Blue Prism
Blue Prism
Module 1: Introduction to Robotics and RPA
- Definition and scope of Robotics and RPA
- Historical development and milestones
- Current and future applications
- Role of Robotics in industrial automation
- Advantages and challenges of integrating Robotics in processes
Module 2: Basics of Robotics
- Sensors, actuators, and effectors
- Control units and processors
- Communication interfaces
- Robot motion and positioning
- Forward and inverse kinematics
- Dynamics of robot movement
Module 3: Programming Languages for Robotics
- Overview of programming languages used in Robotics
- Selecting the right language for specific tasks
- Practical coding sessions using common Robotics programming languages
- Debugging and optimization techniques
Module 4: Control Systems
- Basics of feedback systems
- Closed-loop control
- Proportional, Integral, and Derivative control
- Tuning PID controllers for optimal performance
Module 5: Machine Learning for Robotics
- Introduction to machine learning concepts
- Supervised and unsupervised learning
- Training robots using machine learning algorithms
- Case studies of ML applications in Robotics
Module 6: Robotics Process Automation (RPA)
- Defining RPA and its significance
- Key components and terminology in RPA
- Overview of popular RPA tools (e.g., UiPath, Blue Prism)
- Comparison and selection criteria
- Real-world scenarios where RPA can be applied
- Analyzing the impact of RPA on business processes
Module 7: RPA Development
- Designing and developing RPA workflows
- Handling exceptions and errors in RPA processes
- Scripting languages for customizing RPA solutions
- Advanced coding techniques for RPA development
- Integrating RPA with enterprise systems (e.g., ERP, CRM)
- Data exchange and communication protocols
Module 8: Cognitive Automation
- Understanding cognitive computing in the context of RPA
- Cognitive automation vs. traditional RPA
- Incorporating NLP for text analysis and understanding
- Building language models for RPA bots
- Implementing image recognition for process automation
- Pattern matching techniques in RPA
Module 9: Case Studies and Projects
- Examining successful implementations of Robotics and RPA
- Learning from industry case studies
- Applying learned concepts to real-world scenarios
- Developing and presenting RPA projects