5 – M1L1 05 Program Overview V1

Now let’s take a deep dive into the program, and talk about what you will learn in the next few months. First of all, to get the most out of this program, you’ll ideally have Intermediate Python skills including Numpy and Pandas, and prior exposure to statistics, linear algebra, and calculus. We’ve designed this program to be accessible to anyone who is passionate about using advanced data analytics to make sense of financial data. With that in mind, we will review certain bath encoding concepts as they are used or point you to other Udacity resources to refresh your background knowledge. The Nadir degree program has two terms. Each term contains four projects and will take three months to complete. Prior to each project, there’s a set of lessons, quizzes, and exercises that will introduce you to a topic and prepare you for the project. You will then practice what you’ve learned by completing the project. Note that much of your learning will come from working on the project, trying different things and even going beyond what is required as you explore what’s possible. We highly encourage you to take the time, to make each project your own unique reflection of what you have learned and what you are capable of. Students who successfully complete term one are eligible to enroll in term two. At the end of term two, you will embark on a Capstone Project which will give you the opportunity to use everything you’ve learned to design and evaluate quantitative trading strategies. In term one, you will learn about the Fundamentals of Quantitative Finance. You will apply quantitative methods that are practiced in the financial industry including regression, optimization, and trading signal generation. You will work on projects that reflect the actual quant workflow as it’s done in financial firms, with real data sets. Term one is designed to prepare you for term two, which applies more advanced methods to the quant workflow. In term two, you’ll use machine learning algorithms to generate trading signals. You’ll use natural language processing to analyze financial statements and apply recurrent neural networks to analyze news data. You’ll get hands on practice with backtesting, which is a realistic simulation designed to evaluate the effectiveness of a strategy. Finally, you will use advanced techniques to combine several trading signals together to optimize a portfolio. We hope that sounds exciting to you. We can’t wait to see you in the classroom.

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