Learn TinyML Online: Free Course with AI Tutor & Certificate
For developers and engineers, this free TinyML course teaches you how to run AI on microcontrollers. You'll master 6 modules spanning Introduction to TinyML, Fundamentals of Machine Learning, Embedded Systems Basics, TinyML Frameworks and Tools, Deploying TinyML Models, and Hands-on TinyML Projects to build smart embedded solutions.
What you'll learn in this TinyML course
Five concrete outcomes you'll walk away with, each mapped to modules in the curriculum below.
Understand and articulate the core concepts and applications of TinyML and its ecosystem.
Apply fundamental machine learning techniques and neural network principles to develop TinyML solutions.
Design and program embedded systems, including microcontrollers and sensors, for TinyML applications.
Utilize and optimize TinyML frameworks and tools, such as TensorFlow Lite for Microcontrollers and Edge Impulse.
Deploy, test, and maintain TinyML models in real-world scenarios, ensuring efficient performance and integration with sensors.
TinyML course syllabus
01 Introduction to TinyML
- What is TinyML?
- Applications of TinyML
- Benefits and Challenges
- Overview of TinyML Ecosystem
02 Fundamentals of Machine Learning
- Basic Concepts of Machine Learning
- Types of Machine Learning
- Introduction to Neural Networks
- Training and Evaluation
03 Embedded Systems Basics
- Understanding Embedded Systems
- Microcontrollers and Sensors
- Programming Embedded Devices
- Power Management in Embedded Systems
04 TinyML Frameworks and Tools
- Overview of TinyML Frameworks
- TensorFlow Lite for Microcontrollers
- Edge Impulse
- Model Optimization Techniques
05 Deploying TinyML Models
- Model Deployment Strategies
- Testing and Validation
- Real-world Deployment Examples
- Monitoring and Maintenance
06 Hands-on TinyML Projects
- Setting Up Your Development Environment
- Building a Simple TinyML Application
- Integrating Sensors with TinyML
- Optimizing Model Performance
Real-world projects you'll work on
Practice the exact kind of work TinyML professionals do on the job.
Google Home Mini: Voice Command Recognition with TinyML
Tesla's Smart Energy Management: Predictive Maintenance Using TinyML
Amazon Go: Real-time Object Detection for Automated Checkout Systems
Apple's HealthKit: Wearable Health Monitoring with TinyML
Skills you'll gain
Add these to your LinkedIn profile and resume the day you finish.
Who should take this TinyML course?
And exactly what you need before starting (spoiler: almost nothing).
This course is for
- IoT enthusiasts wanting to add AI capabilities to hardware projects.
- Software developers looking to transition into embedded machine learning.
- Electronics engineering students in India building modern hardware portfolios.
- Data scientists interested in deploying models on edge devices.
Prerequisites
- Basic understanding of Python or C++ programming is recommended.
- Familiarity with fundamental machine learning concepts helps but is not strictly required.
- A general interest in microcontrollers and hardware components.
How learning works on LearnTube
The structure of a bootcamp, the price of free.
AI curates your path
Our AI picks the top 1% of video content for each topic and arranges it into a structured, goal-based curriculum. No more tutorial roulette.
Learn, then get quizzed
After every lesson, your AI tutor asks you a question and gives personalised feedback on your answer, so gaps get fixed immediately.
Finish with proof
Complete the course, build the capstone project, and claim a certificate recognised by 900+ hiring partners.
A complete TinyML course: free, structured and job-focused
Designed for software developers and electronics engineers, this free TinyML course teaches you how to bring machine learning to resource-constrained devices. You'll start with an Introduction to TinyML and the Fundamentals of Machine Learning, moving quickly into Embedded Systems Basics. The curriculum focuses on practical skills, teaching you to program microcontrollers, manage power, and understand neural networks at the edge.
As you progress into TinyML Frameworks and Tools, you'll work with TensorFlow Lite for Microcontrollers and Edge Impulse. The program then covers Deploying TinyML Models, ensuring you know how to test and maintain real-world applications. You'll apply these skills in Hands-on TinyML Projects, building impressive portfolio pieces. These include a Google Home Mini voice command recognition system, Tesla's smart energy management for predictive maintenance, Amazon Go real-time object detection, and an Apple HealthKit wearable monitoring application.
LearnTube makes mastering embedded machine learning easy and interactive. The platform pairs curated YouTube video lessons with an AI tutor that gives you a quiz after every lesson to test your knowledge. All learning content is completely free to access. If you want to prove your new skills to employers, you can choose to add an optional paid certificate at the end of your training.
Jobs you can target after learning TinyML
TinyML is a gateway skill for some of the fastest-growing roles in tech.
Designs and deploys AI models directly onto microcontrollers and edge devices.
Builds connected hardware systems that use local AI for real-time decision making.
Optimizes machine learning algorithms to run efficiently on resource-constrained frameworks.
Integrates sensors and neural networks to create smart, low-power consumer electronics.
Typical entry-level salary ranges in India as of November 2026. Actual compensation varies by city, company and experience.
Earn a TinyML certificate employers recognise
Finish the course and claim a certificate you can share anywhere.
- Learn 100% free: every lesson, quiz and the AI tutor cost nothing
- Claim your certificate when you complete the course (an optional paid add-on)
- Recognised by 900+ hiring partners across India
- One click to share on LinkedIn and add to your resume
Why learners choose LearnTube
Real reviews from Google. You learn free, you get assessed free, and you pay only if you want the certificate.
Though I have 11 years of experience as an HRBP, the course helped me refresh my knowledge and gave me insights into new trends in the market. The modules were clear and easy to understand, and the quizzes were well designed. I have added the certificate to my LinkedIn profile.
I had a lot of doubts while learning, but the AI chatbot answered them in detail with simple summaries. The videos on the platform saved me a lot of time as I didn't have to search YouTube and watch random content.
Just earned my certificate in HR Management from LearnTube.ai! The platform is user-friendly and the assessment was a great way to validate my knowledge. Feeling proud of this accomplishment!
I enrolled in a LearnTube personalized course to get into a Data Analytics role. It helped me learn SQL in depth and gave me hands-on experience with Power BI. I attached the LearnTube certificate to my CV, it added credibility to my profile, and I'm currently in the interview process.
The interface is user-friendly and intuitive, making it easy to navigate the course. I encountered no errors during my time using the platform, which was a refreshing change from other online learning platforms.
Just cleared the Business Analyst assessment and got certified! Loved how the course simplifies big concepts like data-driven decision making into short, practical lessons. The automated quizzes kept me on track the whole time. Perfect boost for my resume!
The certificate gave me a real edge during my B.Tech. By the time I graduated, I had skills that set me apart from my peers, and the certification opened up more job opportunities. It gave me the confidence to stand out during interviews.
I manage many software projects as a General Manager and was looking for a good certification program to stay competitive. After researching many programs, I chose LearnTube and it was much better than I expected. The material is well-organized and practical, and what I liked most is the lifetime access.
Frequently asked questions
Everything learners ask before starting this TinyML course.
Is this TinyML course completely free to take?
Yes, the entire learning experience is free. You can watch all curated video lessons and take every AI-generated quiz without paying anything. An official certificate is available as an optional paid upgrade once you finish the modules.
How long does it take to learn embedded machine learning?
The timeline depends entirely on your personal schedule. This is a self-paced program, meaning you can complete the six modules and hands-on projects as quickly or slowly as you prefer.
What kind of projects will I build in this program?
You will build several real-world applications. Projects include a voice command recognition system like Google Home Mini, predictive maintenance models inspired by Tesla, and wearable health monitoring applications using Apple HealthKit concepts.
Is TinyML still in demand for modern tech jobs?
Yes, demand for edge AI skills is growing rapidly. Companies need engineers who can run machine learning models locally on low-power devices to improve privacy, reduce latency, and save bandwidth in smart electronics.
Do I need to buy expensive hardware to learn TinyML?
No, you do not need expensive hardware to get started. You can learn the concepts using software simulators and frameworks like Edge Impulse before deciding to test your models on physical microcontrollers later.
Can I get a certificate for completing this training?
Yes, you can earn a verifiable certificate. While all educational content and quizzes are free, the official certification is an optional paid add-on that you can attach to your resume or LinkedIn profile.
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