Many times in finance, companies are tasked with analyzing historical data to better predict future outcomes, whether it's to value a company, invest in a stock, or to better predict risk. Using Python and machine learning techniques, students can learn to better predict in a faster and more accurate way.
This course will begin with advanced Python and statistics topics such as object-oriented programming and regression models. After learning this first module, students will learn how to apply these concepts using real-world financial data by building a predictive returns model using regression.
The next section of the course will introduce students to important financial statements and ratios. After students learn these financial concepts, they will be introduced to how to pull data from these statements and compute these important financial ratios using Python.
After an initial analysis, students will cover more advanced financial modeling topics that measure present value, cost of capital, and the rate of return of an investment. Students will then apply those concepts using Python and Machine learning to build predictive financial models. After building these models, students will learn how to build out a budgeting model using only Python. Lastly, students will learn how to visualize their findings and export them into a PDF report, Excel file, or SQL database.
At the end of the course, students will feel comfortable making decisions driven by data analysis in Python. This course is perfect for anyone working in all areas of finance, risk management, reporting, general financial management, and financial investments.
This course requires students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Immersive or Python for Finance Immersive before taking this course.
From our hands-on training style to world-class instructors and custom-crafted curriculum, we deliver results our alumni are proud of.
Very good course if you want to get into the details of python, data analysis and machine learning concepts. Plenty of time to exercise and try out the concepts at your own pace. Tim is a great teacher who is able to explain complex concepts in a simple way.
Excellent and enjoyable class! Art has a systematic method of teaching that allows for relevant tangents based on the interests of the class. We even spent an entire class on a project I had for work and from which the other students benefitted also. Art is great at focusing on the proper way to think (data types and data structures!) and the logic behind the code, as well as explaining all the concepts and syntax in a methodical fashion that builds well upon previous material. He is also 100% accessible outside of classroom hours for help/questions etc. I am continuing with many other Practical Programming classes. Highly recommend!
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I didn't expect to learn much in a 4 session Python course, but Art's teaching style was very fitting for me. As the Chinese proverb states: Tell me, I'll forget. Show me, I'll remember. Involve me, I'll understand.
—James C.
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Attend this course in-person in NYC or live online. Engage with expert instructors, ask questions, and get feedback on your exercises and projects.
Unlike other providers, these are not mass open-enrollment classes. At Practical Programming, you’ll learn in small groups (typically 8-15 students) and receive personalized attention.
Get face-to-face interaction with an instructor and other students when you learn at our 185 Madison Ave, NYC campus. Courses are hands-on with a computer and software provided.
Get the same interactivity and access to the instructor as in-person students. There are no extra fees and we’ll work with you to ensure your remote setup is perfect.
Upon completion of this course, you’ll receive an official certificate testifying to your mastery of the curriculum. We’ll send you a link where you can download your certificate, share it online with your friends, post it to your professional network on LinkedIn, and view all your earned certificates. Congratulations on your achievement!
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We offer a single free retake of the class within a year.
You can also access recordings of each session in your student portal within one business day of the session’s end. Recordings are available for one month after the session.
This course requires students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Immersive or Python for Finance Immersive before taking this course.
This course does not qualify for payment plans or student financing. See our Payment Plan FAQ to find related programs that qualify.
You may attend this training virtually (online) at the scheduled time the course is offered (New York, Eastern Time).
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There are no extra fees or taxes for our courses. The price you see on this page is the maximum you’ll pay us.
We don’t currently offer discounts as we do our best to affordably prices our courses.
