Process Automation Using AI
Professor
Valdis Saulespurens
About the professor
Valdis Saulespurēns has been implementing various AI solutions for more than 20 years. In addition to teaching programming courses at RTU and RBS, Valdis uses machine learning for big data aggregation, processing, and analysis at the National Library of Latvia.
Course Description
This course empowers professionals to harness the power of artificial intelligence to optimize and automate business processes. By exploring the applications of AI across various functional areas, participants will gain the skills to identify automation opportunities, select appropriate tools, and implement AI-driven solutions. Through a combination of theoretical knowledge and practical exercises, this course equips individuals to enhance operational efficiency, reduce costs, and drive business growth. By the end of the course, participants will be able to measure the ROI of AI initiatives and demonstrate their impact on overall business performance.
Course Goals
Provide an understanding of AI and its application in business process automation.
Develop skills to choose and apply AI tools for automation of specific processes.
Teach practical design and implementation of AI solutions that improve company efficiency.
Demonstrate real examples of AI being used for process automation in various industries.
After the course participants will be able to:
Assess automization opportunities
Select the most appropriate AI tools
Contribute to the optimization of business processes
Make business decisions related to the application of AI
Course will be:
Online and In Person
Prerequisites
- Basic knowledge of data processing and business process management.
- A basic understanding of IT technology and programming is preferred but not required.
- Interest in the application of technology in business improvement.
Teaching methods used:
- Theoretical lectures with practical examples.
- Hands-on tasks using AI tools and platforms.
- Group discussions and case studies.
- Solving real-world problems using AI technologies.
- Teacher’s advice and feedback on participants’ work.
Topic 1
Introduction to AI and process automation
What is artificial intelligence? The role and applications of AI in business.
The basics of process automation and its benefits.
AI technologies and their applications in automation.
Examples and case studies: How companies are using AI in process automation.
Topic 2
Data processing and creation of AI models
Importance of data in AI process automation.
Data preparation and cleaning for building AI models.
Building machine learning models for process automation.
Hands-on lesson: Building an AI model for a data processing task.
Topic 3
Integration of RPA and AI in process automation
A combination of Robotic Process Automation (RPA) and AI.
Integration of AI and RPA technologies in business processes.
Practical examples and tools: How to combine RPA and AI to automate complex tasks.
Hands-on lesson: Developing an AI solution using RPA and AI tools.
Topic 4
Implementation of AI solutions and evaluation of effectiveness
Integration of AI solutions into existing enterprise systems.
Evaluating and optimizing the effectiveness of solutions.
Risk management and challenges in implementing AI solutions.
Professor
Valdis Saulespurens
About the professor
Valdis Saulespurēns has been implementing various AI solutions for more than 20 years. In addition to teaching programming courses at RTU and RBS, Valdis uses machine learning for big data aggregation, processing, and analysis at the National Library of Latvia.
About the professor
Valdis Saulespurēns has been implementing various AI solutions for more than 20 years. In addition to teaching programming courses at RTU and RBS, Valdis uses machine learning for big data aggregation, processing, and analysis at the National Library of Latvia.
Course Description
This course empowers professionals to harness the power of artificial intelligence to optimize and automate business processes. By exploring the applications of AI across various functional areas, participants will gain the skills to identify automation opportunities, select appropriate tools, and implement AI-driven solutions. Through a combination of theoretical knowledge and practical exercises, this course equips individuals to enhance operational efficiency, reduce costs, and drive business growth. By the end of the course, participants will be able to measure the ROI of AI initiatives and demonstrate their impact on overall business performance.
Course Goals
Provide an understanding of AI and its application in business process automation.
Develop skills to choose and apply AI tools for automation of specific processes.
Teach practical design and implementation of AI solutions that improve company efficiency.
Demonstrate real examples of AI being used for process automation in various industries.
After the course participants will be able to:
Assess automization opportunities
Select the most appropriate AI tools
Contribute to the optimization of business processes
Make business decisions related to the application of AI
Course will be:
Online and In Person
Prerequisites
- Basic knowledge of data processing and business process management.
- A basic understanding of IT technology and programming is preferred but not required.
- Interest in the application of technology in business improvement.
Teaching methods used:
- Theoretical lectures with practical examples.
- Hands-on tasks using AI tools and platforms.
- Group discussions and case studies.
- Solving real-world problems using AI technologies.
- Teacher’s advice and feedback on participants’ work.
Topic 1
Introduction to AI and process automation
What is artificial intelligence? The role and applications of AI in business.
The basics of process automation and its benefits.
AI technologies and their applications in automation.
Examples and case studies: How companies are using AI in process automation.
Topic 2
Data processing and creation of AI models
Importance of data in AI process automation.
Data preparation and cleaning for building AI models.
Building machine learning models for process automation.
Hands-on lesson: Building an AI model for a data processing task.
Topic 3
Integration of RPA and AI in process automation
A combination of Robotic Process Automation (RPA) and AI.
Integration of AI and RPA technologies in business processes.
Practical examples and tools: How to combine RPA and AI to automate complex tasks.
Hands-on lesson: Developing an AI solution using RPA and AI tools.
Topic 4
Implementation of AI solutions and evaluation of effectiveness
Integration of AI solutions into existing enterprise systems.
Evaluating and optimizing the effectiveness of solutions.
Risk management and challenges in implementing AI solutions.