What you’ll learn
A guided curriculum that takes you from data fundamentals to applied Data Science & AI in 12 weeks (full-time) or 24 weeks (part-time) - with real projects across analytics and machine learning.
Foundation
SQL, Python, Jupyter Notebooks, Git and GitHub, linear algebra, probability and statistics.
Data Analytics
Data analysis, preparation, visualisation and exploration.
Classic Machine Learning
Supervised and unsupervised learning, model improvement, Naive Bayes, SVM, Random Forests, pipelines and classification.
Deep Learning
Neural networks (implementation, troubleshooting & optimisation), CNNs, autoencoders, data augmentation, TensorFlow, Keras and scikit-learn.
Natural Language Processing
Text processing for NLP, RNNs, LSTMs, attention mechanisms, transformers and chatbot building.
Chapter 0: Pre-Work
Data Science & AI blends programming, statistics and modelling to turn data into insights and intelligent systems. In this pre-work chapter, you’ll build the foundations (Python, SQL, maths basics and tooling) so you can start the bootcamp ready to analyse, model and iterate.
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
Monday to Friday · 09:30–15:30 (CET/CEST)
Live class
09:30–11:00
Live class
11:30–13:00
Guided practice
14:00–15:30
How you’ll learn
Online Live Learning
- Join interactive live online classes where you can ask questions, collaborate with peers and get feedback in real time - scheduled to work well for learners in Slovenia (CET/CEST).
Independent study
- Part-time: 9 hours live learning + ~11 hours independent study (20 hours/week total)
- Full-time: 22.5 hours live learning + ~17.5 hours independent study (40 hours/week total)
Flipped Classroom Method
- We use a flipped-classroom approach: you preview key concepts, then use live sessions for discussion, practice and feedback. It keeps learning active and helps you progress faster.
Guided Practice
- Expect guided exercises, pair work and regular project reviews. You’ll build a portfolio as you learn, so every week produces something tangible.
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 computer science degree to join. We start from the basics and build step by step, with pre-work and ongoing support. Whether you’re learning for your current role, preparing for a new project, or aiming for a role change, the bootcamp is designed to help you progress with confidence.
- 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 programming and logic: Any prior coding helps, but it’s enough to be comfortable with basic programming concepts and logical problem-solving (we reinforce fundamentals during pre-work).
- English Proficiency: B1 level (or higher) with the ability to follow technical material and communicate effectively, as the bootcamp is taught in English.
- Commitment to Learning: A proactive attitude toward learning and practicing coding, especially during the pre-unit to establish a solid foundation for continuing in the bootcamp.
Career Services Center
Career workshops
Short, practical sessions for learners and the wider CLA community. Get a feel for our Career Services, meet our advisors, and drop in for focused support - from CV polishing to interview prep.
1:1 career guidance
Structured sessions to clarify your goals and build a realistic plan - whether you’re aiming to grow in your current role, move into a more technical position, or start applying for junior opportunities.
Mock interviews
Practise common behavioural and technical interview questions. Learn how to highlight your strengths, talk through projects, and approach salary conversations with more confidence.
CV & cover letter reviews
Get tailored feedback on your CV and cover letter to help you stand out, communicate impact, and match your applications to specific roles.
Jobs & internships round-up
Curated opportunities shared by our team to help you spot roles that match your level and direction. Great if you’re exploring your next step while upskilling.
Career resources access
Ongoing access to career materials, assignments and practical resources inside our learning platform - including templates, examples and guidance for your search.
Guidance & networking events
Meet professionals working in tech and product roles, ask questions, and learn how teams hire and work. Join Career Chat-style events to build connections and get real-world perspective.
Alumni community
Stay connected with classmates and alumni. Share resources, discuss tools and trends, and exchange relevant job openings and opportunities.
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.