What you’ll Learn
A practical curriculum that takes you from fundamentals to applied 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, Probabilities and Statistics.
Data Analytics
Data Analysis, Data Preparation, Data Visualization 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, Autoencoder Architecture, Data Augmentation, Tensorflow, Keras and Scikit-Learn.
Natural Language Processing
Text coding for NLP, Recurrent Neural Networks (RNN), LSTM, Attention Mechanisms, Transformer Model and chatbot building.
Chapter 0: Pre-Work
Data science and AI are increasingly used across industries to turn data into decisions. In this chapter, we cover the foundations you’ll need to start your learning journey—so you can build confidence before the live classes begin.
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)
Lecture Session
09:30 - 11:00
Lecture Session
11:30 - 13:00
Hands-on Session
14:00 - 15:30
Our Methodology
Online Live Learning
- Interactive live sessions where you learn with instructors and peers in real time—ideal for staying on track in CET/CEST.
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
- Study key concepts independently, then use live sessions to practise, ask questions, and apply the material through exercises and projects.
Guided Practice
- Hands-on exercises and portfolio projects with structured feedback—so you build skills you can use in real scenarios.
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 formal computer science qualifications to join. We cover the essentials early on and help you build confidence step by step. This bootcamp works for beginners and for professionals looking to upskill in data and AI—just be ready to commit time each week and practise consistently.
- 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 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 practicing coding, especially during the pre-unit to establish a solid foundation for continuing in the bootcamp.
Career Services Center
Career Development Workshops
Short, practical workshops for learners and the wider CLA community—covering topics like CV structure, LinkedIn optimisation, and how to explain projects clearly. Great if you want to refresh your approach or get quick feedback.
Personalised Career Counseling Sessions
1:1 sessions to clarify your goals and build a realistic plan—whether you’re upskilling for your current job, moving into a new specialism, or preparing to apply for new roles.
Mock Interviews
Practise common interview questions and get structured feedback. We’ll also cover how to talk about your projects, handle technical questions, and approach salary discussions (including typical expectations for Norway vs. international roles).
CV & Cover Letter Reviews
Targeted recommendations on your CV and cover letter—tailored to the roles you’re applying for and aligned with common recruitment expectations in Norway and across Europe.
Job and Internship Round-Up
A curated list of current opportunities—selected by our career specialists and focused on realistic entry-level and junior-friendly roles, plus positions suitable for upskilling professionals.
Career Resources Platform Access
Access to career materials inside our platform—including templates, assignments, examples, and resources for navigating the tech job market.
Professional Guidance & Networking Events
Join online events with professionals from the industry to learn how teams work, what hiring managers look for, and how to build connections—useful whether you’re applying in Norway or remotely across Europe.
Alumni Networking
Stay connected with your cohort and alumni community. Share resources, discuss tools and trends, and keep each other informed about relevant job openings and events.
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.