Fayetteville, AR - Pryor Center

1 E. Center St, Ste 270, Fayetteville, United States, 72701

The venue is centrally located in Fayetteville Square, making it easily accessible by car, with ample street parking and public garages nearby. For those arriving by air, the Northwest Arkansas National Airport (XNA) is approximately 15 miles away. Public transportation is also available, with several local bus routes serving the downtown Fayetteville area.
NobleProg Training Place, City Fort Smith, AR

Fort Smith, AR

900 Rogers Ave, Fort Smith, United States, 72901

Conveniently off I‑40 (Exit 10/Rogers Ave), the venue offers easy access by car. Guests flying in can come through Fort Smith Regional Airport, located approximately 7 miles away​.The venue is just minutes from downtown businesses, local attractions, and dining options.

Fayetteville, AR - The Root

3537 N Steele Blvd Ste. 110, Fayetteville, United States, 72703

Easily accessible from I‑49 via Steele Boulevard exit. The venue is located on Fayetteville Square with street and nearby garage parking. Northwest Arkansas Regional Airport (XNA) is approximately 15 miles away. Attendees can also use local bus routes serving downtown.

Little Rock, AR - Regus - Regions Center

400 West Capitol Avenue, Little Rock, United States, 72201

The building is located in downtown Little Rock at 400 W Capitol Ave. It is easily accessible by car via Interstate 30 and is situated near major downtown businesses. For those arriving by air, the Bill and Hillary Clinton National Airport (LIT) is approximately 6 miles away. Visitors will find ample street parking and nearby garage options, along with convenient walkable access to dining and lodging.

Explore Our Courses

TinyML: Running AI on Ultra-Low-Power Edge Devices

 21 Hours

This instructor-led, live training in Arkansas (online or onsite) is aimed at intermediate-level embedded engineers, IoT developers, and AI researchers who wish to implement TinyML techniques for AI-powered applications on energy-efficient hardware.

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

  • Understand the fundamentals of TinyML and edge AI.
  • Deploy lightweight AI models on microcontrollers.
  • Optimize AI inference for low-power consumption.
  • Integrate TinyML with real-world IoT applications.
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TinyML for IoT Applications

 21 Hours

This instructor-led, live training in Arkansas (online or onsite) is aimed at intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

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

  • Understand the fundamentals of TinyML and its applications in IoT.
  • Set up a TinyML development environment for IoT projects.
  • Develop and deploy ML models on low-power microcontrollers.
  • Implement predictive maintenance and anomaly detection using TinyML.
  • Optimize TinyML models for efficient power and memory usage.
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Deploying AI on Microcontrollers with TinyML

 21 Hours

This instructor-led, live training in Arkansas (online or onsite) is aimed at intermediate-level embedded systems engineers and AI developers who wish to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

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

  • Understand the fundamentals of TinyML and its benefits for edge AI applications.
  • Set up a development environment for TinyML projects.
  • Train, optimize, and deploy AI models on low-power microcontrollers.
  • Use TensorFlow Lite and Edge Impulse to implement real-world TinyML applications.
  • Optimize AI models for power efficiency and memory constraints.
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Introduction to TinyML

 14 Hours

This instructor-led, live training in Arkansas (online or onsite) is aimed at beginner-level engineers and data scientists who wish to understand TinyML fundamentals, explore its applications, and deploy AI models on microcontrollers.

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

  • Understand the fundamentals of TinyML and its significance.
  • Deploy lightweight AI models on microcontrollers and edge devices.
  • Optimize and fine-tune machine learning models for low-power consumption.
  • Apply TinyML for real-world applications such as gesture recognition, anomaly detection, and audio processing.
Read more...

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Upcoming Courses

Introduction to TinyML

2025-08-07 9:30 am
14 hours
Fayetteville, AR - Pryor Center
$ 2703 (Online)
$ 3123 (Classroom)

Deploying AI on Microcontrollers with TinyML

2025-08-25 9:30 am
21 hours
Fayetteville, AR - Pryor Center
$ 4054 (Online)
$ 4684 (Classroom)

Introduction to TinyML

2025-09-04 9:30 am
14 hours
Fayetteville, AR - Pryor Center
$ 2703 (Online)
$ 3123 (Classroom)

TinyML for IoT Applications

2025-09-22 9:30 am
21 hours
Fayetteville, AR - Pryor Center
$ 4054 (Online)
$ 4684 (Classroom)

TinyML for IoT Applications

2025-10-06 9:30 am
21 hours
Fayetteville, AR - Pryor Center
$ 4054 (Online)
$ 4684 (Classroom)

Deploying AI on Microcontrollers with TinyML

2025-10-20 9:30 am
21 hours
Fayetteville, AR - Pryor Center
$ 4054 (Online)
$ 4684 (Classroom)

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