Data Science & AI.

Launch your career in data science and artificial intelligence with hands-on, industry-ready experience. In this immersive program, you’ll learn how to turn raw data into powerful insights, train intelligent models, and build real-world AI applications. Gain experience in data analytics, preparing and visualizing data, classic machine learning (supervised & unsupervised learning, SVMs, random forests), deep learning architectures (including neural networks, CNNs, autoencoders, and data augmentation)and Natural Language Processing. Graduate with a professional portfolio and the practical expertise to stand out in the rapidly growing AI and data-driven job market.

Level

Beginner

Duration

120 Hours

Format

Self-Paced

Certification

Included

Data Science and AI using Python with charts

Why Learn with Code Labs Academy?

Portfolio‑First Projects

Build proof, not just knowledge. You’ll complete hands‑on assignments inspired by real tasks, then turn them into portfolio work you can share with managers, clients, or recruiters.

Mentor Support

Get feedback that helps you improve faster. Our mentors review your work, answer questions, and help you understand trade‑offs—so you learn how to think like a practitioner.

Clear Learning Roadmap

Stay focused with a structured path. Each course maps skills to milestones and projects, so you always know what you’re learning and why it matters.

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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).


Career Coaching & Preparation

Learning is only one part of the journey. If your goal is to use your new skills in a role (or to grow in your current one), we can support you with portfolio polishing, interview preparation, and a clearer job-search plan aligned with your strengths.



Ready to Level Up Your Skills?

Start building momentum today. Join our learning community and develop practical tech skills you can apply right away—at work, on side projects, or in your next role.

Frequently Asked Questions