What you’ll learn
We’ll guide you through a carefully curated curriculum designed to take you from ‘curious’ to confident in Data Science & AI in as little 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, preparation, visualisation and exploration
Classical machine learning
Supervised and unsupervised learning, model improvement, Naive Bayes, SVM, random forests, ML 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, transformers, and chatbot building
Chapter 0: Pre-work
Data science & AI skills are increasingly valuable across industries. This track focuses on working with data, preparing it, analysing it, and building machine learning models to generate insights and predictions. In this chapter, you’ll cover foundations to get ready for the bootcamp.
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 tackles the curve fitting problem (finding the best curve equation for a dataset). It’s divided into sections that exercise key concepts such as OOP, SQL, linear algebra, and the machine learning workflow.
Learning schedule
Monday to Friday, 09:30–15:30 (Stockholm time, 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
- Learn through interactive live sessions where you engage directly with instructors and peers in real time—supporting collaboration, feedback, and faster skill development.
Self-study
- Part-time: 9 hours live learning + 11 hours self-study = 20 hours per week
- Full-time: 22.5 hours live learning + 17.5 hours self-study = 40 hours per week
Flipped classroom
- Use a flipped classroom approach: prepare with guided material, then use live time to practise, ask questions, and deepen understanding.
Guided practice
- Build skills through hands-on exercises and portfolio projects—supported by instructors and structured feedback so you keep progressing.
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 prior qualifications to join. We assume no prior knowledge and guide you through the essentials early on, helping you build a strong foundation from the ground up. Whether you’re exploring data for the first time or upskilling for more analytical work, the programme is designed to get you progressing quickly and confidently.
- Laptop or computer: A reliable laptop or desktop computer with sufficient processing power, capable of running the required tools.
- 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 algorithms and programming: Some familiarity with programming concepts helps you follow the course more comfortably.
- English proficiency: B1 level (or equivalent) 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 pre-work to establish a solid foundation.
Career services centre
Career development workshops
Open sessions for you and the wider CLA community. Get a feel for our Career Services Centre, meet our career advisors, and drop in for quick CV/LinkedIn polish or practical job-search tips.
1:1 career coaching sessions
Structured, personalised sessions to clarify your goals and build an action plan—whether you’re aiming for a new role, internal progression, or stronger technical responsibilities.
Mock interviews
Practise common interview questions and learn how to communicate impact, highlight your strengths, handle technical and behavioural interviews, and navigate salary discussions with confidence.
CV and cover letter reviews
Get tailored feedback on your CV and cover letter to help recruiters understand your skills, projects, and value—aligned to the roles you’re targeting.
Job and internship round-up
Curated opportunities, platforms, and search strategies to help you find roles that match your level—whether you’re applying for junior positions, internships, or upskilling-friendly roles.
Career resources platform access
Access to career materials, assignments, templates, and tech industry resources—so you can keep improving your profile and approach over time.
Professional guidance and networking events
Meet professionals, ask questions, and learn from real industry experiences. Get guidance and connect with others through structured career chats and community events.
Alumni networking
Stay connected with classmates and alumni to share resources, discuss industry topics, and help one another spot relevant 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.