Welcome to Robotic Process Automation

Welcome to Robotic Process Automation

Introduction to Robotic Process Automation (RPA) for Accountants and Finance Practitioners:

Robotic Process Automation (RPA) is revolutionizing the way accountants and finance professionals handle repetitive and rule-based tasks. With the rapid growth of Python as a programming language for automation purposes, coupled with the power of tools like Google Colab, accountants now have a formidable toolkit at their disposal to enhance efficiency and accuracy in their daily workflows.

Python's Role in Automation:

Python has emerged as a go-to programming language for automation due to its simplicity, versatility, and an extensive ecosystem of libraries and frameworks. Accountants can leverage Python to automate tasks like data entry, data validation, report generation, and more. Its readability and robust community support make it an ideal choice for streamlining financial processes.

• Data Retrieval: Python can fetch data from various sources, like databases and web APIs, automating data collection.

• Data Scraping from Websites: Python can scrape websites for financial data, news, or market trends using libraries like BeautifulSoup or requests.

• Data Cleaning: Automation scripts in Python can clean and preprocess data, ensuring accuracy and consistency.

• Custom Functions: Python allows you to create user-defined functions to reduce repetition and scale your automation efforts, making tasks like forecasting and financial modeling more efficient.

• Python Integration with Excel: Microsoft announced seamless integration of Python and Excel analytics. This feature enables users to input Python code directly into cells, run Python calculations in the Microsoft Cloud, and receive results, including plots and visualizations.

The Power of Google Colab for Automation:

Google Colab, a cloud-based Jupyter Notebook environment, is a tremendous learning tool and resource for accountants looking to automate tasks effectively. Its key advantages include access to free cloud resources, pre-installed libraries, and seamless integration with Google services. In this portal, we will mainly rely on Google Colab to demonstrate many of the automation flows and processes. Colab's collaborative capabilities, scheduled execution options, and the ability to access and process data from Google Drive make it a powerful learning tool for accountants and finance professionals seeking to automate routine processes.

Useful Environments and Installations

Google Colab

Google Colab set up. Click on embedded links below to open video and google colab.

Google Colab Setup

Access Google Colab:

Open your web browser and go to the Google Colab website: https://colab.research.google.com/ 

• Sign in with Google Account:

  • Click the "Sign In" button in the upper-right corner.

  • Sign in with your Google account. If you don't have one, you can create a Google account for free.

• Create a New Notebook:

  • After signing in, you'll be taken to the Colab dashboard.

  • Click the "New Notebook" button to create a new Jupyter Notebook. This will open a new tab with an empty notebook.

• Set Runtime Type:

  • In the new notebook, go to the "Runtime" menu at the top.

  • Select "Change runtime type" to configure the hardware acceleration and Python environment for your notebook.

  • You can choose between CPU, GPU, or TPU for hardware acceleration. For most tasks, CPU is sufficient, but GPU and TPU are available for more resource-intensive tasks.

  • Choose the Python version you want (typically Python 3).

• Working with Notebooks:

  • The notebook interface is similar to Jupyter Notebook. You can add code cells, text cells, and run code interactively.

  • To add a new code cell, click the "+ Code" button.

  • To add a new text cell, click the "+ Text" button.

  • To run a code cell, click the play button (▶) next to the cell or press Shift+Enter.

Anaconda Navigator Installation

Anaconda Navigator is useful for automating Python tasks because it provides isolated environments, package management, integration with popular IDEs, version control, and resource management. Its cross-platform compatibility and user-friendly interface simplify automation setup and execution, making it a valuable tool for running Python code efficiently.

Useful Online ancillary Resources for Python

Python Training Course from JP Morgan Chase

JPMorgan Chase, one of the world's leading financial institutions, has taken a proactive stance by introducing a Python training course accessible through their GitHub repository. This course serves as an introduction to numerical computing and data visualization using Python. It's meticulously designed to empower individuals without formal programming backgrounds, demonstrating how complex concepts can be made accessible through practical demonstrations.

ISLP a key resource for practitioners of Robotic Process Automation

Benefits for Students of  Robotic Process Automation (RPA): Python Integration: ISLP offers a practical approach, which is a popular programming language in the field of automation and RPA. Students can leverage Python's versatility to apply statistical models and machine learning algorithms to automate data-driven decision-making processes. Statistical Foundations: ISLP provides a solid foundation in statistical learning, which is essential for designing and fine-tuning automation processes. Replete with ISLP GitHub.  Another free online recommended text is Python for Data Science.

Python Automation full Tutorial

Python Automation Full Tutorial to perform common tasks free from CodeCamp.org. The series of learning modules proposed here will assist you in developing automation strategies for your own requirements.