What You’ll Learn
We coach you through a specially curated curriculum designed to take you from “just curious” to confidently practicing data science & AI 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 & optimization), CNN architectures, autoencoder architectures, data augmentation, TensorFlow, Keras, and Scikit-Learn
Natural Language Processing
Text coding for NLP, recurrent neural networks (RNN), LSTM, attention mechanisms, transformer models, and chatbot building
Chapter 0: Pre-Work
Careers in data science & AI have been among the most in-demand in recent years. They involve 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 & 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
From Monday to Friday, 9:30am to 3:30pm (live online)
Lecture Session
9:30am - 11:00am
Lecture Session
11:30am - 01:00pm
Hands-on Session
02:00pm - 03:30pm
Our Methodology
Online Live Learning
- At Code Labs Academy, 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, looking for a career change, or upskilling in your current role, 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 (intermediate) 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
Intro workshops and focused sessions for you and the wider Code Labs Academy community. Sample what our Career Services Center offers, meet our Career Advisor, and drop in for last-minute resume tune-ups.
Personalized Career Counseling Sessions
Structured 1:1 sessions to clarify your career goals and build a plan to reach them through supportive coaching and Career Action Planning.
Mock Interviews
Practice common behavioral and technical interview questions, learn how to highlight your strengths, show employers what you bring to the table, navigate salary conversations, and more.
Resume & Cover Letter Reviews
Get personalized feedback on your resume or cover letter, tailored to capture recruiters’ attention and help you land interviews for roles you’re excited about.
Job and Internship Roundup
A curated list of the latest job and internship opportunities, hand-picked by our career specialists and focused on realistic entry-level and early-career roles.
Career Resources Platform Access
Ongoing access to our learning platform’s career resources, assignments, templates, and tech industry insights to support your job search and long-term growth.
Professional Guidance & Networking Events
Connect with tech professionals to get career advice, hear real-world stories, and expand your network through live Career Chat events and panel discussions.
Alumni Networking
Stay in touch with classmates and alumni to share resources, spark insightful conversations, and surface job opportunities that may be a great fit for your community.
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.