Austin, TX – Regus at Dobie Center

2021 Guadalupe Street, Suite 260, Austin, United States, 78705

The venue is located in the vibrant West Campus neighborhood near the University of Texas at the Dobie Center, easily reachable by car via I‑35 or I‑35 Frontage Road and Loop 1, with on-site and street parking nearby. From Austin–Bergstrom International Airport (AUS), about 11 miles southeast, a taxi or rideshare takes around 20–25 minutes via TX‑71 West and I‑35 North. Public transit users can take Capital Metro routes to the University of Texas/Dobie Mall stop directly in front of the building, placing it within a short walk for attendees without cars.

Austin, TX - Regus - Littlefield Congress

106 E 6th St, Austin, United States, 78701

The venue is conveniently situated near I‑35 and US‑183, making it easily accessible by car, with both public and garage parking options—such as the Littlefield Garage at 508 Brazos—located within walking distance. For those using public transportation, the venue is just a short walk from the Downtown Station (CapMetro) and is served by several bus routes. Travelers arriving by air will find that Austin-Bergstrom International Airport is approximately 8 miles away, providing straightforward access to and from the venue.

Explore Our Courses

SLMs for Smart Cities: Urban Planning and Management with AI

 14 Hours

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 improve urban living.

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.
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SLMs for Educational Tech: Tailoring AI for Learning and Development

 14 Hours

This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level educational technologists, instructional designers, and AI developers in education 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.
  • Design AI-driven learning experiences using SLMs.
  • Implement SLMs in various educational settings.
  • Evaluate the effectiveness of SLMs in learning outcomes.
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Small Language Models (SLMs) for On-Device AI

 21 Hours

This instructor-led, live training in Austin (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.
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Small Language Models (SLMs): Developing Energy-Efficient AI

 21 Hours

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.

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.
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Small Language Models (SLMs) for Human-AI Interactions

 14 Hours

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.

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

  • Understand the fundamentals of conversational AI and the role of SLMs.
  • Design and implement user-centric AI interactions.
  • Develop and train SLMs for interactive applications.
  • Evaluate and improve the effectiveness of human-AI communication using appropriate metrics.
  • Deploy scalable and ethical AI-driven conversational interfaces in real-world scenarios.
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Small Language Models (SLMs) for Domain-Specific Applications

 28 Hours

This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish 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.
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Small Language Models (SLMs): Applications and Innovations

 14 Hours

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

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

  • Understand the architecture and functionality of Small Language Models.
  • Implement SLMs for tasks such as text generation and sentiment analysis.
  • Optimize and fine-tune SLMs for specific use cases.
  • Deploy SLMs in resource-constrained environments.
  • Evaluate and interpret the performance of SLMs in real-world scenarios.
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Upcoming Courses

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

2025-10-06 9:30 am
21 hours
Austin, TX – Regus at Dobie Center
$ 4054 (Online)
$ 4054 (Classroom)

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

2025-10-20 9:30 am
21 hours
Austin, TX - Regus - Littlefield Congress
$ 4054 (Online)
$ 4054 (Classroom)

Small Language Models (SLMs): Applications and Innovations

2025-11-03 9:30 am
14 hours
Austin, TX – Regus at Dobie Center
$ 2703 (Online)
$ 2703 (Classroom)

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

2025-11-17 9:30 am
21 hours
Austin, TX - Regus - Littlefield Congress
$ 4054 (Online)
$ 4054 (Classroom)

Small Language Models (SLMs) for Human-AI Interactions

2025-12-01 9:30 am
14 hours
Austin, TX – Regus at Dobie Center
$ 2703 (Online)
$ 2703 (Classroom)

Small Language Models (SLMs) for Human-AI Interactions

2025-12-15 9:30 am
14 hours
Austin, TX - Regus - Littlefield Congress
$ 2703 (Online)
$ 2703 (Classroom)

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