Eight weeks. Machine learning, neural networks, and real AI applications. You come in curious. You leave ready to build.
Genius Bootcamp is not a passive course where you watch videos and forget everything by Friday. It is eight weeks of building real things, breaking them, and understanding why they work. That order is deliberate: you learn by doing and by recalling, not by watching, and the things you build and debug with your own hands are the things that stay.
You will start with the foundations of machine learning and end up training your own neural networks. Each week is a rung that rests on the one below it, so a hard idea in week five is reachable because of what you genuinely earned in weeks one to four. Everything is grounded in Caribbean context. The datasets are local. The problems are real. The skills transfer globally.
No computer science degree required. No prior coding experience required. What you need is consistency and the willingness to think hard, and a particular attitude to being stuck. Getting stuck is not a sign you do not belong here; it is the normal feeling of your brain stretching into something it cannot do yet. The word "yet" is doing real work in that sentence.
Evening sessions designed around school and work schedules. Recordings available for every session.
Blended format. Kingston hub sessions plus live virtual access for participants across Jamaica.
Funded by The Genius Project. No registration fees, no hidden costs. Laptops can be borrowed where needed.
The bootcamp is built around two ideas that learning science keeps confirming. The first is that knowledge becomes skill through use: you remember and can apply what you actively build, break, and rebuild far more than what you passively watch. That is why you write code from week one instead of waiting until you have "covered the theory." The second is scaffolding. A genuinely hard subject like neural networks is reachable only because each week sits on the one before, and instructors give you a supported worked example first, then fade that support until you can do it alone. You spend the whole programme working at the edge of what you can manage with a little help, which is exactly where learning happens fastest.
The hardest part of an intensive is not the maths, it is the moment you feel stuck and start to doubt you belong. This is where mindset decides outcomes. Treating a failed model as "I have not solved this yet" rather than "I am not smart enough" is the difference between the students who finish and the ones who fade, and our 92% completion rate is built as much on that culture as on the curriculum. Add the autonomy of picking your own final project and the sense of building alongside a cohort who have your back, and you get motivation that comes from inside, the kind that lasts eight demanding weeks.
Active learningScaffoldingGrowth mindsetSelf-Determination Theory
Every week builds on the last, and that is the point. New skills hook onto skills you already own, so the curriculum is sequenced as a ladder of scaffolds rather than a pile of topics. By week 8 you will have a portfolio of working AI projects.
Variables, functions, loops, data structures. We move fast. By Friday you are writing scripts that pull and clean data. Tools: Python, VS Code, Google Colab.
What is data? How do you explore it? We use real Jamaican datasets, from crime statistics to agricultural yields. Pandas, NumPy, and Matplotlib from day one.
Supervised learning. You train a model to predict something real, crop disease likelihood, student dropout risk, traffic patterns. Scikit-learn, train/test splits, evaluation metrics.
Feature engineering, hyperparameter tuning, cross-validation. Why does your model fail on new data? How do you fix it? The difference between a good model and a great one.
How the brain inspired the algorithm. Perceptrons, layers, activation functions, backpropagation explained without heavy math. Build your first neural net with TensorFlow/Keras.
Convolutional neural networks. Teaching machines to see. Project: build an AI that identifies Jamaican plant diseases from photos. Real agricultural impact.
Text as data. Sentiment analysis of Jamaican Creole social media. Build a chatbot. Introduction to large language models and how they actually work under the hood.
You pick the problem, you build the solution, you present to a panel of tech industry professionals and potential employers. You pick the problem on purpose: that ownership is what makes the final stretch feel like yours rather than an assignment, and it is a big part of why people pour real effort into it. Presenting also forces deep understanding, because you cannot explain a system clearly until you truly grasp it. Your GitHub portfolio is your proof of work.
Finished fifth form or sitting CAPE? This is where your tech journey accelerates. You do not need to wait for university.
Already working but want to pivot into tech? The bootcamp runs evenings so you do not have to quit your day job to start building your future.
UWI, UTech, NCU student and your degree is not moving fast enough? Come supplement it with real applied AI skills.
Build and deploy machine learning systems for companies in Jamaica and remotely.
Turn raw data into decisions. Banks, health systems, and government agencies all need this.
Help Caribbean businesses understand and adopt AI. High demand, low supply right now.
Build your own AI product. Many Genius Bootcamp graduates move directly into the Startup Lab.
No. We start from zero. You will write your first line of Python in week one. What matters is that you show up and put in the work.
Ideally yes. If you do not have one, contact us when you apply and we will arrange a loaner device for the duration of the program. We use Google Colab for most work, so even an older machine can handle it.
Yes. The Genius Project is a non-profit funded through donations. Every Jamaican youth who qualifies attends at no cost. There are no hidden fees.
Plan for around 15 hours per week. Three evening sessions of two to three hours each, plus independent project work. It is intensive by design. That is why graduates come out ready.
You get access to The Genius Project alumni network, ongoing mentorship, job board connections, and priority placement in the Startup Lab if you want to build your own product.
The program is designed for ages 15 to 30. If you are outside that range and feel strongly about applying, reach out and we will talk.
Almost everyone feels this, and it is worth separating the feeling from the fact. Ability in AI is built through practice, not handed out at birth, so the meaningful question is not whether you are "smart enough" but whether you will keep going when something does not click on the first try. We design for exactly that: hard concepts are scaffolded with worked examples before you fly solo, the weeks build gently on each other, and instructors expect you to get stuck because being stuck is what learning feels like from the inside. Treat each error as "not yet" rather than "can't," show up consistently, and the skill follows. That mindset, more than any prior background, is what our 92% completion rate is made of.
Cohorts run three times per year. Spots fill up. If you are serious about AI, get your application in now.