What you’ll learn
Guiding you through a carefully curated curriculum designed to take you from ‘just curious’ to confident in Data Science & AI in as few as 12 weeks (full-time) or 24 weeks (part-time), with live sessions aligned to CET/CEST for learners in Hungary.
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, model improvement, 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, recurrent neural networks (RNN), LSTM, attention mechanisms, transformer models, and chatbot building.
Chapter 0: Pre-Work
Data Science & AI has become one of the most valuable skill sets in recent years. It involves working with data, cleaning and evaluating it, and developing machine learning models to predict outcomes and support decisions. In this chapter, we cover the foundations of Data Science & AI 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, 09:30–15:30 (CET/CEST, Budapest time)
Lecture Session
09:30 - 11:00
Lecture Session
11:30 - 13:00
Hands-on Session
14:00 - 15:30
Our Methodology
Online Live Learning
- Elevate your learning experience with interactive online live sessions, where you’ll engage directly with instructors and peers in real time, with schedules aligned to CET/CEST for learners in Hungary.
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
- Experience a dynamic learning approach with our flipped classroom method, empowering you to learn actively and engage deeply in our bootcamp curriculum.
Guided Practice
- Engage in an immersive learning experience where we focus on active participation, hands-on exercises, and portfolio building to help you develop practical, reusable skills.
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 computer science degree to join our bootcamp. We assume no prior knowledge and guide you through the basics in the first weeks, helping you build a strong foundation step by step. Whether you’re completely new or upskilling for a more technical role, the programme is designed to help you progress quickly and confidently, from Hungary on a CET/CEST schedule.
- 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 of Algorithms and Programming: Some familiarity with programming concepts 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, especially during the pre-unit to establish a solid foundation for the bootcamp.
Career Services Center
Career development workshops
Open sessions for you and the wider CLA community. Get a feel for what our Career Center offers, meet our careers advisors, and drop in for quick CV and LinkedIn improvements.
Personalised 1:1 career guidance
Structured sessions to clarify your goals and map a realistic plan, whether you’re upskilling for your current role in Hungary or preparing for new opportunities.
Mock interviews
Practise common behavioural and technical interview questions, learn how to communicate your strengths, and get comfortable discussing expectations and salary ranges.
CV & cover letter reviews
Get actionable feedback on your CV and cover letter, tailored to highlight your projects and skills in a way recruiters and hiring managers can quickly understand.
Job and internship round-up
A curated overview of opportunities, shared by our career specialists, with a focus on junior and entry-level roles, including remote options that can work from Hungary.
Career resources platform access
Access career materials, practical assignments, templates, and curated tech-industry resources through our learning platform.
Professional guidance & networking events
Meet tech professionals to learn about different roles and career paths, and connect with others through our Career Chat events.
Alumni networking
Stay connected with classmates and alumni, share insights, discuss trends, and exchange opportunities that may be relevant to learners in Hungary and across Europe.
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.