Small Language Models (SLMs) for Human-AI Interactions Training Course

This instructor-led, live training US (online or onsite) is designed for beginner-level to intermediate-level data scientists and developers who intend to implement and leverage Small Language Models within applications tailored for government. Upon completion of this program, participants will be able to:

• Comprehend the architecture and operational mechanics of Small Language Models.
• Implement SLMs to execute tasks such as text generation and sentiment analysis.
• Optimize and fine-tune SLMs to address specific use cases.
• Deploy SLMs in environments with resource constraints.
• Evaluate and interpret the performance of SLMs in real-world scenarios.

This instructor-led, live training program, available via US (remote or on-premises), is intended for intermediate-level educational technologists, instructional designers, and artificial intelligence developers within the education sector. The curriculum focuses on integrating Small Language Models (SLMs) into educational platforms to optimize teaching and learning processes.

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

• Analyze the role of SLMs in educational technology.
• Design AI-driven learning experiences using SLMs.
• Implement SLMs in various educational settings.
• Evaluate the effectiveness of SLMs in learning outcomes.

This instructor-led, live training provided US (online or onsite) is designed for intermediate-level municipal planners, local government administrators, and smart city solution architects seeking to deploy Small Language Models (SLMs) within government initiatives to enhance urban services.

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

• Evaluate the utility of SLMs in municipal smart city environments for government operations.
• Incorporate SLMs with civic data repositories to support evidence-based policy decisions.
• Formulate implementation plans for integrating SLMs into urban management frameworks.
• Measure the efficacy of SLM deployments in advancing urban planning objectives and smart infrastructure.

This instructor-led, live training program, offered online or onsite in US, is designed for data scientists and machine learning engineers at the intermediate level who seek to develop and implement small language models customized for specialized sectors, including legal, healthcare, and technical industries.

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

• Comprehend the significance and practical applications of domain-specific language models within government and public sector contexts.
• Select and preprocess specialized datasets necessary for effective model training.
• Train and fine-tune language models to address specific operational requirements.
• Evaluate and benchmark model performance using metrics relevant to the target domain.
• Deploy domain-specific language models in real-world environments for government

This instructor-led, live training in US (online or onsite) is designed for senior machine learning engineers and AI researchers seeking to create energy-efficient AI solutions using small language models that are both high-performing and environmentally responsible. This course is intended for government professionals who require advanced technical capabilities.

Upon completion of this training, participants will be able to:

• Assess the impact of AI systems on energy consumption and environmental sustainability.
• Apply model compression and optimization techniques to minimize the size and energy footprint of AI models.
• Utilize energy-efficient hardware and software frameworks for AI deployment.
• Implement best practices for sustainable AI development.
• Advocate for and contribute to sustainable practices in the AI industry.

This instructor-led, live training in US (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.

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

• Understand the challenges and solutions for implementing AI on compact hardware.
• Optimize and compress AI models for efficient on-device deployment.
• Utilize modern AI frameworks and tools for on-device model implementation.
• Design and develop real-time AI applications for mobile and IoT devices.
• Evaluate and ensure the security and privacy of on-device AI systems.