What you’ll learn
A hands-on Data Science & AI curriculum built to help you analyse data, build models, and understand modern ML workflows—typically completed in 12 weeks full-time or 24 weeks part-time.
Foundation
SQL, Python, Jupyter Notebook, Git/GitHub, linear algebra, probability, and statistics
Data Analytics
Data analysis, preparation, visualisation, and exploration
Classic Machine Learning
Supervised/unsupervised learning, pipelines, model improvement, and evaluation
Deep Learning
Neural networks, CNNs, troubleshooting and optimisation, TensorFlow/Keras, and Scikit-Learn
Natural Language Processing
Text processing, RNN/LSTM, attention mechanisms, transformers, and chatbot building
Chapter 0: Pre-Work
Data Science & AI power everything from smarter products to better decision-making. In this chapter, we cover the foundations—working with data, building reliable workflows, and understanding the basics you’ll need to start modelling confidently.
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–Friday, 09:30–15:30 (Iceland time, UTC/GMT)
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 learn directly from instructors in real time—accessible from Iceland (UTC/GMT) and across Europe.
Self-study that actually works
- 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 approach
- Use pre-reading and guided materials to prepare, then spend live sessions practising, discussing, and applying what you’ve learned—so class time stays hands-on and useful.
Guided practice and portfolio building
- You’ll practise continuously through exercises, labs, and projects—building a portfolio that demonstrates your skills clearly, whether your goal is professional upskilling, freelance work, or a new role.
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
No formal prerequisites are required, but you’ll get the most out of the program if you’re ready to practise consistently. We cover fundamentals early (especially during pre-work) and build toward applied machine learning and AI projects—useful for analysts, engineers, and curious professionals upskilling from Iceland.
- Laptop or computer: A reliable laptop or desktop computer with enough power to run development tools and notebooks comfortably.
- Stable internet connection: Reliable internet access for live sessions, labs, and assignments.
- Basic computer literacy: Comfort navigating an OS, using productivity tools, and working online.
- Comfort with basic programming concepts: Some familiarity is helpful (variables, loops, functions). If you’re new, the pre-work is designed to get you ready.
- English proficiency: B1 level or higher to follow technical content and participate in discussions.
- Commitment to learning: A proactive attitude toward practice—especially early on—to build a strong foundation for later ML topics.
Career Services Center
Career & skills workshops
Short sessions for learners and the wider CLA community. Join practical workshops on topics like portfolio storytelling, LinkedIn optimisation, and how to map your skills to real roles in the tech market.
Personalised 1:1 guidance
Structured sessions to clarify your goals and build an action plan. Whether you want to grow in your current job, move into a more technical role, or explore a new path, we’ll help you plan realistic next steps.
Mock interviews (behavioural + technical)
Practise common interview scenarios and learn how to communicate your process. We cover STAR-style answers, technical walkthroughs, salary conversations, and how to follow up professionally.
CV & cover letter reviews
Get detailed feedback tailored to your goal—more interviews, better alignment with job descriptions, and clearer proof of your skills through projects and outcomes (not just buzzwords).
Job and internship round-up
A curated view of opportunities that match early-career and junior-friendly requirements, plus roles suitable for professionals who are adding new technical capabilities through upskilling.
Career resources platform access
Access our career materials, templates, assignments, and curated resources for navigating the tech industry—available alongside your learning content.
Professional guidance & networking events
Join online events to hear from practitioners and ask real questions about roles, hiring, and day-to-day work. Learn how others broke into tech, advanced internally, or moved into more technical projects.
Alumni network
Stay connected with classmates and CLA alumni to share resources, discuss tools and trends, and highlight opportunities—especially valuable for learners in smaller markets like Iceland.
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.