About the training
This is an entry-level course on the basic concepts of the artificial intelligence and their use for developing artificial intelligence systems. After completing the training, the trainees are able to apply in practice the acquired knowledge to plan and organize the use of artificial intelligence applications in their companies and institutions.
This is an entry-level course on the basic concepts of the artificial intelligence and their use for developing artificial intelligence systems. After completing the training, the trainees are able to apply in practice the acquired knowledge to plan and organize the use of artificial intelligence applications in their companies and institutions.
What you will learn
- Artificial Intelligence Foundations;
- Introduction to AI and ML;
- Artificial Intelligence for Business Users;
- Nexus between HPC and AI.
- Artificial Intelligence Foundations;
- Introduction to AI and ML;
- Artificial Intelligence for Business Users;
- Nexus between HPC and AI.
Training information
The participants learn the principles of creating and using intelligent business applications. Furthermore, the relationship between artificial intelligence and HPC (incl. Internet of Things, blockchains and big data) is also explored in this course. The relationship between artificial intelligence and cybersecurity is explored as well.
The curriculum is structured in such a way as to allow tailoring depending on the specifics of the business of the trainees. The course consists of four topics (each topic 8 hours), and each topic includes two modules (each module 4 hours).
The typical training ideally incorporates 32 hours (4 days for 8 attendees) with the following agenda:
Artificial Intelligence Foundation:
o First module. Emergence and brief history of artificial intelligence (AI). What Is AI? (human vs. rational and thought vs. behavior, four groups of definitions). Roots of AI (philosophy, mathematics, economics, neuroscience, psychology, computer engineering, control theory and cybernetics, linguistics);
o Second module. Classical and modern AI. The State of the Art. Solving Problems by Searching. Knowledge (definition, classifications, common sense knowledge). Knowledge representations (rules, frames, semantic networks);
Introduction to AI and ML:
o First module. Intelligent architectures and components. Motivation to improve. Introduction to ML (definition, classification, variety of methods). Supervised, unsupervised and reinforcement learning;
o Second module. Artificial neural networks and deep learning. Progress of deep learning (from McCulloch–Pitts model to deep learning). Fundamentals. Applications. Advantages and disadvantages;
Artificial Intelligence for Business Users:
o First module. AI in marketing and sales. AI for customer service. AI in finance. AI in accounting and auditing. AI in human resources. AI in supply chain and logistics. AI in manufacturing;
o Second module. AI in insurance. AI in credit, lending, and mortgage. AI in tourism and hospitality. AI in transportation. AI in real estate. AI in education. AI in healthcare. AI in energy. AI in media and entertainment. AI in fashion. AI in video games and eSports. AI in sports;
Nexus between HPC and AI:
o First module. Convergence of High-Performance Computing (HPC), Cloud, and Big Data Domains. Event- and time-driven computing. Cyber-physical systems and AI. Enabling the HPC and AI;
o Second module. Internet of Thing (IoT). Block chains (BC). Intelligent infrastructures and applications integrating IoT and BC.
Additionally, the course includes hands-on sessions where participants can apply the theoretical knowledge gained to real-world scenarios. These practical exercises are designed to reinforce learning and ensure that participants can effectively utilize AI and HPC technologies in their respective fields.
To further support the learning process, the course offers access to a variety of resources, including online tutorials, research papers, and interactive tools. These supplementary materials enable participants to deepen their understanding and stay updated with ongoing advancements in AI and HPC technologies. They provide valuable insights into the latest trends, challenges, and best practices in the application of AI and HPC across various industries, enriching the learning experience.
The participants learn the principles of creating and using intelligent business applications. Furthermore, the relationship between artificial intelligence and HPC (incl. Internet of Things, blockchains and big data) is also explored in this course. The relationship between artificial intelligence and cybersecurity is explored as well.
The curriculum is structured in such a way as to allow tailoring depending on the specifics of the business of the trainees. The course consists of four topics (each topic 8 hours), and each topic includes two modules (each module 4 hours).
The typical training ideally incorporates 32 hours (4 days for 8 attendees) with the following agenda:
Artificial Intelligence Foundation:
o First module. Emergence and brief history of artificial intelligence (AI). What Is AI? (human vs. rational and thought vs. behavior, four groups of definitions). Roots of AI (philosophy, mathematics, economics, neuroscience, psychology, computer engineering, control theory and cybernetics, linguistics);
o Second module. Classical and modern AI. The State of the Art. Solving Problems by Searching. Knowledge (definition, classifications, common sense knowledge). Knowledge representations (rules, frames, semantic networks);
Introduction to AI and ML:
o First module. Intelligent architectures and components. Motivation to improve. Introduction to ML (definition, classification, variety of methods). Supervised, unsupervised and reinforcement learning;
o Second module. Artificial neural networks and deep learning. Progress of deep learning (from McCulloch–Pitts model to deep learning). Fundamentals. Applications. Advantages and disadvantages;
Artificial Intelligence for Business Users:
o First module. AI in marketing and sales. AI for customer service. AI in finance. AI in accounting and auditing. AI in human resources. AI in supply chain and logistics. AI in manufacturing;
o Second module. AI in insurance. AI in credit, lending, and mortgage. AI in tourism and hospitality. AI in transportation. AI in real estate. AI in education. AI in healthcare. AI in energy. AI in media and entertainment. AI in fashion. AI in video games and eSports. AI in sports;
Nexus between HPC and AI:
o First module. Convergence of High-Performance Computing (HPC), Cloud, and Big Data Domains. Event- and time-driven computing. Cyber-physical systems and AI. Enabling the HPC and AI;
o Second module. Internet of Thing (IoT). Block chains (BC). Intelligent infrastructures and applications integrating IoT and BC.
Additionally, the course includes hands-on sessions where participants can apply the theoretical knowledge gained to real-world scenarios. These practical exercises are designed to reinforce learning and ensure that participants can effectively utilize AI and HPC technologies in their respective fields.
To further support the learning process, the course offers access to a variety of resources, including online tutorials, research papers, and interactive tools. These supplementary materials enable participants to deepen their understanding and stay updated with ongoing advancements in AI and HPC technologies. They provide valuable insights into the latest trends, challenges, and best practices in the application of AI and HPC across various industries, enriching the learning experience.
Certificate
Other (eg. certificate of attendance / participation)
Price
Free
Level
Entry-level (Those with an initial experience or cybersecurity studies)
Teaching Method/s
Hybrid
Duration
1 to 3 days
Discount
No
Type
Training/course theoretical and hands on