Book Image

Robotic Process Automation Projects

By : Nandan Mullakara, Arun Kumar Asokan
Book Image

Robotic Process Automation Projects

By: Nandan Mullakara, Arun Kumar Asokan

Overview of this book

Robotic Process automation helps businesses to automate monotonous tasks that can be performed by machines. This project-based guide will help you progress through easy to more advanced RPA projects. You’ll learn the principles of RPA and how to architect solutions to meet the demands of business automation, along with exploring the most popular RPA tools - UiPath and Automation Anywhere. In the first part, you’ll learn how to use UiPath by building a simple helpdesk ticket system. You’ll then automate CRM systems by integrating Excel data with UiPath. After this, the book will guide you through building an AI-based social media moderator using Google Cloud Vision API. In the second part, you’ll learn about Automation Anywhere's latest Cloud RPA platform (A2019) by creating projects such as an automated ERP administration system, an AI bot for order and invoice processing, and an automated emergency notification system for employees. Later, you’ll get hands-on with advanced RPA tasks such as invoking APIs, before covering complex concepts such as Artificial Intelligence (AI) and machine learning in automation to take your understanding of RPA to the next level. By the end of the book, you’ll have a solid foundation in RPA with experience in building real-world projects.
Table of Contents (14 chapters)

Artificial intelligence (AI)

Everyone looking to get to the next stage of RPA implementation is adding different aspects of AI to their automation initiatives. As per Deloitte, initiatives that scale are more likely to use a combination of RPA and AI. According to their study, almost half (45 percent) of organizations scaling automation combine RPA and AI. The automation programs also report whether the automation initiatives meet or exceed their expectations.

Among AI, we are seeing lots of implementations with ML, computer vision, and Natural Language Processing (NLP). These are being used in specific use cases where AI is enabling smart detection, prediction, and execution; for example, to read emails (NLP), image or video processing (computer vision), and sentiment detection. As per a study conducted by Deloitte, the most popular AI solutions being implemented are ML-based solutions, expert or rule-based systems, and NLP-based solutions.

Let's look at two key areas where...