Call for Papers
Background
The workshop’s background is rooted in the rapidly expanding influence of AI across sectors such as healthcare, finance, education, manufacturing, and cybersecurity. As organizations increasingly adopt AI-driven solutions, professionals must develop the skills to choose appropriate tools, integrate them into workflows, and measure their impact. This workshop was created to meet that need, blending academic insight with industry best practices. By offering a mix of lectures, demonstrations, and interactive exercises, it ensured participants not only learned about AI capabilities but also left prepared to apply these technologies strategically and responsibly in their own domains.
Goal/Rationale
The Artificial Intelligence Tools & Applications workshop was designed to bridge the gap between AI theory and real-world practice, empowering participants to understand, evaluate, and apply AI solutions effectively. The primary goals were to:
- Introduce participants to foundational AI concepts, including machine learning, natural language processing, and computer vision.
- Familiarize attendees with leading AI tools, frameworks, and platforms—both open-source and commercial—that can be leveraged across industries.
- Provide hands-on demonstrations that show how AI can enhance efficiency, improve decision-making, and enable innovative solutions.
- Encourage critical thinking about ethical considerations, including fairness, bias, transparency, and data privacy.
Scope and Information for Participants
The Artificial Intelligence Tools & Applications workshop covers both the theoretical foundations and practical applications of AI, providing participants with a balanced, hands-on learning experience. The scope includes key AI concepts such as supervised and unsupervised learning, natural language processing, computer vision, and generative AI, as well as the exploration of widely used tools like TensorFlow, PyTorch, scikit-learn, and cloud-based AI services. Participants will engage in live demonstrations and guided exercises to understand how AI can be integrated into various domains, from business analytics to automation and innovation projects.
Before attending, participants are encouraged to review basic data analytics concepts and bring a laptop for interactive activities. All necessary datasets, software links, and resources will be provided. No prior programming experience is required, although familiarity with basic technology workflows is beneficial. The workshop aims to ensure participants leave with actionable knowledge, practical skills, and relevant AI resource materials.
