The data industry is evolving rapidly, and by 2026, certain roles will be critical for driving innovation, efficiency, and strategic decision-making across industries. As organizations increasingly ...

The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Data Is the Fuel, but It's Often Unfit for the Rid... Data Is the Fuel, but It's Often Unfit for the Rid... When we talk about artificial intelligence (AI) in investing, the conversation often jumps ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The global demand for Explainable AI (XAI) is accelerating as organizations seek greater transparency and accountability in artificial intelligence systems used across critical industries. According ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

The programme aims to prepare the next generation of technology professionals from underserved communities by equipping them with practical skills in AI and Data Science ...