Learn how to turn raw data into useful insights and build real-world AI applications. You’ll cover data analytics, data preparation and visualisation, classical machine learning (supervised and unsupervised), deep learning (neural networks, CNNs, autoencoders), and Natural Language Processing. Finish with projects and a portfolio that demonstrate practical capability.
We’ll guide you through a carefully curated curriculum designed to take you from ‘just curious’ to confident in Data Science & AI in as few as 12 weeks full-time (or 24 weeks part-time).
SQL, Python, Jupyter Notebook, Git and GitHub, Linear Algebra, Probabilities and Statistics.
Data Analysis, Data Preparation, Data Visualization and Data Exploration.
Machine Learning, Supervised and Unsupervised learning, ML model enhancement, Naive Bayes, SVM, Random Forests, ML Pipelines and Classification.
Neural Networks (implementation, troubleshooting & optimisation), CNN Architectures, Autoencoder Architecture, Data Augmentation, Tensorflow, Keras and Scikit-Learn.
Text coding for NLP, Recurrent Neural Networks (RNN), LSTM, Attention Mechanisms, Transformer Model and chatbot building.
You don’t need any prior qualifications in computer science or programming to join our bootcamp. We assume no prior knowledge and will guide you through the basics in the first few weeks, ensuring you build a strong foundation from the ground up. Whether you're starting from scratch or upskilling for your current role (or your next opportunity), our programme is designed to help you progress quickly and confidently.
Show what you can do with real outcomes. Throughout your course, you’ll complete hands-on projects based on realistic scenarios. By the end, you’ll have a portfolio that demonstrates practical skills.
Learn with support from industry professionals. Get personalised feedback on your projects, help when you’re stuck, and guidance that keeps you moving forward.
Stay focused with a structured path. Each course follows a clear roadmap with learning objectives, skill milestones, and project deliverables—so you always know what’s next and why it matters.
