Myanmar, Yangon - Classroom

near Wyndham Grand, U Aung Myat Road Mingalar Taung Nyunt Township, Yangon, Myanmar, 11221

Set in Yangon, this classroom is well located in the Mingalar Taung Nyunt Township near the famous Lake, with all amenities and WiFi.

For Sales Enquires and Meetings

All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.

Explore Our Courses

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

 21 Hours
This instructor-led, live training in Myanmar (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.
Read more...

TinyML for IoT Applications

 21 Hours
This instructor-led, live training in Myanmar (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.
Read more...

Deploying AI on Microcontrollers with TinyML

 21 Hours
This instructor-led, live training in Myanmar (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.
Read more...

Introduction to TinyML

 14 Hours
This instructor-led, live training in Myanmar (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

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

2025-06-02 09:30
21 hours
Myanmar, Yangon - Classroom
252,991 INR (Online)
279,991 INR (Classroom)

TinyML for IoT Applications

2025-06-16 09:30
21 hours
Myanmar, Yangon - Classroom
252,991 INR (Online)
279,991 INR (Classroom)

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

2025-06-30 09:30
21 hours
Myanmar, Yangon - Classroom
252,991 INR (Online)
279,991 INR (Classroom)

Deploying AI on Microcontrollers with TinyML

2025-07-14 09:30
21 hours
Myanmar, Yangon - Classroom
252,991 INR (Online)
279,991 INR (Classroom)

Introduction to TinyML

2025-07-24 09:30
14 hours
Myanmar, Yangon - Classroom
168,661 INR (Online)
186,661 INR (Classroom)

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