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10 GitHub Awesome Lists for Data Science

KDnuggets

After Kaggle, this is one of the best sources for free datasets to download and enhance your data science portfolio. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. It includes tutorials, courses, books, and project ideas for all levels.

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How to Combine Streamlit, Pandas, and Plotly for Interactive Data Apps

KDnuggets

The free tier supports multiple apps and handles reasonable traffic loads, making it perfect for sharing dashboards with colleagues or showcasing your work in a portfolio. He bridges the gap between emerging AI technologies and practical implementation for working professionals.

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10 GitHub Repositories for Mastering Agents and MCPs

KDnuggets

Both of these technologies are dominating the AI space, and companies are using them to automate repetitive tasks and reduce workforce, as agentic AI can outperform junior-level employees in certain cases. After learning the basics, you can get inspiration from these projects and start building your portfolio.

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Mosaic AI Announcements at Data + AI Summit 2025

databricks

AI Functions are now up to 3x faster and 4x lower cost than other vendors on large-scale workloads, enabling you to process large-scale data transformations with unprecedented speed. This unified entry point for all your AI services provides centralized governance, usage logging, and control across your entire AI application portfolio.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

Join Donna Laquidara-Carr in this new webinar as she shares the exciting findings of several recent studies that reveal how portfolio owners, construction managers, and contractors are using data to manage risk, create better projects, and help their businesses gain a strategic edge!

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A Beginner’s Guide to Learning PySpark for Big Data Processing

ProjectPro

One of the most in-demand technical skills these days is analyzing large data sets, and Apache Spark and Python are two of the most widely used technologies to do this. What if you could use both these technologies together? PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency.

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Top 10 Data Engineering Tools You Must Learn in 2025

ProjectPro

Data engineers manage that massive amount of data using various data engineering tools, frameworks, and technologies. Data ingestion systems such as Kafka , for example, offer a seamless and quick data ingestion process while also allowing data engineers to locate appropriate data sources, analyze them, and ingest data for further processing.