Robotic Process Automation (RPA)

5.

Advanced RPA and Intelligent Automation

5.1.

Cognitive Automation

5.1.1.

AI and ML Integration

5.1.1.1.

5.1.1.2.

Model Deployment

5.1.2.

Natural Language Processing

5.1.2.1.

Text Extraction

5.1.2.2.

Sentiment Analysis

5.1.3.

Character Recognition Technologies

5.1.3.1.

Optical Character Recognition

5.1.3.2.

Intelligent Character Recognition

5.1.3.3.

Document Digitization

5.1.3.4.

Handwriting Recognition

5.1.4.

Machine Learning Applications

5.1.4.1.

Predictive Analytics

5.1.4.2.

Classification Models

5.1.4.3.

Regression Models

5.2.

Process Mining and Discovery

5.2.1.

Automated Discovery Tools

5.2.1.1.

Event Log Analysis

5.2.1.2.

Process Mapping Automation

5.2.2.

System Log Analysis

5.2.2.1.

Bottleneck Identification

5.2.2.2.

Process Optimization Insights

5.3.

Analytics and Reporting

5.3.1.

Performance Dashboards

5.3.1.1.

Real-Time Monitoring

5.3.1.2.

Customizable Metrics

5.3.2.

Business Outcome Measurement

5.3.2.1.

Cost Savings Tracking

5.3.2.2.

Productivity Metrics

5.3.3.

Predictive Analytics

5.3.3.1.

5.3.3.2.

Proactive Issue Detection

Previous

4. RPA Development Fundamentals

Go to top

Next

6. RPA Governance and Scaling