AI

Tabular deep learning is the use of neural networks to solve problems involving structured data arranged in rows and columns. It offers a new way to analyze business, scientific, or transactional data by learning patterns directly from the table instead of manual feature engineering. This type of…

Active Learning is a machine learning technique where models ask for labels only on the data they are most uncertain about. Instead of labeling everything, this method helps teams focus effort where it matters most. The result is higher accuracy with fewer labeled examples. This approach is…

Data Centric AI is the practice of improving data quality to get better AI results. Instead of focusing only on models, this approach fixes messy labels, fills missing data, and balances datasets. The goal is to make the data more accurate, so even simple models can perform well. This concept is…

When Google DeepMind’s Amar, Product and Design Lead, introduced Gemini’s new Vibe Coding experience in AI Studio, it felt like the beginning of something extraordinary. The promise was simple yet powerful. Describe your app idea, and Gemini would automatically connect the right models and APIs to…

It started with a single tweet. Amazon CEO Andy Jassy announced a new multi-year partnership with OpenAI worth $38 billion. The deal, he said, would give OpenAI access to Amazon’s industry-leading AWS infrastructure and “hundreds of thousands of Nvidia GPUs.” Markets reacted instantly. Amazon’s…

Consulting was supposed to be the first white-collar casualty of AI. Headlines said as much. Fast Company warned consultants to beware. The Economist asked who needs Accenture in the age of AI. By early summer, reports noted roughly 60 billion dollars had been clipped from Accenture’s market cap.…

When one word can move markets, language becomes policy. That’s what happened when OpenAI’s Chief Financial Officer Sarah Friar used the word backstop during a Wall Street Journal interview. Within hours, it set off a chain reaction of outrage, think-pieces, and political commentary. What sounded…

The demand for AI and Machine Learning professionals is growing faster than ever. Whether you’re starting your journey or upskilling to stay ahead, earning a Certified AI and Machine Learning Expert credential from the Global Tech Council can set you apart. This guide covers the essential tips,…

Artificial Intelligence and machine learning are now central to how organizations grow, compete, and innovate. Companies want professionals who can turn data into decisions, automate complex workflows, and build trustworthy systems that scale. Demand keeps rising because AI delivers measurable…

The demand for AI and machine learning professionals remains one of the strongest in the global job market. In 2025, salaries for AI roles continue to climb as companies invest in automation, predictive analytics, and generative systems. Growth spans big tech, healthcare, finance, manufacturing,…

The AI revolution is reshaping the job market faster than most people realize. While automation will replace some roles, it is also creating new opportunities for those who can adapt. The key to staying ahead is to build skills that work with AI, not against it. Future-proofing your career means…

Earning a recognized AI and machine learning certification might sound like a long-term project, but with the right program, it can be achieved in just a month. The Certified AI and Machine Learning Expert program by Global Tech Council is designed to be flexible, practical, and achievable within…