Practical methods for explainable AI/machine learning models
Wednesday, 16th December 2020 | 14:30 p.m. – 17:30 p.m. | 2,5 CPD
Wednesday, 16th December 2020 | 14:30 p.m. – 17:30 p.m. | 2,5 CPD
Until recently, the main driver for investment in Machine Learning (ML) and Artificial Intelligence (AI) has been to gain competitive edge. Nowadays, it is apparent that these technologies are becoming a necessity within the 4th industrial revolution context. All these advancements provide stakeholders with the benefit of AI-powered decision-making, which allows enterprises to improve their operational efficiencies and increase their productivity, revenue and ROI.
However, enterprise adoption has been limited, in part due to the inability of the algorithms to explain their actions. Machine learning models can be non-intuitive and difficult to understand, therefore business owners feel unsure about what their AI/Machine learning models are doing. This webinar will cover methodologies for interpreting AI/Machine Learning driven processes, since this knowledge is considered crucial for several industries, including financial services.
Join the webinar (14:00 p.m. – 14:30 a.m.)*
Sessions (14:30 p.m. – 17:30 p.m. including two 15-minute breaks between sessions)
- Introduction: Seminar’s Objectives
- What is AI & ML?
- Why AI & ML need to provide explanations
- How to select the right ML algorithm for a business problem
- Methodologies for interpreting Machine Learning models
- Examples of use cases of interpretable AI / ML models in business
- Summary and Conclusion.
*Note: Please join the meeting 30 minutes prior to the webinars’ start time (join at 14:00 p.m.), in order to make sure that you do not face any connection difficulties or any other technical issues.
This webinar is ideal for Developers, Data Scientists, AI Engineers, Analysts and technical leaders who want to add a layer of interpretability on top of their machine learning models. The webinar is also addressed to business leaders who wish to learn how to translate and better understand algorithmic model outcomes in order to be able to make informed decisions.
To register for the webinar, please complete the registration form. Once your registration is submitted, you will receive an email stating the participation fee, including any discounts, if applied. Kindly note that the payment should be made at least two days prior to the webinar’s date, in order for your registration to be confirmed.
*Last Date for 10% Early Bird Discount: 02/12/2020
Other discounts available:
- For more than two (3+) participants from the same company a 10% discount is available on the total cost, before the VAT and HRDA subsidy. This discount only applies for participants who enrol in the same seminar/webinar, on the same day. This discount can only be combined with the early bird discount and the HRDA subsidy, when applicable.
- For individuals/legal entities who/which register in more than two (3+) seminars/webinars during the same semester (January-June & July-December), a 10% discount is available on the total cost, before the VAT and HRDA subsidy. This discount only applies for individuals/legal entities who/which enrol in more than two (3+) seminars/webinars during the same semester, on the same day. This discount can only be combined with the early bird discount and the HRDA subsidy, when applicable.
- There is a 10% discount for alumni members. This discount should be applied before the VAT and HRDA subsidy and can only be combined with the early bird discount and the HRDA subsidy, when applicable.
- There is a 10% Early Bird discount on selected seminars/webinars for participants who enrol in a training course until a specific date which is stated above. This discount should be applied before the VAT and HRDA subsidy and can only be combined with the HRDA subsidy, when applicable.
- HRDA subsidy for all HRDA approved seminars/webinars.
For any queries, please contact Irini Avraam on +357 22 207 460 or at firstname.lastname@example.org.
CPD: This webinar may contribute to Continuing Professional Development requirements. Shortly after the webinar’s date, participants will receive electronically a certificate of attendance confirming the total number of training hours (2,5 CPD).
Senior Manager, Digital Innovation Lead, Management Consulting, KPMG in Cyprus
Konstantinos holds a BEng and an MEng in Electrical and Computer Engineering from the National Technical University of Athens. He also holds an MSc in Advanced Computing from the Imperial College London.
Konstantinos is a Senior Manager in the Management Consulting department of KPMG in Cyprus, leading the Digital Innovation team. Konstantinos has extensive hands-on experience in designing and developing innovative digital solutions in various platforms for a range of organisations in different industries. He is also involved in product development services.
Furthermore, Konstantinos has extensive knowledge in modern web and mobile technologies. More specifically, he applies the Artificial Intelligence and Machine Learning technologies and provides end-to-end digital solutions in order to solve business problems of clients.
Assistant Manager, Management Consulting, KPMG in Cyprus
Danis possesses more than five years of experience in the field of Artificial Intelligence and Data Science. He is currently a member of the Digital Innovation team, developing digital solutions for the retail, telecom and financial services sectors. He has hands-on experience on a variety of digital innovation technologies, such as Artificial Intelligence and Intelligent Automations. He has extensive knowledge of helping clients to interpret and understand the cause and effect of Artificial intelligence algorithms.
Danis has developed and delivered training workshops such as the “Introduction to Artificial Intelligence for business” and the “Introduction to data visualisation and advanced concepts in machine learning”.
Danis also worked in the UK as a Data Scientist and as a Data Science Contractor for a multi-national corporation. During his employment, he developed a variety of solutions to clients and solved important business problems through the delivery of end-to-end intelligent processes.
Senior Advisor, Management Consulting, KPMG in Cyprus
Georgios holds a BSc in Mathematics from the National Kapodistrian University of Athens and an MSc in Computer Science from the University of Edinburgh.
Georgios is a Senior Advisor in the Management Consulting department of KPMG in Cyprus. He is currently working in the Digital Innovation team, part of IT Advisory. Georgios has been applying cutting edge statistical and machine learning techniques, as well as advanced and complicated data manipulation methodologies to support data science and business solutions, mainly focusing on financial services.
His area of expertise includes artificial intelligence, intelligent automation and machine learning. Georgios is also participating in the technical design and development of innovative and practical solutions that aim to enhance the digital experience of clients in a transformational way (e.g. product development, API development/integration).