What You Need to Know Before
You Start

Starts 7 June 2025 16:56

Ends 7 June 2025

00 days
00 hours
00 minutes
00 seconds
course image

The Complete Course for Generative AI for RPA

Master Generative AI for RPA and learn Efficient Automation, Optimization and scalability in RPA with Blue Prism!
via Udemy

4052 Courses


1 hour 19 minutes

Optional upgrade avallable

Not Specified

Progress at your own speed

Paid Course

Optional upgrade avallable

Overview

Generative AI is a branch of artificial intelligence that focuses on creating models capable of generating new, human-like content such as text, images, music, or code. It is underpinned by deep learning and neural networks, which allow machines to learn patterns from vast datasets and produce novel outputs.

Unlike traditional AI systems designed to perform specific tasks or make decisions based on predefined rules, generative AI models aim to simulate creativity by creating original and contextually relevant content.

Syllabus

  • Introduction to Generative AI
  • Overview of AI and RPA
    What is Generative AI?
    History and evolution of Generative AI technologies
    Importance of Generative AI in RPA
  • Fundamentals of Deep Learning and Neural Networks
  • Basics of deep learning
    Understanding neural networks
    Key architectures: CNNs, RNNs, LSTMs, and Transformers
    Training and optimizing neural networks
  • Generative AI Models
  • Types of generative models: GANs, VAEs, and autoregressive models
    Generating text: NLP and language models
    Image generation: applications and techniques
    Music and code generation: tools and frameworks
  • Tools and Platforms for Generative AI
  • Introduction to popular frameworks (TensorFlow, PyTorch)
    RPA tools and integration with generative models
    Setting up development environments
  • Designing Generative AI Applications for RPA
  • Identifying RPA use cases for generative AI
    Building prototypes of generative AI applications for RPA
    Case studies and real-world examples
  • Implementation and Deployment
  • Best practices for deploying generative AI in RPA
    Monitoring and maintaining AI models
    Ethical considerations and bias in generative AI systems
  • Future of Generative AI in RPA
  • Emerging trends and technologies
    Challenges and opportunities in advancing generative AI
    Long-term impact on industries and workflow automation
  • Course Summary and Project Work
  • Recap of key concepts and methodologies
    Final project: create a generative AI application for a specific RPA use case
    Assessments and feedback mechanisms

Taught by

Narsi Naidu Chilla


Subjects

Business