Did you know Python is one of the best solution to quantitatively analyze your finances by taking an overview of your timeline? This hands-on course helps both developers and quantitative analysts to get started with Python and guides you through the most important aspects of using Python for quantitative finance. With numerous practical examples through the course, you will develop a full-fledged framework for Monte Carlo, which is a class of computational algorithms and simulation-based derivatives and risk analytics.
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- Access 6 lectures & 5.5 hours of content 24/7
- Understand Python & its various data structures
- Work with Python libraries & tools designed specifically for analytical and visualization purposes
- Get an overview of cash flow across the timeline
- Learn concepts like Time Series Evaluation, Forecasting, Linear Regression & more
- Compute Value at Risk (VaR) & simulate portfolio values using Monte Carlo Simulation
Financial modeling is a core skill required by anyone who wants to build a career in finance. This eBook explores the terminologies of financial modeling with the help of Excel. It provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. The book takes an intuitive approach to model testing and covers best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and have the skills you need to build financial models to extract the information required to make informed business decisions.
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- Lifetime access to eBook with 292 pages
- Learn the basic ingredients of a financial model
- Explore the key concepts of Excel such as formulas & functions
- Understand your financial projects, build assumptions, & analyze historical data
- Develop data-driven models & functional growth drivers
We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. This eBook starts by giving a general introduction to machine learning, making every concept clear and understandable. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow.
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- Lifetime access to eBooks with 254 pages
- Understand more about machine learning
- Know every step of a machine learning project
- Combine Excel functions, add-ins, & connections to databases and to cloud services
- Learn different machine learning models on various types of data to be analyzed
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