Cognitive Solutions and RPA Analytics faq

learnersLearners: 579
instructor Instructor: Automation Anywhere, Inc. instructor-icon
duration Duration: instructor-icon

This course will introduce you to cognitive automation and RPA analytics. You will learn how to deploy cognitive automation using Artificial Intelligence (AI) and Automation Anywhere’s cognitive solution, IQ Bot. You will also explore how RPA analytics help interpret and improve automated business processes. You will learn to use the Web Control Room for Operational Analytics and Bot Insight for Business Analytics and CoE Analytics. Finally, you will learn how to use the RPA mobile app to study and edit the default CoE dashboard.

Course Feature Course Overview Pros & Cons Course Provider
Go to class

Course Feature

costCost:

Free

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

10th Jul, 2023

Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 17th, 2023]

This course provides an overview of cognitive solutions and RPA analytics. It covers topics such as cognitive automation, AI, Automation Anywhere’s cognitive solution, IQ Bot, RPA analytics, Web Control Room, Bot Insight, and the RPA mobile app. Participants will learn the six steps to deploy cognitive automation, how to use the IQ Bot portal, and how to generate RPA analytics. They will also explore the different types of RPA analytics and learn how to use the RPA mobile app.

[Applications]
Upon completion of this course, participants will be able to apply cognitive automation to extract semi- or unstructured data, interpret large volumes of data in near real-time, and generate actionable information. They will also be able to use Automation Anywhere's IQ Bot portal to develop cognitive IQ bots, and use the Web Control Room and Bot Insight to generate RPA analytics. Additionally, they will be able to use the RPA mobile app to study and edit the default CoE dashboard published via Bot Insight.

[Career Paths]
Recommended Career Paths:
1. Cognitive Solutions Developer: Cognitive solutions developers are responsible for developing and deploying AI-based solutions to automate business processes. They must have a strong understanding of AI and machine learning algorithms, as well as the ability to design and develop software applications. The demand for cognitive solutions developers is growing rapidly, as more companies are looking to leverage AI to improve their operations.

2. RPA Analytics Consultant: RPA analytics consultants are responsible for helping companies understand and interpret the data generated by their RPA bots. They must have a strong understanding of data analysis and visualization techniques, as well as the ability to develop custom dashboards and reports. The demand for RPA analytics consultants is growing, as more companies are looking to leverage RPA to improve their operations.

3. AI/ML Engineer: AI/ML engineers are responsible for developing and deploying AI-based solutions to automate business processes. They must have a strong understanding of AI and machine learning algorithms, as well as the ability to design and develop software applications. The demand for AI/ML engineers is growing rapidly, as more companies are looking to leverage AI to improve their operations.

4. Data Scientist: Data scientists are responsible for analyzing and interpreting large volumes of data to generate insights and actionable information. They must have a strong understanding of data analysis and visualization techniques, as well as the ability to develop custom dashboards and reports. The demand for data scientists is growing, as more companies are looking to leverage data to improve their operations.

[Education Paths]
Recommended Degree Paths:
1. Bachelor's Degree in Computer Science: This degree path provides students with the foundational knowledge and skills needed to understand and develop computer systems, software, and applications. It also covers topics such as algorithms, data structures, operating systems, and computer architecture. With the increasing demand for automation and AI, this degree path is becoming increasingly popular.

2. Master's Degree in Artificial Intelligence: This degree path focuses on the development of AI systems and their applications. It covers topics such as machine learning, natural language processing, computer vision, and robotics. This degree path is ideal for those who want to specialize in the development of AI systems and their applications.

3. Master's Degree in Data Science: This degree path focuses on the analysis and interpretation of large datasets. It covers topics such as data mining, machine learning, and predictive analytics. This degree path is ideal for those who want to specialize in the analysis and interpretation of large datasets.

4. Doctoral Degree in Cognitive Science: This degree path focuses on the study of the mind and its processes. It covers topics such as cognitive psychology, neuroscience, and artificial intelligence. This degree path is ideal for those who want to specialize in the study of the mind and its processes.

Pros & Cons

Pros Cons
  • pros

    Great Course

  • pros

    Industry it represents sounds good

  • pros

    Positive feedback

  • cons

    Inaccurate project tool

  • cons

    Poor support

  • cons

    Software for projects not working

Course Provider

Provider Coursera's Stats at OeClass