What you’ll learn
A curated curriculum designed to build your Data Science & AI skills—from foundations to machine learning and deep learning—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.
Classic Machine Learning
Machine learning, supervised and unsupervised learning, ML model enhancement, 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 processing for NLP, RNNs and LSTMs, attention mechanisms, transformer models, 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 (Copenhagen time, CET/CEST)
Monday to Friday, 09:30–15:30
Lecture session
09:30 - 11:00
Lecture session
11:30 - 13:00
Hands-on session
14:00 - 15:30
Our methodology
Online live learning
- Join interactive live online sessions where you engage with instructors and peers in real time. For learners in Denmark, live sessions run in Copenhagen time (CET/CEST).
Self-study
- Part-time: 9 hours live learning, 11 hours self-study (20 hours/week)
- Full-time: 22.5 hours live learning, 17.5 hours self-study (40 hours/week)
Flipped classroom method
- Prepare with guided material before class, then use live sessions for practice, feedback, and deeper understanding.
Guided practice
- Build confidence through hands-on exercises, structured projects, and portfolio work—supported by feedback and practical review.
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 in computer science or programming to join. We start from the fundamentals and guide you step by step. Whether you’re new to tech or upskilling alongside work in Denmark, the programme is designed to help you progress 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.
- Comfort with basic programming concepts: No prior experience is required, but familiarity with basic programming logic will help you follow the course more 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 strong foundation for the bootcamp.
Career Services Center
Career Development Workshops
Open sessions for you and the wider CLA community. Meet our Careers Advisor, explore what our Career Center offers, and drop in for quick CV or LinkedIn improvements.
Personalised Career Counselling Sessions
Structured 1:1 sessions to clarify your goals and create a plan—whether you’re progressing in your current role, exploring a new direction, or preparing for a technical interview.
Mock Interviews
Practise common behavioural and technical interview questions. Learn how to highlight your strengths, communicate your project work, and navigate salary conversations with confidence.
CV & Cover Letter Reviews
Get personalised, practical feedback on your CV and cover letter—tailored to help recruiters quickly understand your skills, projects, and impact.
Job & Opportunity Round-Up
A curated round-up of relevant roles and opportunities—selected by our career specialists and aligned with junior and upskilling pathways.
Career Resources Platform Access
Access templates, assignments, and resources on our learning platform—from CV structure and LinkedIn checklists to job-search strategy and interview preparation.
Professional Guidance & Networking Events
Join online events with tech professionals to learn from real experiences, ask questions, and expand your network—including opportunities relevant to Denmark and the wider European market.
Alumni Networking
Stay connected with classmates and alumni. Share resources, discuss industry trends, and exchange opportunities—building long-term community in Denmark 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.