What you’ll learn
A project-based curriculum designed to take you from “just curious” to applying Data Science & AI workflows—data prep, modelling, and deployment—in as few as 12 weeks (full-time) or 24 weeks (part-time). Learn in English with live sessions that fit Romania (Bucharest time, EET/EEST).
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 shaping how teams build products and make decisions. In this pre-work chapter, you’ll cover the foundations—Python, SQL, and key maths concepts—so you can start the bootcamp with confidence and a shared baseline.
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
From Monday to Friday 10:30am to 4:30pm (Bucharest time)
Lecture Session
10:30am - 12:00pm
Lecture Session
12:30pm - 02:00pm
Hands-on Session
03:00pm - 04:30pm
How you’ll learn
Online Live Learning
- Join interactive live sessions online and collaborate with instructors and peers in real time. Sessions are scheduled to work well for learners in Romania (Bucharest time, EET/EEST), so you can participate without timezone friction.
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 short readings and videos, then use live time for practice, Q&A, and feedback—so you learn by doing, not by memorising.
Guided Practice
- Work through hands-on exercises, labs, and real projects with guidance, code reviews, and portfolio-building support—ideal for focused upskilling.
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. We assume no prior knowledge and guide you through the fundamentals in the first weeks, so you build confidence from the ground up. Whether you’re starting fresh or upskilling alongside your current role, the program is designed to help you progress quickly and consistently—online, in English, and in Bucharest-friendly time slots.
- 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 practical guidance on portfolio storytelling, LinkedIn optimization, and job-search habits—plus quick drop-ins for last-minute CV improvements.
Personalised Career Counseling Sessions
Structured 1:1 sessions to clarify your direction, define realistic next steps, and build a plan—whether your goal is internal growth, a new role, or moving into a tech-adjacent position.
Mock Interviews
Practice common behavioural and role-specific interview questions, learn how to talk about your projects clearly, and get support with remote interview dynamics and salary conversations.
Resume & Cover letter Reviews
Get tailored feedback on your CV/resume and cover letter so recruiters can quickly understand your strengths. We focus on clarity, ATS-friendly structure, and presenting projects in a way that fits Romania and EU hiring expectations.
Job and Internship Round-Up
A curated selection of opportunities shared by our career team—covering junior roles, internships, and skill-building positions, including remote-friendly options where available.
Career Resources Platform Access
Access career materials, templates, assignments, and tech industry resources inside our learning platform—so you can keep improving even after the bootcamp.
Professional Guidance & Networking Events
Meet tech professionals for practical advice and perspective. Join our Career Chats to learn how different roles work in real teams and expand your network in Romania and beyond.
Alumni Networking
Stay connected with classmates and CLA alumni to share opportunities, exchange ideas, and keep learning together through thoughtful discussions and community support.
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.