Navigating Financial Data with Python

Elevate your financial analytics skills with Python for Finance, exploring cutting-edge techniques for data retrieval, time series analysis, and predictive modeling.

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unfold_more19 exercises
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An outline of this training course

This course comprehensively covers the application of Python in financial analysis. Starting with an introduction to Python's capabilities in the financial sector, it progresses through acquiring financial data from sources like Yahoo Finance and NASDAQ API. The course then delves into time series analysis, exploring data plotting, financial libraries, and creating custom functions for financial metrics. Advanced sections include forecasting with the Facebook Prophet model and practical, hands-on exercises in Google Colab, emphasizing interactive and applied learning in financial data prediction and analysis.


What are needed to take this course 

Participants should have a basic understanding of Python programming, including variables, loops, and functions, as well as some familiarity with fundamental financial concepts. Access to a computer with internet connectivity is essential for accessing course materials and using APIs. Participants should have Python installed, preferably the latest version, and be comfortable with an Integrated Development Environment (IDE) like Jupyter Notebook or Google Colab. Knowledge in using Python libraries such as pandas, NumPy, and matplotlib, commonly employed in financial data analysis, is also beneficial. Above all, a keen interest and willingness to learn and experiment with Python in the realm of finance is crucial for making the most out of this course.


Who is this course for

Tailored for a diverse audience, including financial analysts, data scientists, investment bankers, portfolio managers, and students in finance or economics. It is also well-suited for Python programmers looking to venture into finance, DIY investors and traders seeking to enhance their portfolio analysis skills, and anyone with a foundational understanding of Python and basic finance concepts. This course caters to those interested in leveraging Python's powerful data analysis capabilities for financial applications, making it ideal for professionals and enthusiasts at the intersection of finance and technology.



Details of what you will learn during this course

By the end of this course, you will:

  • Master the retrieval and manipulation of financial data from sources like Yahoo Finance and NASDAQ API using Python.
  • Conduct in-depth time series analysis and implement financial indicators such as moving averages.
  • Utilize Python’s financial libraries for advanced data visualization and analysis.
  • Develop custom functions and metrics for detailed financial analysis.
  • Learn to create and fine-tune predictive models for financial forecasting, focusing on the Facebook Prophet model.
  • Apply these skills in real-world scenarios through practical exercises in Google Colab, enhancing hands-on experience in financial data analysis.


What you get with the course

  • Over two hours of intensive training videos
  • Resource pack for practical application


Program Level

Intermediate to Advanced


Field(s) of Study

Data Science and Analysis, Econometrics, Business Intelligence


Instruction Delivery Method


QAS Self-study


***This course was published in January 2024


Enterprise DNA is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website:



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Course Overview




Foundations of Financial Analysis with Python


Data Retrieval and Initial Processing


Advanced Data Analysis Techniques


Comparative Analysis and Metrics


Forecasting Financial Trends


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