress your career
  • Programmers, Engineers, Business Analysts who want to specialize in finance
  • Citizens interested in finance and investments
  • Professionals interested in learning how to code and apply their skills in practice
  • Finance graduates and professionals who need to upskill their knowledge in Data science tools for optimization and problems solving.

Applied Learning | On hand projects | Business Case studies

Interactive sessions | Group discussions | Networking

Placements salary Hikes | Max 130% | Ave 75%

Unlimited access to the world Largest Biggest Widest Data Science Digital Library

Course Outline

Course Introduction, Material and Anaconda Python software setup Python & Machine Learning for Financial Analysis

Part 1- Python Programming Fundamentals
Variable assignment, Math Operations, Precedence and Print/Get
Data Types
Comparison Operators, Logical Operators and Conditional Statement
Files Operations
Data Science Python Libraries for Data Analytics (NumPy)
Data Science Python Libraries for Data Analytics (Pandas)
Data Visualization with Matplotlib and Pandas
Data Visualization with Seaborn

Part 2 – Python for Financial Analysis
Data sources – Pandas Data reader & Quandl
Pandas with Time series Data
Capstone Stock Market Analysis project
Time series Analysis
Stock Data Analysis and Visualization in Python
Asset Allocation and Statistical Data Analysis
Capital Asset Pricing Model (CAPM)

Part 3 – Machine and Deep learning in Finance
Prediction of Stocks Future using Machine and Deep Learning
Segmentation of Bank market using unsupervised Machine learning Techniques
Perform Sentiment Analysis on Stock Data using natural Data processing.

Part 4 – Python for Algorithmic Trading
Basics of algorithmic trading with Quantopian and Zipline
Advanced Quantopian and Trading Algorithm

Part 5- Python for Investment Fundamentals Data Analytics
Rate of return of stocks and Risks
Rate of return of stock portfolios and Risks
Correlation between stocks
Diversifiable and non-diversifiable risk
Regression analysis
Alpha and Beta coefficients
Measuring a regression’s explanatory power with R^2
Markowitz Efficient frontier calculation
Capital asset pricing model
Sharpe ratio
Multivariate regression analysis
Monte Carlo simulations and using in Corporate Finance context
Derivatives and type of derivatives
Applying the Black Scholes formula
Using Monte Carlo for options pricing and stock pricing

Data science used cases in Finance domain