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The question “Will AI replace data scientists?” has become one of the hottest discussions in today’s tech ecosystem. As artificial intelligence (AI) continues to advance rapidly, automation, predictive analytics, and generative models are revolutionising how organisations manage and interpret data. But does this progress mean AI tools will completely take over the role of data scientists — or will they act as powerful allies that amplify human expertise?

Pomelli is the latest AI-powered marketing assistant developed by Google Labs and DeepMind, built to redefine how businesses plan and create their marketing campaigns. Introduced in October 2025, Pomelli allows brands to produce on-brand, professional-quality marketing materials in just minutes—without needing large design teams or agencies.

Digital marketing isn’t just about running ads or creating social media posts. It’s a structured process designed to connect brands with the right audience at the right time. Understanding the 4 stages of digital marketing helps businesses design campaigns that move customers smoothly from awareness to loyalty. Whether you’re a student learning digital marketing or a professional building an online strategy, mastering these four stages is key to long-term success.

In today’s information-driven world, data science courses have emerged as one of the most in-demand career fields. Every enterprise—from startups to global corporations—relies on data to make smarter decisions and improve efficiency. As the sphere continues to evolve, more students and professionals are looking for first-class education to become skilled information scientists.

Artificial Intelligence (AI) is no longer just a trending term—it’s the backbone of today’s digital transformation. From personalised recommendations on Netflix to chatbots that handle customer support, AI powers the technology that drives modern life. In 2025, the demand for AI talent has reached a record high, and professionals across industries are upskilling to keep pace. But one critical question remains: Which is the most popular course for AI in 2025?

The 70-20-10 Rule in digital marketing is a strategic framework designed to help marketers allocate their time, budget, and efforts efficiently across different kinds of marketing activities. This rule helps balance stability with innovation, ensuring marketers focus on proven strategies while still testing new ideas and exploring fresh opportunities for growth. It has been adopted by major brands like Google and Coca-Cola as a practical approach to managing marketing investments.

The discussion around Data Analytics vs Data Science continues to grow as technology transforms the way businesses utilise information. Both fields are essential for turning raw data into insights, but they differ greatly in purpose, skills, and outcomes. Understanding these differences can help students and professionals make smarter career choices in today’s data-driven world.

Artificial Intelligence (AI) is transforming how brands interact, automate tasks, and enhance customer experiences. But one question keeps emerging — AI Agent vs AI Chatbot, what’s the real difference? While both tools rely on AI-powered communication, their roles, intelligence level, and capabilities vary greatly. This blog explores how AI agents are redefining automation and why chatbots remain vital for digital engagement.

This blog post explains the fundamental differences between Data Science and Artificial Intelligence, using relatable examples to clarify their roles and applications. Data Science focuses on analyzing historical data to derive insights, while Artificial Intelligence utilizes those insights to make autonomous decisions and perform tasks. Readers will gain a clear understanding of both fields and their interconnections.

The rise of AI-powered platforms has created a debate that every tech student and professional needs to understand: Will data science survive this automation wave? With AI tools becoming more sophisticated, the boundaries between artificial intelligence, automation, and analytics are blurring. But the real story isn’t about replacement — it’s about evolution. AI will transform how data science is practised, not eliminate it.