Object Detection
Bootcamp
Stop learning AI in theory and start building it in reality. In this rigorous 4-week cohort, you will step into the shoes of a real AI team. Collect raw images, lead a crew of annotators, master quality assurance, and train your very own machine learning model from scratch.
The 4-Week Technical Journey
A structured progression from project ideation to production-grade model deployment.
Project Kickoff & Foundations
Step into your role as Project Owner. We begin by designing and scoping your custom image labeling project. You will define the architecture, assign cohort roles, and set up your deep learning workflows using essential industry tools like Label Studio and Google Drive.
Data Collection & Annotation
Time to gather your raw materials. Through rapid "project-day cycles," you will work alongside your cohort crew to strategically acquire raw images. Once collected, your team will execute rigorous bounding-box annotation protocols to start building high-fidelity training sets.
QA & Refinement
Great AI requires flawless data. This week focuses entirely on dataset quality control. Switching into roles like QA Lead and Reviewer for your peers projects, you will validate datasets, detect biases, and apply strict QA workflows before final dataset packaging.
Model Training & Certification
Bring your data to life. You will use Google Colab or Teachable Machine to train, evaluate, and iterate your own mini-model. The bootcamp culminates in a final presentation of your working object detection system to earn your DeeLab Academy Certification.
Your Credential
What You'll Learn & Tools We Use
By the end of this 4-week intensive, you'll have the real-world experience to:
- 1 Design and scope end-to-end image labeling projects.
- 2 Perform high-quality bounding box annotations.
- 3 Implement strict QA and review processes across a team.
- 4 Package raw datasets for machine learning consumption.
- 5 Train, test, and evaluate basic image-based models.
We focus on powerful, free or low-cost industry tools — so you can keep building long after the bootcamp ends.
Tools in Action
Join the Next
Cohort
Confirmed Intake
21 Sep – 23 Oct 2026
Only 25 seats remaining for this intake. Secure your spot to join a dedicated crew of peers and get the hands-on experience, mentorship, and practical skills needed to build real AI systems from the ground up.
Manual & Bank Transfer →
Corporate & Team Training
Empower your team to build real AI solutions. We design customized, hands-on bootcamps tailored to your company's specific industry challenges — from manufacturing defect detection to retail inventory automation.
Custom Scope & Projects
We tailor the curriculum so your team learns by building models using your own company data, use cases, and preferred tech stack.
Scalable Upskilling
Flexible delivery and specialized cohort pricing for teams of 5 or more, designed to get your entire squad production-ready.
Frequently Asked Questions
Everything you need to know before applying.
The bootcamp is open to anyone who wants to understand how AI models are built from the ground up — no prior AI knowledge or coding experience is required. It is equally valuable for programme managers and project managers who commission or oversee AI projects, for contractors and freelancers who collect or annotate data professionally, and for anyone in a technical or operational role who wants a complete, hands-on picture of the full pipeline. Understanding how raw images become a trained model helps you plan better, communicate across teams more effectively, and deliver higher-quality results faster — a genuinely valuable skill whether you are leading a project, working inside one, or building your own.
All tools used in the bootcamp are free or very low cost so you can keep using them long after the course ends. For annotation you will work with Label Studio (Community Edition), MakeSense.ai, and Roboflow. Datasets are organised and shared via Google Drive. For model training you will use Google Colab and Google's Teachable Machine — no local GPU or specialist hardware is required. A standard laptop with a modern browser is all you need.
By the end of the bootcamp you will have designed and scoped a real image labeling project from scratch, collected and organised raw image datasets, performed high-quality bounding box annotations to production standards, led peer QA and review processes to catch errors and dataset bias, packaged a dataset correctly for machine learning consumption, and trained, tested, and evaluated your own working image-based model. You will also have experienced real team dynamics — rotating between roles like Project Owner, Annotator, QA Lead, and Reviewer — which mirrors exactly how professional AI data teams operate.
Yes — the Object Detection Bootcamp is fully online and you can join from anywhere in the world. DeeLab Academy is based in Singapore. We are also open to designing on-site workshops for organisations or markets where there is sufficient demand; if you are interested in an in-person format for your team or region, reach out through our contact page.
There is currently no formal industry-wide certification body for data annotation training — this is a gap the AI ecosystem is still addressing. DeeLab Academy has built its training and certification system following the best current industry practices and methodologies, and we are fully open to being audited by any recognised consultancy that wishes to validate our processes. Our curriculum is designed and delivered by a five-member team of multi-year industry experts. We collect structured feedback from every cohort, read every response, and continuously improve our content — because better-trained people produce better AI data, and that matters to us.