What you’ll learn
We coach you through a carefully curated curriculum designed to take you from ‘just curious’ to confident and job-ready in Data Science & AI in as few as 12 weeks (full time).
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 enhancement, Naive Bayes, SVM, random forests, ML pipelines and classification
Deep Learning
Neural networks (implementation, troubleshooting and optimisation), CNN architectures, autoencoder architectures, data augmentation, TensorFlow, Keras and scikit-learn
Natural Language Processing
Text encoding for NLP, recurrent neural networks (RNN), LSTM, attention mechanisms, transformer models and chatbot building
Chapter 0: Pre-Work
Data science has been one of the most prestigious and in-demand careers in recent years. It involves handling data, cleaning it, evaluating it and developing machine learning models to predict outcomes of events. 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 end-to-end machine learning workflow.
Learning Schedule
From Monday to Friday, 9:30am to 3:30pm (UK time)
Lecture session
9:30am - 11:00am (UK time)
Lecture session
11:30am - 01:00pm (UK time)
Hands-on session
02:00pm - 03:30pm (UK time)
Our Methodology
Live online learning
- At Code Labs Academy, you’ll learn in interactive live online sessions where you can ask questions in real time, collaborate with peers and get feedback from instructors – helping you build skills faster and with more confidence.
Self study
- Part time: around 9 hours of live learning and 11 hours of self study, totalling 20 hours per week.
- Full time: around 22.5 hours of live learning and 17.5 hours of self study, totalling 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 with the bootcamp curriculum.
Guided practice
- Engage in an immersive learning experience where we focus on active participation, hands-on exercises and portfolio building to ensure a solid foundation for your knowledge.
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 any prior qualifications in computer science or programming to join our bootcamp. We assume no prior knowledge and will guide you through the basics in the first few weeks, ensuring you build a strong foundation from the ground up. Whether you’re new to the field, changing careers or upskilling in your current role, our programme is designed to get you up to speed quickly and confidently.
- Laptop or Computer: A reliable laptop or desktop computer with sufficient processing power and capable of running necessary programmes.
- 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 course 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 towards learning and practising coding, especially during the pre-unit, to establish a solid foundation for continuing in the bootcamp.
Code Labs Academy Career Services
Career development workshops
Taster sessions for you and the wider Code Labs Academy community. Sample what our Career Services offer, meet our Careers Advisor and drop in for last‑minute CV tidy‑ups.
Personalised career counselling sessions
Structured 1:1 sessions to identify your career goals and create practical strategies to achieve them through friendly counselling conversations and Career Action Planning.
Mock interviews
Practise common behavioural interview questions and learn how to show employers the value you bring, highlight your strengths and navigate salary and offer discussions with confidence.
CV & cover letter reviews
Get personalised, actionable feedback on your CV and cover letters, tailored to catch the attention of recruiters and help you secure interviews for the roles you want.
Job and internship round‑up
Regular updates on new employment and internship opportunities, hand‑picked by our career specialists and tailored to be genuinely entry‑level or early‑career friendly.
Career resources platform access
Ongoing access to our learning platform’s career service materials, assignments and tech‑industry resources to support your job search and long‑term development.
Professional guidance & networking events
Meet tech professionals from different industries to get career advice and insights, and expand your network through our Career Chat events and community meet‑ups.
Alumni networking
Connect with classmates and Code Labs Academy alumni to share opportunities, swap experiences, start insightful discussions and support each other’s next career steps.
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.