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Launch Your Career in Edge AI Engineering

Running a model in the cloud is easy. Running it on a device with 256KB of RAM and a battery is the job. This program teaches you to shrink, deploy and measure models that run where the data is.

Global #1 Training & Internship Program

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Program Summary

Edge AI is the practice of running inference on the device instead of in the cloud, because of latency, privacy, bandwidth or power. This program builds a practical foundation in that work: how a model is chosen for a constrained target, how quantisation and pruning shrink it, how it is compiled and deployed, and how you measure whether accuracy survived the squeeze.

Alongside the technical modules, the program includes hands-on labs and a virtual internship. You will train a small model, quantise and convert it, deploy it to an emulated microcontroller and a single-board computer, benchmark latency and power, and finish with project work you can show to an employer.

Why Refonte Learning's Edge AI Engineer Course is the Best Fit for You

  • Concrete Projects, Real-World Experience
  • In-Depth Skill Enhancement
  • Seasoned Guidance
  • Potential Internship

Program Specifics

Requirement

Engaged in bachelor's or postgraduate studies in Aerospace, Electrical Engineering, Physics, Computer Science, or related fields

Period

3 months

Dedication time

10-12 Hours/Week

Career Result

Edge AI Engineer, TinyML Engineer, Embedded Machine Learning Engineer, ML Deployment Engineer and Computer Vision Engineer roles across semiconductors, industrial, automotive and consumer products.

Competencies you'll develop

  • Edge AI Architecture & When Not to Use It
  • Model Selection for Constrained Targets
  • Quantisation, Pruning & Distillation
  • TensorFlow Lite Micro & ONNX Runtime
  • Accelerators, NPUs & Hardware Mapping
  • Latency, Memory & Power Benchmarking
  • On-Device Vision & Audio Pipelines
  • Data Collection, Labelling & Drift
  • Deployment, Versioning & Monitoring

Expertise Featured

  • Edge AI Architecture & When Not to Use It
  • Model Selection for Constrained Targets
  • Quantisation, Pruning & Distillation
  • TensorFlow Lite Micro & ONNX Runtime
  • Accelerators, NPUs & Hardware Mapping
  • Latency, Memory & Power Benchmarking
  • On-Device Vision & Audio Pipelines
  • Data Collection, Labelling & Drift
  • Deployment, Versioning & Monitoring

Tools Taught

tools taught

Educational Mentors

mentor

PhD Matthias Schmidt

Department of Data Engineering

Leveraging his deep-rooted knowledge as a senior data engineer, Matthias Schmidt plays a pivotal role in shaping our Data Engineering Training & Internship program. With a remarkable 16-year background in computer science, he excels in diverse domains such as sophisticated regression analysis, algorithmic design for enhancing customer loyalty, financial econometrics, and quantitative risk forecasting. His proficiency extends to harnessing big data solutions tailored for banking and financial services, making him an invaluable mentor in the field of data engineering.

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Matthias Schmidt

Your Educational Path

Quantise and prune a model to fit a microcontroller, then measure exactly how much accuracy you traded for the memory you saved.

Convert and deploy to an emulated MCU and a single-board computer, and benchmark latency, memory and power on each.

Build an on-device vision or keyword-spotting pipeline that runs in real time without sending data anywhere.

Need clarification about the course? Get in touch with us

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Application DETAILS

Enroll today with just three easy steps and dive into our rich learning opportunities to start your educational journey.

Step 1

Sign Up

Register and complete your application for the course/program that catches your interest

Step 2

Buy

Complete the payment for the course fees to enroll and reserve your place.

Step 3

Kickstart your learning

Your learning journey kicks off with the next cohort - don't miss it!

Admission Prerequisites

Obligatory: Working towards a bachelor's or higher-level degree

We delight in recognizing your successes

Upon successful completion of the program, Refonte Learning offers two certificates: a Training Certificate and a Certificate of Internship. Students who demonstrate outstanding performance may receive a Letter of Recommendation and a Certificate of Appreciation for their achievements. In addition, top performers will be rewarded with exclusive prizes such as Amazon vouchers, gift hampers, and personalized T-shirts.

Advantages of the Program

  • Concrete Projects, Real-World Experience
  • In-Depth Skill Enhancement
  • Potential Futures
certificates

Application Fees

We believe in making our programs accessible to everyone. That's why we offer a variety of financing options, including competitive rates as low as 0% interest and no hidden costs. You can also choose to make a convenient one-time payment.

Equated Monthly Installment payment options

Explore budget-friendly EMI plans with reputable finance firms. Overcome financial obstacles and stay focused on your personal development.

Credit/Debit Card and Paypal

Costs as low as

Installment I: USD 204

Installment II: USD 98

One-Time Payment Options

Experience the ease and flexibility of a single payment, allowing you to start your career journey without any hassle.

Credit/Debit Card and Paypal / Online Banking

Total Enrollment Costs

USD 300

Important Datest & Deadlines

Date & Deadlines

Details

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Frequently Asked Questions

What career opportunities does this course provide?

Edge AI Engineer, TinyML Engineer and Embedded Machine Learning Engineer roles at semiconductor, industrial and consumer employers such as ARM. A growing commercial market.

Do I need a GPU or special hardware?

No. Labs use small models, free cloud tiers and emulated targets; a Raspberry Pi is optional.

Is this course suitable for beginners?

It suits learners with some Python and basic machine learning. No embedded background is needed.

Will I receive a certification upon completion?

Yes, a Refonte Learning certificate of completion. It is not an industry certification exam.

Can I take this course while working full-time?

Yes. It requires 10-12 hours per week and sessions are recorded.

Ready to fulfill your dream of becoming a Professional Edge AI Engineer?

Begin your journey with Refonte International's Training & Internship Program for comprehensive training, valuable certificates, and exciting future opportunities.

Apply Now