Latest Posts

7 AI Tools I Can’t Live Without as a Professional Data Scientist

A professional data scientist shares 7 essential AI tools that have revolutionized his workflow, covering everything from writing and research to coding, data analysis, and local model experimentation.

A Complete Guide to Seaborn

This comprehensive guide details intermediate to advanced Seaborn usage for Python data visualization. It covers setting themes, creating various plot types (relational, categorical, distribution, regression), using grid layouts, visualizing correlations, and fine-tuning plots with Matplotlib hooks for clear, accurate communication.

10 Polars One-Liners for Speeding Up Data Workflows

This article presents 10 concise Polars one-liners to accelerate data manipulation workflows. It covers key operations like lazy loading, filtering, and aggregation, positioning Polars as a high-performance alternative to Pandas.

7 Best Chrome Extensions for Agentic AI

This article showcases 7 agentic AI Chrome extensions, contrasting them with reactive AI. It details tools like Magical, Merlin, Zapier Agents, Recall, BrowserAgent, Taskade AI, and Perplexity AI for automating workflows, enhancing research, and boosting browser productivity.

Building a Gmail Inbox Management Agent in n8n

Learn to build an automated Gmail inbox management agent using n8n. This agent scores incoming emails by sender, content, and category, then routes them to priority-specific actions like labeling, creating tasks, or sending Slack alerts.

Building AI Automations with Google Opal

Google Opal is a new, experimental no-code tool that translates natural language prompts into visual AI workflows. It empowers both technical and non-technical users to build and share custom AI micro-applications using Google's models.

Free AI and Data Courses with 365 Data Science— 100% Unlimited Access until Nov 21

365 Data Science offers free, unlimited access to its entire AI and data science learning platform from Nov 6-21, 2025. This initiative provides courses, hands-on projects, and industry-recognized certifications for aspiring tech professionals.

5 Practical Examples for ChatGPT Agents

This article explores 5 practical examples of ChatGPT Agents moving beyond conversation to real-world action. It covers automating data cleaning, managing AI customer support, streamlining content production, building research assistants, and orchestrating DevOps. These agents integrate with APIs to automate complex workflows, enhancing efficiency across various sectors.

5 Fun Data Science Projects for Absolute Beginners

Learn data science by doing! This post highlights 5 video tutorials for beginners, covering the complete workflow: data cleaning, exploratory analysis, visualization with Plotly, feature engineering, and deploying a model with Streamlit.

The Algorithmic X-Men

This article creatively explains seven essential machine learning algorithms by comparing their strengths and weaknesses to iconic X-Men characters, from Wolverine as a Decision Tree to Jean Grey as a Neural Network.

How I Built a Data Cleaning Pipeline Using One Messy DoorDash Dataset

This article details building a data cleaning pipeline for a messy DoorDash dataset. It covers data exploration, fixing datetime types, imputing missing `store_primary_category` values via a smart `mode()`-based strategy, and dropping remaining NaNs for analysis.

The 5 FREE Must-Read Books for Every AI Engineer

This article highlights five essential, free resources for AI engineers. The recommendations span foundational texts on neural networks, a comprehensive deep learning book, a practical course, a book on agent-based AI, and a paper on ethics.

7 Steps to Mastering Data Storytelling for Business Impact

Master data storytelling with a 7-step guide. This workflow transforms complex analysis into clear, actionable business insights by defining questions, knowing your audience, choosing metrics, and crafting a compelling narrative.

Decoding Agentic AI: The Rise of Autonomous Systems

Agentic AI represents the next AI frontier: autonomous systems capable of planning, acting, and self-improving. Unlike static LLMs, these agents use modular design (planning, memory, tools) and a "observe, plan, act, reflect" cycle for continuous learning and problem-solving.

Data Analytics Automation Scripts with SQL Stored Procedures

Learn to automate data analytics tasks by encapsulating complex SQL queries into reusable stored procedures. This guide shows how to create a procedure in MySQL and call it from a Python script for streamlined workflows.

Why Do Language Models Hallucinate?

Language model hallucinations are not a mysterious flaw but a direct result of training and evaluation methods that reward confident guessing over admitting uncertainty. The issue is rooted in simple classification errors.

5 Useful Python Scripts for Busy Data Engineers

This article provides five practical Python scripts for data engineers to automate common operational tasks: monitoring pipeline health, validating schemas, tracking data lineage, analyzing database performance, and ensuring data quality.

5 Docker Containers for Language Model Development

This article details five Docker container setups (NVIDIA CUDA, PyTorch, Hugging Face, Jupyter, llama.cpp/Ollama) designed to streamline language model development. They offer isolated, reproducible environments to accelerate LLM research, fine-tuning, and inference.

How to Build Production-Ready UI Prototypes in Minutes Using Google Stitch

Google Stitch is a new AI tool that generates production-ready UI prototypes from simple text or image prompts. This guide shows how to quickly create, iterate, and export designs, accelerating app development.

5 Strategic Steps to a Seamless AI Integration

This article provides a five-step strategic roadmap for businesses to successfully integrate AI. It emphasizes starting with a clear purpose, building a strong data foundation, training staff, scaling smartly, and embedding ethics.

5 AI-Assisted Coding Techniques Guaranteed to Save You Time

Enhance coding productivity with 5 AI-assisted techniques: context-rich prompting, dual-AI code & review, automated testing, legacy refactoring, and parallel task execution. AI handles repetitive work, letting developers focus on architecture and creativity.

From Dataset to DataFrame to Deployed: Your First Project with Pandas & Scikit-learn

This article guides beginners through building a machine learning regression model in Python using Pandas and Scikit-learn. It covers loading and cleaning a dataset, handling missing values, creating preprocessing pipelines, training a Random Forest model to predict employee income, evaluating its performance, and saving the model for future deployment.

Mapping the AI Education Surge: Which States and Schools Are Leading the Pack in 2025

A 2025 report reveals a massive surge in US AI degree programs, with a 167% increase in Master's degrees since 2022. The South, led by Texas, now leads the nation, signaling a decentralization of AI education beyond tech hubs.

Automating Web Search Data Collection for AI Models with SerpApi

This sponsored post highlights SerpApi, a tool that automates data collection from search engines. It solves web scraping challenges by providing a simple API that returns structured JSON data for use in AI models and analytics.

How To Set Business Goals You’ll Actually Reach (Sponsored)

What you need is a system to support the formation of goals within a structure that enables turning these broad ambitions into concrete, achievable targets. This article will provide a simple three-step framework to do so.

Unlock Business Value: Build a Data & Analytics Strategy That Delivers

Gartner's guide helps data leaders build business-driven D&A strategies, moving beyond vague "data-driven" goals. It introduces the DASOM framework and actionable steps to align D&A with business objectives, ensuring tangible value delivery.

Processing Large Datasets with Dask and Scikit-learn

Learn to efficiently process large datasets and build ML models using Dask and scikit-learn. This guide covers loading, cleaning, and transforming data with Dask's lazy computation, seamlessly integrating with scikit-learn for scalable workflows.

Exploring Metaclasses in Python: Unleashing the Power of Class Creation

An introduction to Python metaclasses for data scientists. This post explains how metaclasses act as blueprints for classes, controlling their creation process, much like classes are blueprints for objects.

Debunking 5 Myths About Cloud Computing for Small Business (Sponsored)

Top 5 Open Source Video Generation Models

This post highlights the top 5 open-source video generation models—Wan 2.2, HunyuanVideo, Mochi 1, LTX-Video, and CogVideoX-5B—as powerful, privacy-focused alternatives to closed systems like Google's Veo and OpenAI's Sora.

Deploy an AI Analyst in Minutes: Connect Any LLM to Any Data Source with Bag of Words

Learn to deploy an AI analyst in minutes with Bag of Words, an AI data layer that connects any LLM to SQL databases. This guide walks through a simple Docker setup to turn your data into interactive, AI-powered insights.

The Lazy Data Scientist’s Guide to Exploratory Data Analysis

This guide promotes an efficient, or "lazy," approach to Exploratory Data Analysis (EDA) using Python automation tools like ydata-profiling and Sweetviz to handle repetitive tasks, saving time for deeper, domain-specific analysis.

ChatLLM. An Honest Review of Our All-in-One AI Platform

ChatLLM by Abacus.AI is an all-in-one platform offering access to major AI models like GPT, Claude, and Gemini for a low monthly fee. It provides document analysis, coding, and image generation but has some notable drawbacks.

What Does the End of GIL Mean for Python?

Python's Global Interpreter Lock (GIL) is being made optional via PEP 703, enabling true multithreading. This promises major performance boosts for CPU-bound tasks but requires developers to manage new concurrency complexities.

5 Practical Docker Configurations

Enhance Docker efficiency with 5 key configurations: optimize caching with strategic layering, use multi-stage builds for lean & secure images, securely manage environment variables, streamline networking & volumes, and fine-tune resource allocation for predictable performance.

Is ChatGPT Study Mode a Hidden Gem or a Gimmick?

This article explores ChatGPT's Study Mode, a feature designed for personalized learning. It weighs the benefits like interactive quizzing against drawbacks such as potential inaccuracies and over-reliance to determine its true value.

10 Command-Line Tools Every Data Scientist Should Know

This post highlights 10 essential command-line tools for data scientists, updated for 2025. It covers utilities for data retrieval, text processing, parallel execution, and version control to enhance productivity and efficiency.

10 Python One-Liners to Optimize Your Hugging Face Transformers Pipelines

Discover 10 Python one-liners to optimize Hugging Face Transformers pipelines. Enhance performance and efficiency with GPU acceleration, batching, half-precision, faster tokenization, truncation, and ensure reproducibility for robust NLP/LLM workflows.

The Lazy Data Scientist’s Guide to Time Series Forecasting

This guide champions an efficient, 'lazy' approach to time series forecasting. It shows how to use modern Python libraries like Prophet, AutoARIMA, and AutoML platforms to get accurate predictions quickly, avoiding tedious manual tuning.

Debunking 5 myths about cloud computing for small business (Sponsored)

Top 5 Text-to-Speech Open Source Models

This article reviews the top 5 open-source Text-to-Speech (TTS) models: VibeVoice, Orpheus, Kokoro, OpenAudio S1, and XTTS-v2. It highlights their unique features, from multi-speaker podcasts to zero-shot voice cloning.

Building Machine Learning Application with Django

A step-by-step tutorial on building a complete machine learning web application with Django. Learn to train a scikit-learn model, create a user-friendly web interface, and expose a JSON API for programmatic predictions.

Data Cleaning at the Command Line for Beginner Data Scientists

This article introduces beginner data scientists to powerful command-line tools (head, tail, wc, cut, sort, uniq, grep, sed, awk) for efficient data cleaning, transformation, and exploration of CSV files without requiring Python.

7 LinkedIn Tricks to Get Noticed by Recruiters

This article provides seven actionable tricks for professionals, particularly in data science, to optimize their LinkedIn profiles. It emphasizes using targeted keywords, showcasing projects, and strategic engagement to attract recruiters.

Agentic AI Coding with Google Jules

Google Jules is an asynchronous, agentic AI coding system that automates development tasks like bug fixes, updates, and testing. It integrates with GitHub, executes in secure cloud VMs, and provides transparent plans and diffs for review.

Creating a Text to SQL App with OpenAI + FastAPI + SQLite

This guide demonstrates building a Text-to-SQL application using OpenAI, FastAPI, and SQLite. It covers setting up the project, connecting to a database, using OpenAI's API for query generation, and containerizing the app with Docker.

10 Essential Agentic AI Interview Questions for AI Engineers

This guide provides 10 essential agentic AI interview questions for AI engineers, covering core concepts, tool integration, planning, multi-agent systems, and safety. It emphasizes practical experience, design choices, and understanding trade-offs.

How Data Engineering Can Power Manufacturing Industry Transformation

Data engineering is crucial for modern manufacturing, enabling the industry to harness vast data from IIoT and legacy systems. It helps build data pipelines for predictive maintenance, supply chain optimization, and operational efficiency.

5 NotebookLM Tips to Make Your Day a Little Easier

This article offers five practical tips for data scientists to leverage Google's NotebookLM. It covers clustering research, integrating external AI for fact-checking, generating outlines, maintaining dynamic documentation, and refining sources.

How To Get More Done Without Working More Hours (Sponsored)

Stop wasting time on repetitive tasks. Learn how smart business automation can boost your productivity, cut costs, and get you back hours a week.

Collecting Real-Time Data with APIs: A Hands-On Guide Using Python

A hands-on guide to collecting real-time data using APIs in Python. Learn to use the `requests` and `pandas` libraries with practical examples, from a simple user generator to the complex Eurostat statistical data API.

The Benefits of an “Everything” Notebook in NotebookLM

This article details how data scientists can use Google's NotebookLM to create an "everything" notebook. This centralized knowledge base boosts productivity with semantic search, cross-document synthesis, and advanced querying.

How To Use Synthetic Data To Build a Portfolio Project

This guide demonstrates how to create synthetic data using random, rule-based, simulation, and AI methods. It provides a step-by-step walkthrough for building a complete portfolio project, from model training to a Streamlit app.

Top 5 Agentic Coding CLI Tools

This article reviews the top 5 agentic coding CLI tools: Claude Code, OpenCode, Droid, Codex CLI, and Gemini CLI. It shares personal experiences, pros, cons, and installation commands, highlighting tools for daily tasks, customization, debugging, and leveraging LLMs. Node.js is a common prerequisite.

Top 10 Free API Providers for Data Science Projects

This article presents a curated list of 10 free APIs essential for data science projects. It categorizes them for easy access to foundational datasets, web scraping, geospatial information, financial markets, and social media data.

The Complete Guide to Building Data Pipelines That Don’t Break

This guide details a systematic approach to building robust data pipelines, emphasizing software engineering principles. It covers validation, idempotency, schema evolution, backpressure, data quality monitoring, observability, and testing to prevent failures and reduce maintenance.

A Gentle Introduction to TypeScript for Python Programmers

An introductory guide for Python developers learning TypeScript. It compares key concepts like type systems, classes, and functions, highlighting how TypeScript provides robust, compile-time safety that prevents common Python runtime errors.

10 Newsletters for Busy Data Scientists

Discover 10 top free newsletters for busy data scientists to efficiently stay updated on machine learning, AI, statistics, and data engineering. Curated content helps cut through noise, offering practical insights and career advice.

A Gentle Introduction to MCP Servers and Clients

This post introduces the Model Context Protocol (MCP), a standard for AI systems to securely interact with external tools and data. It defines three roles: hosts (apps), clients (AI), and servers (resource wrappers) for reusable integration.

The 5 FREE Must-Read Books for Every LLM Engineer

This article curates a list of 5 free, essential books for LLM engineers. The recommendations cover diverse, crucial topics including foundational theory, NLP, system scaling on TPUs, model interpretability, and cybersecurity risks.

The 5 FREE Must-Read Books for Every Data Scientist

This article curates a list of five essential and free online books for aspiring data scientists. It emphasizes moving beyond just coding to build a deep understanding of statistical theory, algorithms, and practical applications.

Prompt Engineering Templates That Work: 7 Copy-Paste Recipes for LLMs

This article offers 7 practical, copy-paste prompt engineering templates for LLMs across diverse tasks, including job applications, coding, creative writing, and business strategy, emphasizing structured and guided inputs for superior outputs.

Are AI Browsers Any Good? A Day with Perplexity’s Comet and OpenAI’s Atlas

A hands-on review of AI browsers Perplexity Comet and OpenAI Atlas. While excellent for research and summarizing static content, they fail with dynamic web apps and introduce significant privacy and security concerns.

How I Prepared for a Data Science Interview at a Large Tech Company

A product data scientist shares their interview preparation plan for a large tech company, emphasizing skills that differentiate a product role from traditional data science: advanced SQL, applied statistics, and business acumen.

Building Full Stack Apps with Firebase Studio

An introduction to Firebase Studio, Google's cloud-based IDE. It integrates Firebase services and Gemini AI to streamline full-stack app development, enabling rapid prototyping and deployment with zero local setup.

From Excel to Python: 7 Steps Analysts Can Take Today

A 7-step guide for data analysts to transition their skills from Excel to Python. It covers mapping existing knowledge, learning fundamentals with libraries like Pandas, practicing on real data, and integrating Python with Excel.

From Hustle to Structure: How to Build Repeatable Processes in Your Business (Sponsored)

Transitioning from reactive hustle to proactive structure by building simple, repeatable processes. If you are looking for practical ways to get started in the shift from hustle to structure, this article has you covered.

How to Build and Publish a Docker Image to Docker Hub

A step-by-step guide to containerizing a Python Flask app. Learn to write a Dockerfile, build a Docker image, test it locally, and publish it to Docker Hub, making your application portable and easily shareable.

Make.com Automations for Saving Time as a Data Professional

This article introduces Make.com as a no-code visual platform for data professionals to automate repetitive tasks like data collection, cleaning, and reporting. It highlights how Make.com saves time, improves data accuracy, and integrates with AI, empowering professionals to focus on analysis rather than manual grunt work.

How to Write Readable Python Functions Even If You’re a Beginner

This guide helps beginners write readable Python functions. It covers best practices like clear naming for functions and parameters, keeping functions concise, using docstrings, meaningful variable names, avoiding magic numbers, and implementing type hints for better code clarity.

An Introduction to Zapier Automations for Data Scientists

This post introduces Zapier automations for data scientists, explaining how to use no-code workflows to connect apps, automate repetitive tasks like data collection, reporting, and alerts, saving time, reducing errors, and boosting productivity.

Vibe Coding with GLM 4.6 Coding Plan

This article introduces Z.AI's GLM-4.6 coding model and its affordable ~$3/month subscription, the GLM Coding Plan. It provides a step-by-step tutorial on integrating it with OpenCode to build a complete website from a single prompt.

Here’s When You Would Choose Spreadsheets Over SQL

Don't default to SQL for every data task. This post details when spreadsheets are the better choice: for small data, quick tasks, collaboration, visualization, and when working with non-technical teams.

The Psychology of Bad Data Storytelling: Why People Misread Your Data

This post explores 10 psychological reasons why audiences misinterpret data, from cognitive biases to poor visualization. It provides actionable fixes for data storytellers to present information clearly and drive correct decisions.

Getting Started with the Claude Agent SDK

Build programmable AI agents and CLI apps with Claude Agent SDK. This tutorial covers setup and developing "TrendSmith," a multi-tool app for market trend analysis, integrating web search, data fetching, and local storage.

Cloud 101 for Business Owners (Sponsored)

If you've been hearing about "the cloud" for years but still aren't sure what it means for your business, we get it. Let's cut through the noise.

Qwen Code Leverages Qwen3 as a CLI Agentic Programming Tool

Qwen Code is a new agentic CLI programming tool powered by the Qwen3-Coder model. It enhances developer productivity by understanding codebases, suggesting optimizations, and automating tasks directly from the command line.

The Best Local Coding LLMs You Can Run Yourself

This article explores the best local coding LLMs for developers, highlighting options like GLM-4, DeepSeekCoder V2, Qwen3-Coder, Codestral, and Code Llama. It details their features, performance, context windows, and hardware requirements.

Top 7 Python Package Managers

This article explores 7 popular Python package managers: uv, pip, Poetry, Conda, Miniconda, Mamba, and Pixi. It details their features, installation, and ideal use cases, from beginner-friendly Anaconda to fast alternatives like uv and Mamba for data science.

Reinvent Customer Engagement with Dynamics 365: Turn Insights into Action

Enhance customer engagement with Microsoft Dynamics 365. This AI-powered platform unifies data across sales, marketing, and service, turning fragmented customer insights into actionable, personalized experiences.

A 5-Step Guide to Tackling (Almost) Any Data Science Project

This guide outlines a 5-step framework for successful data science projects, prioritizing business alignment, data exploration, simple baselines, and robust feature engineering over premature optimization of complex models.

What Is Cross-Validation? A Plain English Guide with Diagrams

This guide explains cross-validation, a technique for robustly evaluating machine learning models. It details why it's superior to a single train/test split and covers key methods like k-fold, stratified, and time-series CV.

5 Fun AI Agent Projects for Absolute Beginners

Discover five fun, beginner-friendly AI agent projects, from a pure Python calendar assistant to advanced research bots. This guide provides curated video tutorials to help you build agents that can act, reason, and automate tasks.

How I Actually Use Statistics as a Data Scientist

A data scientist shares that most roles require applied statistics for business problems, not deep academic theory. Focus on concepts like A/B testing, ML model interpretation, and descriptive analysis. Learn core concepts for interviews and advanced skills on the job.

The 5 FREE Must-Read Books for Every Machine Learning Engineer

This article lists 5 free, must-read books for Machine Learning Engineers, emphasizing the importance of deep theoretical understanding over just practical application. It covers foundational math, core algorithms, statistical learning, pattern recognition, and building ML systems.

SQL for Data Analysts: Essential Queries for Data Extraction & Transformation

A concise guide for data analysts on 15 essential SQL queries. It covers fundamental commands like SELECT, WHERE, and GROUP BY, to advanced functions like JOINs, CASE, and window functions for effective data extraction and transformation.

Pandas: Advanced GroupBy Techniques for Complex Aggregations

This guide explores advanced Pandas GroupBy techniques beyond simple sums and means. It covers the distinct uses of agg, transform, apply, and filter for complex scenarios like conditional logic, weighted metrics, and time-series analysis.

Staying Ahead of AI in Your Career

To thrive in the age of AI, collaborate with it instead of resisting. This post advises developing adaptive intelligence, integrating AI into your workflow, and strengthening irreplaceable human skills like empathy and strategic thinking.

7 Free Remote MCPs You Must Use As A Developer

This post highlights seven free remote Model Context Protocol (MCP) servers for developers. These tools, including integrations for GitHub, Figma, and Notion, connect AI assistants to essential services to streamline workflows.

Facing The Threat of AIjacking

AIjacking, a new threat exploiting LLMs via prompt injection, allows AI agents to perform unauthorized actions like data exfiltration without human interaction, bypassing traditional security. The article outlines practical defenses and emphasizes a security-first AI approach.

We Benchmarked DuckDB, SQLite, and Pandas on 1M Rows: Here’s What Happened

A performance benchmark of DuckDB, SQLite, and Pandas on a 1M row dataset. The test compared speed and memory usage for common data analysis tasks, revealing DuckDB's consistent high performance and balanced efficiency.

7 Python Libraries Every Analytics Engineer Should Know

This article highlights 7 essential Python libraries for analytics engineers, covering data manipulation (Polars), quality (Great Expectations), transformation (dbt), orchestration (Prefect), and more to streamline workflows.

Top 7 Open Source AI Coding Models You Are Missing Out On

This article introduces 7 top open-source AI coding models for local deployment, offering privacy, security, and cost savings over cloud-based tools. It details each model's strengths, architecture, and benchmarks, providing alternatives for sensitive codebases.

Our favourite Black Friday deal to Learn SQL, AI, Python, and become a certified data analyst!

DataCamp offers a Black Friday deal (Nov 12-Dec 4) with 50% off full platform access, including 600+ courses, career tracks, and certifications. Learn SQL, Python for data analysis, or dive into AI engineering with tracks covering OpenAI, LLMs, and MLOps. Gain job-ready skills and industry certifications.

5 Cutting-Edge Natural Language Processing Trends Shaping 2026

By 2026, NLP will evolve beyond current models, focusing on five key trends: efficient attention mechanisms, autonomous language agents, world models for reasoning, knowledge graphs for context, and on-device NLP for speed and privacy.

The Complete Guide to Using Google AI Studio

A comprehensive guide to Google AI Studio, covering account setup, interface features, and model selection. Learn to prototype with Gemini, generate code and images, and build AI applications directly from the web-based workspace.

Top SQL Patterns from FAANG Data Science Interviews (with Code)

Ace your FAANG data science interviews by mastering the top 5 SQL patterns. This guide covers aggregation, subqueries, window functions, moving averages, and conditional aggregation, complete with practical PostgreSQL examples.

Git for Vibe Coders

This beginner-friendly guide teaches AI "vibe coders" how to integrate Git and GitHub into their workflow to prevent data loss from AI tools like Claude Code. It covers essential commands for version control, saving snapshots, branching, and automatic backups.

5 Useful Python Scripts for Busy Data Analysts

This article outlines five practical Python scripts designed to automate common, time-consuming tasks for data analysts, such as report formatting, data reconciliation, dashboard creation, and scheduled data pulls.

5 Docker Containers for Your AI Infrastructure

This post highlights five essential Docker containers to build a robust AI infrastructure: JupyterLab for experimentation, Airflow for orchestration, MLflow for tracking, Redis for caching, and FastAPI for serving models.

The Best Proxy Providers for Large-Scale Scraping for 2026

This article compares top proxy providers for large-scale web scraping in 2026, including Bright Data, Oxylabs, Infatica, and NetNut. It highlights their features, pricing, and ideal use cases, concluding Bright Data is superior.

10 Useful Python One-Liners for CSV Processing

Discover 10 powerful Python one-liners for common CSV tasks. This guide shows how to sum, group, filter, and analyze CSV data efficiently using built-in modules, perfect for quick data exploration without external libraries like pandas.

5 Fun NLP Projects for Absolute Beginners

This article outlines five hands-on Natural Language Processing (NLP) projects for beginners. It covers tokenization, Named Entity Recognition (NER), sentiment analysis, text generation, and machine translation with video tutorials.

A Gentle Introduction to vLLM for Serving

An introduction to vLLM, an open-source serving engine that optimizes LLM inference. It uses a core innovation called PagedAttention to achieve high throughput, low latency, and efficient memory use for production applications.

Generative AI Hype Check: Can It Really Transform SDLC?

This post explores Generative AI's impact on the Software Development Lifecycle (SDLC), weighing its productivity benefits against limitations like the need for human oversight, security risks, and struggles with complex, novel tasks.

Weights & Biases: A KDnuggets Crash Course

A practical crash course on using Weights & Biases (W&B) for MLOps. Learn to track experiments, version datasets and models with Artifacts, run hyperparameter sweeps, and improve reproducibility in your ML workflows.

Airtable + GPT: Prototyping a Lightweight RAG System with No-Code Tools

This tutorial guides users through prototyping a lightweight RAG system using Airtable for knowledge, OpenAI's GPT models for generation, and Pipedream for no-code orchestration. It details setting up the workflow and offers code and AI-agent methods for building it.

Using NotebookLM to Tackle Tough Questions: Interview Smarter, Not Harder

This guide demonstrates how to use Google's NotebookLM to enhance technical interview preparation. It uses a Meta recommendation system problem to showcase how the AI tool creates summaries, quizzes, and visual aids to deepen understanding.

The Beginner’s Guide to Tracking Token Usage in LLM Apps

This guide explains why tracking token usage in LLM apps is vital for cost and performance. It provides a step-by-step tutorial on using LangSmith with LangChain and Hugging Face to monitor and visualize token consumption.

5 Signs Your Business Is Ready For AI (Sponsored)

How do you know if you're ready to take the AI plunge? Here are five dead giveaways that AI could transform how you work.

Top 7 ChatGPT Alternatives You Can Try For Free

This article explores seven powerful and free alternatives to ChatGPT for tasks like research, coding, and content creation. It highlights the unique features of Microsoft Copilot, Google Gemini, Grok, You.com, and others.

The Hidden Curriculum of Data Science Interviews: What Companies Really Test

Beyond technical tests, data science interviews have a 'hidden curriculum.' This post reveals the non-technical skills companies truly evaluate, such as business translation, handling ambiguity, and understanding trade-offs.

Beginner’s Guide to VibeVoice

This guide introduces VibeVoice, Microsoft's open-source, next-gen Text-to-Speech framework for expressive, multi-speaker audio. Learn to set up VibeVoice-1.5B on Google Colab, download the model, create transcripts, run inference, and troubleshoot common issues. It highlights VibeVoice's quality and open-source benefits.

API Development for Web Apps and Data Products

A practical guide to API development for web apps and data products. Covers essential principles from user-centric design and RESTful practices to robust security, scaling strategies, and the importance of clear documentation.

Python for Data Science (Free 7-Day Mini-Course)

This post outlines a free, 7-day mini-course for beginners learning Python for data science. It covers fundamental skills like data structures, file I/O, string manipulation, and error handling using only core Python.

What Is Big Tech’s Influence on AI Development?

Big Tech's massive investments accelerate AI development, but their dominance over cloud infrastructure and the AI supply chain raises serious concerns about stifling competition, market control, and significant ethical challenges.

10 Useful Python One-Liners for Data Engineering

Explore 10 practical Python one-liners for data engineering using pandas. This guide covers common tasks like parsing JSON, analyzing performance logs, detecting schema changes, monitoring APIs, and optimizing memory usage.

Building Pure Python Web Apps with Reflex

This tutorial introduces Reflex, an open-source library for building scalable, full-stack web applications entirely in Python. It covers installation, core concepts like state management, and guides you through building a to-do list app.

Nano Banana Practical Prompting & Usage Guide

This guide explores Google's "Nano Banana" (Gemini 2.5 Flash) AI image model. Learn its advanced features, like multi-image composition and semantic inpainting, with practical prompting strategies and usage tips.

5 Excel AI Lessons I Learned the Hard Way

This article shares 5 hard-won lessons for building trustworthy machine learning systems in Excel with XLMiner. It covers multi-method outlier detection, setting random seeds, 3-way data partitioning, monitoring overfitting, and implementing data validation.

Beginner’s Guide to Creating Your Own Python Shell with the cmd Module

Learn to build a custom interactive command-line shell in Python using the built-in `cmd` module. This step-by-step guide covers creating commands, parsing arguments with `shlex`, adding a help system, and creating aliases.

What’s on My Bookmarks Bar: Data Science Edition

A data scientist shares 10 essential bookmarks for staying updated and productive. The list covers everything from new research and trending code to unique datasets, quick visualization tools, and job listings.

Beginner’s Guide to Data Analysis with Polars

Learn the fundamentals of data analysis with Polars, a high-performance Python library. This beginner-friendly guide uses a coffee shop dataset to walk you through installation, data creation, manipulation, and analysis.

We Used 3 Feature Selection Techniques: This One Worked Best

This article compares three feature selection techniques—Filter, Wrapper (RFE), and Embedded (Lasso)—using the scikit-learn Diabetes dataset. The experiment concludes that the Embedded method, Lasso, offered the best performance.

Accessing Data Commons with the New Python API Client

This article introduces Data Commons, Google's open-source initiative to organize public data via a knowledge graph. It details using the new Python API client to access datasets, covering API key setup, library installation, and fetching statistical variables and entities using DCIDs, with examples for Pandas DataFrames.

5 Signs Your Business Is a Prime Target for Cyberattacks

This post highlights 5 signs your business is a prime cyberattack target: weak passwords, outdated software, untrained staff, poor backups, and no monitoring. It stresses that SMBs are heavily targeted and prevention is key.

5 Tips for Building Useful Streamlit Dashboards in Minutes

This article provides five practical tips to build more efficient and useful Streamlit dashboards. It covers performance enhancement with caching, improving UX with input batching, state management, displaying KPIs, and extending features.

7 Steps to Build a Simple RAG System from Scratch

A step-by-step guide to building a simple Retrieval-Augmented Generation (RAG) system from scratch. This tutorial walks through data prep, chunking, vector embeddings with FAISS, and answer generation using an open-source LLM.

Why I Quit My 6 Figure Side Hustle for a Full-Time Data Science Job

A data scientist explains their decision to leave a six-figure freelance career for a lower-paying, full-time job. The choice prioritizes long-term career security, paid learning, and building skills less replaceable by AI.

Lux + Pandas: Auto-Visualizations for Lazy Analysts

Lux is a Python library that enhances Pandas to automate exploratory data analysis. It automatically generates insightful visualizations when a DataFrame is displayed, saving analysts time on repetitive manual plotting tasks.

5 Strategic Steps to a Seamless AI Integration

This guide provides a five-step framework for successful AI integration: defining the problem, building a strong data foundation, upskilling employees, starting with small pilots, and embedding ethical AI practices from the start.

3 Unexpected Uses for NotebookLM

Discover 3 unexpected ways to use NotebookLM for advanced workflows. Learn to combine its power with other AI tools for website gap analysis, rigorous source verification, and transforming complex data into presentation-ready insights.

My Honest Review on Abacus AI: ChatLLM, DeepAgent & Enterprise

This review praises Abacus AI for its exceptional value, offering access to 18+ top LLMs for just $10/month. It highlights key features like ChatLLM for teams, the autonomous DeepAgent, and a comprehensive MLOps enterprise platform.

Data Observability in Analytics: Tools, Techniques, and Why It Matters

Discover Data Observability, the process of monitoring data system health. This post breaks down its five pillars (freshness, volume, schema, distribution, lineage), its benefits, lifecycle, and key industry tools to ensure reliable analytics.

Transform Raw Data Into Real Impact

Bay Path University's online Master's in Applied Data Science helps working professionals transform data into real impact. The program offers practical, hands-on learning, including Generative AI expertise, to advance careers.

Beginner’s Guide to Data Extraction with LangExtract and LLMs

A beginner's guide to LangExtract, Google's open-source Python library. It leverages LLMs like Gemini and OpenAI to extract structured information from unstructured text using simple prompts and few-shot examples.