Python for Data and Finance

New York, 115W 30th St.
Python for Data and Finance
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  • Art Yudin
    Instructor
  • Beginner
    Skill Level
WE ARE OPEN FOR ONSITE and ONLINE BUSINESS
COVID NOTICE

We’ve taken several steps to protect our associates and students: all seats are located 6 ft apart, people are encouraged to wear masks, and we sanitize our classrooms regularly.

ABOUT THE COURSE

Python for Data and Finance is a comprehensive course with an emphasis on the practical application of Python to data analysis. Initially developed for Wall Street professionals, this course quickly became popular among people who crunch numbers, analyze big data and simply want to switch from spreadsheets to the faster and more efficient Python programming language.

WHAT TO EXPECT FROM THIS COURSE

Starting from scratch we will build a foundational understanding of the Python programming language. Afterwards we will gain understanding of NumPy and Pandas, Python libraries heavily used in data analysis and finance. Finally, we will cover Matplotlib, an essential tool for data visualization.

Who should attend:

The main goal of the Python for Data and Finance course is to acquire a modern tool for data analysis and shift from spreadsheets to Python. We spend a great deal of time on gathering data from different sources like Excel, the Web and APIs and manipulating information to solve real-life challenges. During this course we use practical examples, so you can apply Python to daily tasks at work. We are proud to say that many financial giants have used Python for Data and Finance to give their workforce a competitive edge.

WHAT WILL YOU LEARN

  • Introduction to Python
  • Reading/Writing CSV, Excel and TXT files with Python.
  • Introduction to NumPy
  • Manipulate data with Pandas
  • Data visualization with Matplotlib
  • Gathering data from Web and APIs
  • Financial Modeling with Python

Things To Remember

  • Please bring your own laptop to class.
  • We will help you to install all the programs you need in class.
  • If you withdraw one day before the course start date, any deposit paid will be refunded in full.
  • If you cannot attend classes for which you were charged, you could join next cohort and make up the missed classes.