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60 Python Interview Questions For Data Analyst

Analytics Vidhya

Python powers most data analytics workflows thanks to its readability, versatility, and rich ecosystem of libraries like Pandas, NumPy, Matplotlib, SciPy, and scikit-learn. Employers frequently assess candidates on their proficiency with Python’s core constructs, data manipulation, visualization, and algorithmic problem-solving.

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AI Agents in Analytics Workflows: Too Early or Already Behind?

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter AI Agents in Analytics Workflows: Too Early or Already Behind? And, voila!

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10 GitHub Awesome Lists for Data Science

KDnuggets

In this article, we will review some of the most popular and impressive lists for data science. We will explore collections of tools, resources, tutorials, guides, and learning paths, all designed to help you maximize your learning journey in data science. People trust the “awesome” brand.

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Serve Machine Learning Models via REST APIs in Under 10 Minutes

KDnuggets

For that, you need to serve it — expose it through a web API so that other programs (or humans) can send data and get predictions back. You can also refer to my article : Step-by-Step Guide to Deploying Machine Learning Models with Docker. That’s where REST APIs come in. What we’ve built is more than just a toy example.

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How Data Analytics Improves Lead Management and Sales Results

Smart Data Collective

Reading: How Data Analytics Improves Lead Management and Sales Results Share Notification Font Resizer Aa Font Resizer Aa Search About Help Privacy Follow US © 2008-23 SmartData Collective. Accept X By using this site, you agree to the Privacy Policy and Terms of Use. All Rights Reserved. All Rights Reserved. Followers Like 33.7k

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7 Python Statistics Tools That Data Scientists Actually Use in 2025 - KDnuggets

KDnuggets

In this article, we will explore 7 essential Python tools that data scientists are actually using in 2025. These tools are transforming the way analytical reports are created, statistical problems are solved, research papers are written, and advanced data analyses are performed. import statistics as stats 2.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

To succeed in todays landscape, every company small, mid-sized or large must embrace a data-centric mindset. This article proposes a methodology for organizations to implement a modern data management function that can be tailored to meet their unique needs.