What you’ll learn
Guiding you through a carefully curated curriculum that helps you build practical Data Science & AI skills—from analytics to machine learning—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 & AI are among the most in-demand skill sets today. They involve working with data, exploring it, and building machine learning models to help answer questions and predict outcomes. In this chapter, we cover the foundations 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
Monday to Friday 10:30–16:30 (EET/EEST)
Lecture session
10:30 - 12:00
Lecture session
12:30 - 14:00
Hands-on session
15:00 - 16:30
Our methodology
Online live learning
- Learn through interactive online live sessions where you engage directly with instructors and peers in real time. Live classes are scheduled to work well in Finland (EET/EEST), supporting collaboration, feedback, and rapid skill development.
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 materials before class, then use live sessions for practice, discussion, and feedback.
Guided practice
- Build your skills through hands-on exercises, supportive coaching, and portfolio-building projects to turn learning into practice.
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 formal computer science background to join. We guide you through the essentials and help you build a strong foundation from the start. If you’re upskilling in Finland—whether alongside work or studies—be ready to practise regularly during pre-work and throughout the bootcamp to get the most out of the programme.
- 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
Open sessions for you and the wider CLA community. Get a feel for our Career Services, meet our advisors, and drop in for practical guidance—like last-minute CV polishing or LinkedIn updates.
1:1 career counselling sessions
Structured, supportive sessions to clarify your goals and build a plan—whether you’re aiming to grow in your current role, transition to a more technical position, or explore new opportunities.
Mock interviews
Practise common behavioural and competency questions. Learn how to highlight your strengths, communicate impact, and handle salary and expectation conversations with confidence.
CV & cover letter reviews
Get personalised feedback on your CV and cover letter, tailored to help you stand out—especially when applying for roles in Finland and across the EU.
Job and internship round-up
A curated selection of new opportunities shared by our career specialists—helpful for learners looking for junior roles, internships, or entry points into tech-enabled teams.
Career resources platform access
Access career materials, assignments, templates, and tech industry resources via our learning platform—so you can keep improving even after the bootcamp.
Professional guidance & networking events
Meet tech professionals for real-world insights and career advice, and expand your network through community events and Career Chats.
Alumni networking
Stay connected with classmates and CLA alumni to share resources, discuss industry topics, and exchange job leads and learning recommendations.
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.