* All fees are exclusive of vat ** PREMIUM - Customize your learning experience
Artificial intelligence (AI) is a research field that studies how to realize the intelligent human behaviors on a computer. The ultimate goal of AI is to make a computer that can learn, plan, and solve problems autonomously. Although AI has been studied for more than half a century, we still cannot make a computer that is as intelligent as a human in all aspects. However, we do have many successful applications. In some cases, the computer equipped with AI technology can be even more intelligent than us.
In this course, we will study the most fundamental knowledge for understanding AI. We will introduce some basic search algorithms for problem solving; knowledge representation and reasoning; pattern recognition; fuzzy logic; and neural networks.
What Do Participants Learn?
By the end of the course, participants will be able to:
Explain AI concepts and approaches
Apply the different AI appearances in the business value chain
Demonstrate the technologies background
Apply best practices in an AI project with its activities
Assess the available and necessary skills and competencies
Discuss on a qualified level with business and data specialists on relevant topics
Who Should Attend?
This course is designed for employees who for those who understand that continuous improvement, innovation and disruption and recognize that digital transformation is unavoidable.
What Will the Learning Experience Include?
Comprehensive pre-program activities include:
Web-based information forms & surveys completed by attendee.
Direct consultation with the attendee about the expectations.
During the training, participants engage in data, activities, and conversations that lead to insight and knowledge.
Participants learn from expert trainers who have both academic and business experiences.
Highly applicable training content & instructive activities for adding depth to training topics.
**A half-day site visit for integrating the experience & plan next steps. Opportunities to provide connections, ideas & support.
Explore & Practice
Apply & sustain the learning experience by using this ongoing support:
To ensure participant has new skills or behavior progress.
Optional, fee-based mentoring & coaching with the trainer.
Training materials & additional documents (e-books, pdf files, presentations and articles)
Evaluate your training experience by giving us feedbacks and help us to reach our organizational goals.
Section One: Introduction to Artificial Intelligence (AI), Machine Learning (ML) and data science
AI as a concept and appearances
AI as a combination of technologies
AI in historical perspective
AI: sense, reason, act
The thinking in AI: Machine learning
9 building blocks
Section Two: Algorithms and Engines
Supervised learning and applications
Classification: Algorithms like Naive Bayes
Regression: Algorithms like Linear regression and decision trees
Semi-supervised learning and applications
Algorithms like Q-Learning, SARSA
Unsupervised learning and applications
Clustering: Algorithms like K-means and hierarchical
Section Three: Team Work
Practice with building blocks and use cases
Reflection and application to own organization
Creative garage approach to ideate and define an AI Project
AI opportunity matrix
Successful use cases by Porters value chain
Successful use cases by technology
Section Four: Projects
Running successful AI projects
Ideation & problem definition
Exploratory data analysis
Skills and capabilities
Section Five: The Future of Artificial Intelligence
Evaluate the appropriateness of a business application for robotics.
Develop a road map for an organization to gain strategic advantage through the use of artificial intelligence.
Assess the impact of AI on the future of work and society.