Small Language Models (SLMs) Training in Austin

This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level urban planners, city administrators, and smart city solution developers who wish to implement Small Language Models (SLMs) in smart city projects to enhance urban living for government.

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

• Comprehend the application of SLMs in smart cities.
• Integrate SLMs with urban data sets to improve decision-making processes.
• Formulate strategies for deploying SLMs within urban management systems.
• Evaluate the impact of SLMs on urban planning and smart city solutions.

This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level educational technologists, instructional designers, and AI developers for government who wish to integrate Small Language Models (SLMs) into educational platforms to enhance teaching and learning processes.

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

• Understand the role of SLMs in educational technology for government.
• Design AI-driven learning experiences using SLMs.
• Implement SLMs in various educational settings within public sector environments.
• Evaluate the effectiveness of SLMs in improving learning outcomes for government audiences.

This instructor-led, live training in Austin (online or onsite) is designed for intermediate-level IT professionals who aim to deploy small language models directly onto devices with limited processing capabilities. This approach opens up possibilities for innovative applications across various sectors, including those relevant to government operations.

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

• Understand the challenges and solutions associated with implementing AI on compact hardware.
• Optimize and compress AI models for efficient deployment on devices with limited resources.
• Utilize modern AI frameworks and tools to facilitate on-device model implementation.
• Design and develop real-time AI applications suitable for mobile and IoT devices, enhancing capabilities for government use.
• Evaluate and ensure the security and privacy of on-device AI systems, adhering to stringent public sector standards.

This instructor-led, live training in Austin (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly for government.

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

• Understand the impact of AI on energy consumption and the environment.
• Apply model compression and optimization techniques to reduce the size and energy usage of AI models for government applications.
• Utilize energy-efficient hardware and software frameworks for AI deployment in public sector environments.
• Implement best practices for sustainable AI development aligned with government standards.
• Advocate for and contribute to sustainable practices within the AI industry, particularly for government operations.

This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists, machine learning, and AI researchers who wish to create engaging and efficient AI-powered conversational experiences with small language models for government.

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

• Understand the fundamentals of conversational AI and the role of small language models.
• Design and implement user-centric AI interactions that align with public sector workflows.
• Develop and train small language models for interactive applications in government settings.
• Evaluate and improve the effectiveness of human-AI communication using appropriate metrics, ensuring governance and accountability.
• Deploy scalable and ethical AI-driven conversational interfaces in real-world government scenarios.

This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish to develop and implement small language models tailored for specific domains such as legal, medical, and technical fields.

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

• Understand the significance and application of domain-specific language models for government and other public sector workflows.
• Curate and preprocess specialized datasets for model training in alignment with governance and accountability standards.
• Train and fine-tune language models for domain-specific applications, ensuring they meet the needs of specific sectors.
• Evaluate and benchmark models using metrics relevant to their intended domains.
• Deploy domain-specific language models in real-world scenarios, enhancing decision-making and operational efficiency for government operations.

This instructor-led, live training in Austin (online or onsite) is aimed at beginner to intermediate-level data scientists and developers who wish to implement and leverage Small Language Models for government applications.

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

• Comprehend the architecture and functionality of Small Language Models.
• Implement SLMs for tasks such as text generation and sentiment analysis in public sector workflows.
• Optimize and fine-tune SLMs for specific government use cases.
• Deploy SLMs in resource-constrained environments within government agencies.
• Evaluate and interpret the performance of SLMs in real-world government scenarios.