Wall Street Prep
Python for Financial Analysts
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Wall Street Prep Certification Program

Python for Financial Analysts

3 Courses
47h 22m
5,033 Students

Work on the cutting edge of financial analysis by understanding and using the Python coding language, the backbone of modern quantitative finance solutions. Learn Python programming from the ground up, with no previous programming experience required, and get the skills you need to excel in today's world.

Harness the Power of Python for Financial Analysis

Learn Python for Finance
By the end of your journey, you'll have mastered advanced functional programming topics such as closures and decorators, crucial to the use of Python by finance professionals.
  • No Coding Experience Necessary With 40+ hours step-by-step video and access to examples with fully-annotated Jupyter code notebooks, you'll have all the tools you need to learn Python programming from the ground up — all the way to loading data from various sources, manipulating, exploring, analyzing, and charting data sets.
  • Taught by An Experienced Software Engineer Our Python courses are led by a software engineer with a math PhD and over 20 years of development experience in a variety of fields, ranging from data warehousing to REST API development.
  • Get Mastery By Grasping Concepts Learn not just Python syntax, but how Python actually works at a fundamental level — allowing you to write better, cleaner and more effective programs. By the end of your journey, you'll have mastered advanced functional programming topics such as closures and decorators, crucial to the use of Python by finance professionals.

What You'll Learn

Overview: What You'll Learn
  • Basic and advanced Python data types.
  • Functional and Object Oriented Programming.
  • Closures and Python decorators.
  • Exception handling.
  • Datetime and timezone handling.
  • Reading and writing CSV files.
  • JSON and making REST API requests.
  • Using NumPy for highly efficient calculations.
  • Using Pandas for loading and analyzing data sets.
  • Using Matplotlib for generating charts.
Course 1: Introduction to Python
In this introduction to Python you will learn:
  • How to install Python.
  • How to create and use virtual environments (and why you should use them).
  • How to program in Python using Jupyter Notebooks.
  • Boolean (True/False) data type and algebra (and/or/not).
  • Numeric types, including integers and floats.
  • Sequence types (lists, tuples, strings).
  • What Unicode is
  • Dictionaries and sets.
  • Looping (for, while).
  • Conditional execution (if...elif...else).
  • Comprehensions.
  • Writing and using functions, including lambda functions.
  • Built-in functions such as round, sorted, min, max and zip.
Course 2: Intermediate Python
Expand on the basics covered in Course 1 and learn more advanced Python programming concepts. You'll cover:
  • Higher-order functions.
  • Closures.
  • Python Decorators.
  • Importing modules.
  • Reading/writing text files.
  • Reading/writing CSV files.
  • The 'Decimal' type as a more precise alternative to floats.
  • Epochs, dates, times and timezones using native Python.
  • The 'math', 'statistics' and 'random' standard library modules.
  • Creating custom classes.
Course 3: Third-Party Python Libraries
Continue on to focus on a number of commonly-used third-party libraries that are very useful in data analysis. These include:
  • The 'pytz' and 'dateutil' libraries for dealing with dates, times and timezones.
  • The 'requests' library to query Web APIs and ingest JSON data.
  • The 'Numpy' library for highly efficient manipulation of arrays and matrices.
  • The 'Pandas' library for easy and powerful data table manipulations.
  • The 'Matplotlib' library for charting data.
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This program is for analysts that want to leverage Python to:

  • Explore, analyze and visualize data
  • Manipulate data using automated and repeatable processes
  • Gain knowledge of specialized Python third-party libraries
  • Learn how Python works and master best practices

What's Included

Introduction to Python

In this course, you'll learn how to leverage the Python computer coding language to level up your financial analysis skills. We'll help you understand how to use Python to explore, analyze, and visualize data, and to manipulate data using automated and repeatable processes. You'll gain the fundamental Python knowledge needed to explore and leverage ...
In this course, you'll learn how to leverage the Python computer coding language to level up your financial analysis skills. We'll help you understand how to use Python to explore, analyze, and visual ...
In this course, you'll learn how to leverage the Python computer coding language to level up your fi ...
View Course TOC

Intermediate Python

In this course, you will expand on the basics learned in "Introduction to Python" and learn more advanced Python programming concepts to apply in a career as a financial analyst. You will learn about higher-order functions; closures; Python decorators; importing modules; reading/writing text files; reading/writing CSV files; the 'Decimal' type as a ...
In this course, you will expand on the basics learned in "Introduction to Python" and learn more advanced Python programming concepts to apply in a career as a financial analyst. You will learn about ...
In this course, you will expand on the basics learned in "Introduction to Python" and learn more adv ...
View Course TOC

Third-Party Python Libraries

In this third and final course in our series on Python for Financial Analysts, we'll focus on a number of very commonly used third-party libraries highly useful in data analysis. These include: the pytz and dateutil libraries for dealing with dates, times and timezones; the requests library to query Web APIs and ingest JSON data; the Numpy library ...
In this third and final course in our series on Python for Financial Analysts, we'll focus on a number of very commonly used third-party libraries highly useful in data analysis. These include: the py ...
In this third and final course in our series on Python for Financial Analysts, we'll focus on a numb ...
View Course TOC

Course Samples

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Introduction to Python: Course Overview
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The Range Function - Coding
watch video
Introduction to Sorting and Filtering
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Reading Text Files - Coding
watch video
Introduction to Pandas
watch video
Charting with mplfinance - Coding

Get the Python for Financial Analysts Certification

Trainees are eligible to take the WSP Python for Financial Analysts Certification Exam for 24 months from the date of enrollment. Those who complete the exam and score above 80% will receive the certification. The exam is a challenging 2-hour online examination covering the most difficult concepts covered in the program.

Course Highlights

  • Used on the Street

    This is the same comprehensive course our corporate clients use to prepare their analysts and associates.

  • Real Coding Examples

    You'll learn-by-doing by using fully-annotated Jupyter code notebooks as you work through the course; no coding experience necessary.

  • Taught by experienced software developers

    Our instructor is a software engineer with a math PhD and over 20 years of real-world development experience.

  • Instructor Support

    Have a question on course content? Communicate directly with instructors by asking questions throughout the course.

Frequently Asked Questions

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Earn CPE Credits with WSP Online Courses

CPE logo Wall Street Prep 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: www.nasbaregistry.org.
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