What you’ll learn
Coaching you through a carefully curated curriculum designed to take you from ‘just curious’ to ‘portfolio-ready’ in Data Science & AI in as few as 12 weeks (full-time) or 24 weeks (part-time).
Foundation
SQL, Python, Jupyter Notebook, Git and GitHub, linear algebra, probability, and statistics.
Data analytics
Data analysis, data preparation, data visualisation, and data exploration.
Classical machine learning
Machine learning, supervised and unsupervised learning, model improvement, Naive Bayes, SVM, Random Forests, ML pipelines, and classification.
Deep learning
Neural networks (implementation, troubleshooting & optimisation), CNN architectures, autoencoders, data augmentation, TensorFlow, Keras, and scikit-learn.
Natural language processing
Text coding for NLP, recurrent neural networks (RNN), LSTM, attention mechanisms, transformer models, and chatbot building.
Chapter 0: Pre-Work
Data Science & AI are among the most in-demand skill sets today. This bootcamp focuses on working with data, cleaning it, evaluating it, and building machine learning models to predict outcomes. In this chapter, we cover the foundations to get you ready to begin your learning journey.
Introduction to Python
- Python Language And History
- The Basics Of Python
- Fundamental Data Structures In Python
- Classes And Objects
- Modules And Packages
- Input/Output
- Errors And Exceptions
Environments
- Python Environments
- Anaconda
- Jupyter Notebooks
SQL and Databases
- SQL Fundamentals
- SQL Queries
Linear Algebra
- Scalars And Vectors
- Matrices
- Norms
Git and GitHub
- Introduction to Version Control
- Workflow
- Inspecting Repositories
- Undoing Changes
- Fetching And Pulling Changes
- Pushing Changes
Project: Curve Fitting
- This project is about solving the 'Curve fitting' problem, which involves finding the best curve equation to fit a given dataset. It will guide you through an example of this problem and is divided into sections, where each section will exercise the use of fundamental concepts such as OOP, SQL, Linear Algebra, and the final Machine learning workflow.
Learning schedule (CET/CEST)
Monday to Friday 09:30 - 15:30 (CET/CEST)
Lecture session
09:30 - 11:00
Lecture session
11:30 - 13:00
Hands-on session
14:00 - 15:30
Our methodology
Live online learning
- Here at CLA, elevate your learning experience with interactive live sessions where you engage directly with instructors and peers in real time — fostering collaboration and rapid skill development. Sessions are scheduled in CET/CEST, making it easy to join from Belgium.
Self-study
- Part-time: 9 hours live learning, 11 hours of self-study, total 20 hours per week
- Full-time: 22.5 hours live learning, 17.5 hours of self-study, total 40 hours per week
Flipped classroom method
- Experience a dynamic learning approach with our flipped classroom method, empowering you to learn actively and engage deeply in our bootcamp curriculum.
Guided practice
- Engage in an immersive learning experience at our bootcamp, where we focus on active participation, hands-on exercises, and portfolio-building to ensure a solid foundation of your knowledge.
Prefer to learn at your own pace?
Learn with our On-demand Data Science & AI course at your own pace with complete flexibility through our immersive, self-paced program. Master how to transform raw data into powerful insights, train intelligent models, and build real-world AI applications and graduate ready to launch your career in the world of data-driven innovation.
What you’ll need
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 new to the field or looking to upskill, our programme is designed to help you get up to speed quickly and confidently.
- Laptop or computer: A reliable laptop or desktop computer with sufficient processing power and capable of running necessary programs.
- Stable internet connection: Reliable internet access for live learning sessions, hands-on labs, and assignments.
- Basic computer literacy: Ability to navigate operating systems, productivity software, and internet browsers.
- Basic knowledge of algorithms and programming: Familiarity with programming concepts to follow the courses comfortably.
- English proficiency: B1 level with the ability to understand technical materials and communicate effectively, as the bootcamp is conducted in English.
- Commitment to learning: A proactive attitude toward learning and practising coding, especially during the pre-unit to establish a solid foundation for continuing in the bootcamp.
Career Services Centre
Career development workshops
Taster sessions for you and the wider CLA community. Sample what our Career Services Centre offers, meet our careers adviser, and drop in for help with those last-minute CV updates.
Personalised career counselling sessions
Structured 1:1 sessions to clarify your goals and create a practical plan to reach them — whether you’re upskilling for your current role or aiming for a new opportunity.
Mock interviews
Practise common interview questions and learn how to communicate your strengths, talk through projects, and navigate salary expectations with confidence.
CV & cover letter reviews
Get personalised recommendations on your CV or cover letter, tailored to help you stand out and secure interviews for roles that match your goals.
Job and internship round-up
A curated selection of junior roles, internships and entry-level opportunities shared by our career specialists — with guidance on how to approach applications.
Career resources platform access
Access our learning platform’s career materials, assignments and tech industry resources — including templates, examples and practical exercises.
Professional guidance & networking events
Meet tech professionals, hear how they built their careers, and join Q&A sessions to get practical advice and expand your network — including within Belgium and across Europe.
Alumni networking
Connect with classmates and CLA alumni to share useful resources, start insightful discussions, and exchange job opportunities and referrals.
Why Choose Code Labs Academy?
1-to-1 Career Coaching
Personalised support from career specialists: CV and LinkedIn refresh, mock interviews, and a tech-focused job-search strategy.
Portfolio-Ready Projects
Graduate with a GitHub-ready portfolio of real-world projects—built in class and polished with mentor feedback.
Industry-Driven Curriculum
Curriculum refreshed every quarter to match current hiring needs in AI, cybersecurity, and web development.
Recognised Certificate
Showcase your AZAV-accredited Code Labs Academy certificate on LinkedIn, your CV, and visa applications.