What you’ll Learn
Coaching you through an especially curated curriculum designed to take you from ‘just curious’ to ‘fully certified’ in data science in as few as 12 weeks (full 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 has been one of the most prestigious 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 will cover the foundations of data science 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
From Monday to Friday 9:30am to 3:30pm
Lecture Session
9:30am - 11:00am
Lecture Session
11:30am - 01:00pm
Hands-on Session
02:00pm - 03:30pm
Our Methodology
Online Live Learning
- Here at CLA, elevate your learning experience with our interactive online live sessions, where you'll engage directly with instructors and peers in real-time, fostering collaboration and rapid skill development.
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 at our bootcamp, where we focus on active participation, hands-on exercises, and portfolio building to ensure a solid foundation to 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 or looking for a career change, our program 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 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 Centre
Career & Upskilling Workshops
Short, practical sessions for CLA learners and the wider community. Join for actionable guidance, Q&A, and quick improvements—like last-minute CV edits, interview prep drills, or LinkedIn profile upgrades.
1:1 Career Coaching Sessions
Structured, supportive coaching to clarify your direction and build a plan. Whether you’re aiming for a new role, growing in your current company, or mapping a long-term path, we’ll help you define next steps and stay accountable.
Mock Interviews & Feedback
Practise real interview scenarios—from behavioural questions to structured storytelling. Learn how to highlight your strengths, explain projects clearly, and approach salary and role-fit conversations with more confidence.
CV & Cover Letter Reviews
Get detailed feedback tailored to your target roles. We’ll help you improve clarity, structure, and impact—so recruiters can quickly see what you can do (and why it matters).
Job & Internship Shortlist
Curated opportunities shared by our team, selected with junior and upskilling-friendly roles in mind. Great if you want help filtering noise and focusing on realistic next steps.
Career Resources Library
Access templates, guides, assignments, and industry resources inside our learning platform—covering job-search strategy, portfolio presentation, interview preparation, and workplace readiness.
Mentor Talks & Networking Sessions
Meet professionals from across the tech ecosystem to learn how roles work in practice and ask questions directly. Network with peers and speakers in community sessions designed to be welcoming and useful—especially for first-time attendees.
Alumni Community Network
Stay connected after graduation. Share insights, resources, and opportunities with classmates and alumni, and keep learning through discussions and collaboration across cohorts.
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.