What you’ll learn
A project-based curriculum that covers analytics, machine learning and modern AI. Learn Python and SQL, work with real data, and build models for computer vision and NLP—available full-time in 12 weeks or part-time in 24 weeks for learners in Luxembourg (CET/CEST).
Foundation
SQL, Python, Jupyter Notebook, Git/GitHub, linear algebra, probability and statistics
Data analytics
Data analysis, preparation, visualisation, and exploration
Classical machine learning
Supervised/unsupervised learning, model improvement, pipelines, and classification
Deep learning
Neural networks, CNN architectures, autoencoders, data augmentation, TensorFlow, Keras and scikit-learn
Natural language processing
NLP fundamentals, RNN/LSTM, attention mechanisms, transformers, and chatbot building
Chapter 0: Pre-Work
Data science has been one of the most prestigious careers in recent years. It involves handling data, cleaning it, evaluating it, and developing machine learning models to predict outcomes of events. In this chapter, we will cover the foundations of data science 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
How you’ll learn
Live online learning
- Join interactive live sessions where you can ask questions, collaborate with peers, and get feedback in real time. Sessions run in Central European Time (CET/CEST), which is a natural fit for learners based in Luxembourg.
Structured self-study
- Part-time: 9 hours of live learning + around 11 hours of self-study (20 hours/week total)
- Full-time: 22.5 hours of live learning + around 17.5 hours of self-study (40 hours/week total)
Flipped classroom approach
- Prepare with guided materials before class, then use live sessions for discussion, practice, and problem-solving. This keeps learning active and helps you apply concepts faster.
Guided, project-based practice
- Build skills by doing: exercises, projects, and portfolio work supported by instructors. The aim is steady progress, clear feedback, and practical outcomes you can demonstrate.
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 a formal computer science background to get started, but comfort with basic programming ideas will help. We provide pre-work and early guidance so you can build the fundamentals and then move into real Data Science & AI workflows. If you’re joining from Luxembourg, sessions are scheduled in CET/CEST for a smoother learning routine.
- 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 in algorithmics and programming: Familiarity with core programming concepts so you can follow the course comfortably (we’ll support you with pre-work to strengthen this foundation).
- 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—especially during the pre-unit—to establish a strong foundation for the bootcamp.
Career Services Centre
Career workshops & clinics
Short sessions for you and the wider CLA community—covering CV structure, LinkedIn optimisation, portfolio presentation, and practical job-search habits. Perfect for quick improvements and last-minute polish.
1:1 career coaching
Structured sessions to clarify your goals and create a realistic plan. Useful whether you’re applying for new roles, aiming for internal progression, or mapping out a longer-term transition.
Mock interviews
Practise common interview formats (behavioural and role-specific), learn how to structure strong answers, and get feedback on communication, confidence, and salary conversations.
CV & cover letter reviews
Get tailored, actionable feedback to improve clarity, impact and relevance—so recruiters can quickly understand your skills and the value of your projects.
Opportunities round-up
Curated roles and internships shared by our team and community, with a focus on junior-friendly opportunities and realistic entry points.
Career resources access
Access to career templates, exercises, and industry resources within our learning platform—so you can revisit guidance when you need it.
Networking & professional guidance events
Talk with tech professionals, ask questions about day-to-day work, and learn how teams hire and grow. Join community events to connect with peers and build your network—useful in Luxembourg’s international job market.
Alumni community
Stay connected with classmates and alumni to share resources, discuss industry trends, and circulate relevant opportunities across Luxembourg and beyond.
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.