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PyForward - Python Data Analysis with Pandas and NumPy
Rating: 5.0 out of 5(9 ratings)
38 students

PyForward - Python Data Analysis with Pandas and NumPy

Learn how to automate manual processes, analyze big data, and best practices with data analysis and statistics.
Last updated 9/2025
English

What you'll learn

  • Python
  • Data Analysis
  • Computational Analytics
  • Pandas
  • NumPy
  • Python Data Analysis
  • Financial Data Analysis
  • History of Computer Science
  • History of Computational Analytics
  • Computer Science
  • Computational Analytics

Course content

5 sections28 lectures3h 2m total length
  • Welcome to the Course0:35

    Test

  • About Your Instructor0:33

    Keith Alexander Ashe spent his career using data and technology to transform processes and systems. Although he took a couple programming courses in high school and college; he ultimately used weekend projects, self-paced learning, and on-the-job experience to become a full stack software developer. Mr. Ashe previously worked at Booz Allen, Gartner, Citibank, Happy Money, and Rollbar before launching his own consulting firm, Ordinal Prime.


    His last project was working as a contractor with the Bill & Melinda Gates Foundation's Institute for Disease Modeling to prepare Starsim for a public beta release. Starsim is an open-source, stochastic disease simulation modeling tool built using Python.


    He created the PyForward training series because he wanted to make it easier for others to start coding in Python. He is a graduate of Florida A&M University and Columbia University with a BS and MS in Industrial Engineering, respectively. He also earned a Lean Six Sigma Blackbelt from Villanova University.

  • Outline and Objectives

    Course Outline

    • Getting Started

    • A Brief History of Computing

    • Number Systems

    • Bits and Bytes

    • Data Analysis Best Practices

    • Data in the Enterprise

    • Process Improvement

    • Thinking Like a Programmer

    • Intro to AI, ML, DS

    • Python Basics

      • Getting Started

      • Data Structures

      • Pandas and NumPy Libraries

    • Self-Paced Worksheets

    • Data Analysis with Python

    • Creating a Python Cheat Sheet

    • Landing a Job

    • Next Steps & Resources

  • Helpful Hints3:32

    As I mentioned, learning can be difficult but I've designed this course to make it easier to tackle complex topics. This session provides a few tricks and tips that I've picked up throughout my career to make sure that I can effectively learn and apply new knowledge.

Requirements

  • No programming experience. Familiarity with mathematics up to Algebra.

Description

Start Your Journey in Coding and Data Analysis

PyForward gives you the tools to build freedom, resilience, and career sustainability in today’s uncertain economy. You’ll write and understand your first lines of code, learn Python fundamentals, and complete your first data analysis project. With Python, tasks that take hours in Microsoft Excel can be done in minutes or seconds, saving you valuable time and boosting efficiency. You’ll also discover next steps: finding projects, showcasing your work, improving your resume, networking, and landing a job in finance, technology, or data science.


Learn How and Where to Run Python Code with Runsheets

In this course, you’ll get step-by-step video guides to the most popular Python coding environments, including Anaconda Navigator, Anaconda Cloud, and Jupyter Notebook. To make learning easier, we provide Runsheets—Jupyter Notebook files preloaded with code, documentation links, key explanations, and helpful coding tips. These Runsheets let you learn by doing: you can run the code, see the results instantly, and experiment at your own pace. They’re included for:

  • Python Input and Output methods

  • Python Basics

  • Pandas and NumPy

  • Lambda functions

  • A complete Python Data Analysis project

Runsheets are a powerful companion to the video lessons, helping new and aspiring coders build confidence in real coding environments. You’ll practice writing, editing, and executing Python code while reinforcing key concepts and workflows. By the end, you’ll feel comfortable navigating professional Python tools and completing hands-on projects.


Why Python for Data Analysis and Finance?
Python is one of the fastest-growing programming languages—integrated with Microsoft Excel, central to AI and machine learning, and used in orchestration tools including AWS Lambda, Apache Airflow, and KNIME. In finance, it drives automation, reduces reporting and reconciliation times, eliminates End User Computing (EUCs), and helps firms meet regulatory requirements. Learning Python for finance and data analysis now means being ahead of the curve in your team and your industry.


What You’ll Learn:

  • Write and understand Python code confidently

  • Complete your first real-world Python data analysis project

  • Automate Excel tasks and streamline financial reporting

  • Apply Python in finance for compliance, reconciliation, and process automation

  • Build a foundation for AI, machine learning, and modern data visualization tools

Who This Course Is For:

  • Finance professionals looking to future-proof their careers with Python for finance

  • Students or career changers exploring data analysis with Python

  • Anyone who wants to gain a high-demand skill with practical business impact

Your Career Advantage:

  • Freedom – Work on your own terms: in-office, hybrid, or remote

  • Resilience – High-demand skills make you more valuable and secure

  • Sustainability – Future-proof your career as AI and data transform industries

By the end of this course, you’ll have completed your first coding project in Python, mastered core Python for data analysis skills, and positioned yourself to thrive in a fast-changing professional world.

Who this course is for:

  • Finance professionals, data analysts, and aspiring software and data engineers.
  • Beginner Python developers interested in data science and software engineering