Learn using data analytic tools for conducting real-world financial analysis with Python for Finance: Investment Fundamentals & Data Analytics course.
Python for Finance: Investment Fundamentals & Data Analytics online course is designed to help candidates learn concepts and skills of python for finance, investment, tackle financial calculations and portfolio optimization tasks for both beginners who have never even coded before and professional python programmers who want to polish their skills and to help them increase their opportunities to enhance their career prospects.
Python for Finance: Investment Fundamentals & Data Analytics online certification is a short-term course offered by Udemy Inc., a US-based online learning platform. The course content is created by 365 careers, ranking 1 among Udemy’s best-selling providers of business, data science, and finance.
Python for Finance: Investment Fundamentals & Data Analytics syllabus covers major topics, tools, and techniques useful for data analysts and financial analysts such as Rate of return of stocks calculating the risk of stocks, rate of return of stocks, risk of a stock portfolio, covariance, the correlation between stocks, diversifiable and non-diversifiable risk, alpha & beta coefficient, regression analysis, Sharpe ratio, Markowitz efficient frontier calculations. Candidates will also learn about derivatives and their types, using Monte Carlo for options pricing and stock pricing, the Black Scholes formula, and many tools to help learners develop skills at a cost of Rs. 4,999 only.
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Udemy
After completing the Python for Finance: Investment Fundamentals & Data Analytics certification course, learners will be able to gain an understanding of the applications of python programming in investment and finance, build programs with python’s conditional operations, use python to resolve practical tasks, analyse the investment and creating an investment portfolio, calculating risk, return on investment, return of individual securities. Learners will also learn about capital asset pricing models, Monte Carlo simulations, applying the Black Scholes formula, using the Sharpe ratio, etc.
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