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Python for Finance: Investment Fundamentals & Data Analytics

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Learn how to code in Python Take your career to the next level Work with Python's conditional statements, functions, sequences, and loops Work with scientific packages, like NumPy Understand how to use the data analysis toolkit, Pandas Plot graphs with Matplotlib Use Python to solve real-world tasks Get a job as a data scientist with Python Acquire solid financial acumen Carry out in-depth investment analysis Build investment portfolios Calculate risk and return of individual securities Calculate risk and return of investment portfolios Apply best practices when working with financial data Use univariate and multivariate regression analysis Understand the Capital Asset Pricing Model Compare securities in terms of their Sharpe ratio Perform Monte Carlo simulations Learn how to price options by applying the Black Scholes formula Be comfortable applying for a developer job in a financial institution You'll need to install Anaconda. You'll need to install Anaconda. Do you want to learn how to use Python in a working environment? Are you a young professional interested in a career in Data Science? Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems?


'Facial scans that can calculate risk': new tools that will transform your finances - Telegraph

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Lawrence Wintermeyer, CEO of Innovate Finance, expects to see more innovators trying to tap into the unbanked and unrepresented consumer market. He said: "The firm Pockit, for example, gives customers an account and card that they can use to manage their money and make payments. Users can deposit money into their account at thousands of locations across the UK or have their salaries or benefits paid into their account. Pockit users also get cash back deals on the high street and online." So-called "challenger banks" are popping up and Monese is the latest to make waves.