Small Language Models (SLMs) Training in Sud-Vest

This instructor-led, live training session in Sud-Vest (online or onsite) targets intermediate-level urban planners, city administrators, and smart city solution developers who intend to implement Small Language Models (SLMs) in smart city projects to improve urban living standards.

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

• Understand the application of SLMs in smart cities.
• Integrate SLMs with urban data sets for enhanced decision-making.
• Develop strategies for deploying SLMs in urban management systems.
• Assess the impact of SLMs on urban planning and smart city solutions.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level educational technologists, instructional designers, and AI developers in education who aim to integrate Small Language Models (SLMs) into educational platforms to improve teaching and learning processes.

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

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

This instructor-led, live training in Sud-Vest (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.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for advanced-level machine learning engineers and AI researchers who want to develop energy-efficient AI solutions using small language models that are both powerful and environmentally responsible.

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

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

• Grasp the core principles of conversational AI and the strategic role of SLMs.
• Design and implement user-focused AI interactions.
• Develop and train SLMs for interactive applications.
• Assess and enhance the effectiveness of human-AI communication through appropriate metrics.
• Deploy scalable and ethical AI-driven conversational interfaces in real-world scenarios.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for intermediate-level data scientists and machine learning engineers who want to create and apply 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 importance and application of domain-specific language models.
• Curate and preprocess specialized datasets for model training.
• Train and fine-tune language models for domain-specific applications.
• Evaluate and benchmark models using domain-relevant metrics.
• Deploy domain-specific language models in real-world scenarios.

This instructor-led, live training in Sud-Vest (online or onsite) is designed for beginner to intermediate data scientists and developers who wish to implement and utilize Small Language Models across various applications.

Upon completion of this training, participants will be capable of:

• Grasping the architecture and operational mechanics of Small Language Models.
• Implementing SLMs for tasks including text generation and sentiment analysis.
• Optimizing and fine-tuning SLMs for specific use cases.
• Deploying SLMs within resource-constrained environments.
• Evaluating and interpreting SLM performance in real-world scenarios.