Intelligent Automation

Intelligent Automation

Intelligent Automation (IA) consists in the use of digital technologies such as Robotic Process Automation (RPA) and Artificial Intelligence (A.I.) to bring technology-based intelligence in your business processes.

IA is a key ingredient for the the success of the digital businesses today and in the future as it provides the needed effectiveness and efficiency for a sustainable competitiveness. Yet choosing the right technological partner or the most effective deployment model may be a bit cumbersome.

As such, you need the experts that have both the knowledge and the practical experience in the design, deployment and maintenance of complex solutions, integrating your legacy systems with new, state-of-the-art technologies in a sound and efficient enterprise architecture. And once the IA solutions are deployed in production you also need the internal skills and governance to run the new breed of your business.

Our trainers are leading experts in both the fields of RPA – certified UiPath instructors – and the growing academic research of Machine Learning and wider Artificial Intelligent applications. They will provide to you clarity and practical examples on how to integrate such technologies in your current business practice such as to increase competitiveness of your business.

Machine Learning Course

Nowadays strong advances in Artificial Intelligence and Machine Leaning make feasible applications that years ago were thought to be pure fantasy. In the process of digitizing your company AI/ML tools can help either in practical products or in better organization that will increase your efficiency.

The course aims to familiarize the attendees with basic terminology and key concepts in Artificial Intelligence and respectively Machine Learning. We aim to explain some core principles in designing artificial systems. The introduction will define what an AI system is and can do, while the following sections will describe methods and tools to address key concepts such as data, redundancy, optimization, solution quality. While AI/ML has strong theoretical foundations, it contains stochastic components that are unpredictable and, thus, user experience is a strong ingredient into this direction. We initialize this process by emphasizing practical applications, such as data understanding in the highly popular Excel and respectively by designing some simple solution with full implementation into Python.

Who Should Attend

Manager and expert level business employees that are interested in understanding the potential of ML for their business. Course participants should preferably have some background in mathematics or computer science.

Course objectives:

1 .To present key concepts and limitation of an AI/ ML system  

2. To familiarize the attendee with basic terminology in the field

3. To deliver some simple and easy to understand principles of design and use

4. To introduce practical tools that will speed-up the transition from spectator/enthusiast to hands- on user


  1. Introduction to AI/ML (1.5 – 2h)
    1. Key definitions: intelligent system, data, mapping, objective, stochastic-deterministic
    1. Practice: quiz to apply the formulated definitions
  2. Data understanding (1.5 – 2h)
    1. Introduction to statistics: mean, variance, correlation, bias, redundancy, entropy
    1. Practice via Excel:
      1. Outlier identification in “Call-center dataset
      1. Estimation of data bias in “Call-center” dataset
  3. Solving complex problems with Machine Learning(3-4h):
    1. Key concepts: Data, learning system, optimization, loss function
    1. Practice: Data cleaning in Python
    1. Popular learning system: applications and limitations
    1. Practice: Prediction and classification with Python – Application specific to attendees profile

Teaching method and materials

Teaching method:

Information is available as presentation, but teaching is with marker and whiteboard (flipchart) . Illustrative examples on Laptop. Practical application in Excel (LibreOffice, FreeOfice), and some little code in Python

Requirements: it would be nice but not required for attendees to have laptops and access to WiFi

In addition to the workshops and materials provided to you during this Module, we will also provide further reading materials and other resources as well as guidance into the vast array of relevant information sources available in the public domain like the ones below (provided for exemplification purposes only):

Robotic Process Automation

One of the best way to understand RPA and develop Intelligent Automation skills is to take one of the free learning paths of the UiPath Academy.

Artificial Intelligence

There are several outstanding resources available in the public space deep diving into the topic of AI:

YouTube Originals | The Age of A.I.