Small Language Models (SLMs): Developing Energy-Efficient AI Training Course

This live, instructor-led session in Thailand, conducted either online or onsite, is designed for beginner to intermediate-level data scientists and developers looking to implement and leverage Small Language Models across various applications.

By the conclusion of this training, learners will be equipped to:

• Comprehend the architecture and functional aspects of Small Language Models.
• Utilize SLMs for tasks including text generation and sentiment analysis.
• Optimize and fine-tune SLMs to suit specific operational needs.
• Deploy SLMs in settings with limited computational resources.
• Analyze and interpret the performance of SLMs in real-world applications.

This live, instructor-led training in Thailand (online or onsite) caters to intermediate-level educational technologists, instructional designers, and AI developers in education aiming to embed Small Language Models (SLMs) into educational platforms to refine teaching and learning dynamics.

By the end of the session, participants will gain the ability to:

• Grasp the function of SLMs in the context of educational technology.
• Create AI-enhanced learning experiences utilizing SLMs.
• Integrate SLMs into various educational contexts.
• Measure the efficacy of SLMs regarding learning outcomes.

This instructor-led, live training in Thailand (offered online or onsite) is designed for intermediate-level urban planners, city administrators, and smart city solution developers seeking to implement Small Language Models (SLMs) in smart city projects to elevate urban living conditions.

By the conclusion of this training, participants will be able to:

• Comprehend the utility of SLMs in smart city environments.
• Integrate SLMs with urban data to support enhanced decision-making.
• Create strategies for rolling out SLMs within urban management systems.
• Analyze the effect of SLMs on urban planning and smart city solutions.

This interactive, instructor-led live training session in Thailand (available online or on-site) is designed for intermediate-level data scientists and machine learning engineers looking to develop and deploy small language models customized for specialized industries like legal, medical, and technical sectors.

Upon completion of this program, participants will be equipped to:

• Appreciate the significance and practical applications of domain-specific language models.
• Curate and prepare specialized datasets to optimize model training.
• Train and fine-tune language models specifically for targeted domain applications.
• Assess and benchmark model performance using metrics relevant to the specific domain.
• Implement domain-specific language models in practical, real-world environments.

This live, instructor-led session in Thailand (either online or in-person) is tailored for intermediate data scientists and AI/ML researchers aiming to design efficient, engaging conversational experiences using small language models.

By the conclusion of the program, attendees will be able to:

• Comprehend the basics of conversational AI and the role of SLMs.
• Structure and implement user-centric AI dialogue flows.
• Develop and fine-tune SLMs for interactive applications.
• Measure and enhance the efficacy of human-AI exchanges using relevant KPIs.
• Launch scalable, ethical AI conversational interfaces in live production settings.

This live, instructor-led training in Thailand, offered both online and onsite, is designed for mid-level IT professionals looking to deploy small language models on devices with limited processing capacity. This approach paves the way for innovative applications across various sectors.

By the end of this program, participants will be equipped to:

• Navigate the complexities and find solutions for AI implementation on compact hardware.
• Fine-tune and compress AI models for streamlined on-device operation.
• Apply modern AI frameworks and utilities for effective on-device model execution.
• Create real-time AI solutions for mobile and IoT platforms.
• Monitor and guarantee the security and privacy integrity of on-device AI architectures.