A list of premium posts for academy members containing hands-on tutorials, best practices, career advices and learning paths.
📘 Introduction Generating images with AI has never been easier. Hugging Face’s Diffusers library provides a user-friendly way to create stunning visuals using pre-trained diffusion models like Stable Diffusion. In this guide, we’ll walk through the entire process step by step. 🧠 What are Hugging Face Diffusers? Diffusers are models...
📘 Introduction Automation has become a central pillar of modern digital operations, but most tools either limit flexibility or lock you into rigid, predefined steps. n8n stands out because it bridges the gap between low-code usability and deep technical power. It brings together visual workflow building, full control over data, effortless...
📘 Introduction When working with data spread across multiple CSV files, combining them into one unified dataset can save time and simplify your workflow. In this guide, you’ll learn how to merge multiple CSV files into a single Pandas DataFrame using just a few lines of Python. ✅ Prerequisites Before you...
📘 Introduction Working with structured data is a core part of any data engineering or analytics workflow. DuckDB, often called the SQLite for analytics, makes it incredibly easy to query local data files—including JSON—without requiring a complex setup. In this tutorial, you’ll learn how to load JSON data...
📘 Introduction n8n is a flexible and powerful automation platform that helps you connect apps, orchestrate workflows, and even build AI-driven processes — all without writing code. Installing n8n locally with npm gives you a lightweight, customizable setup that runs directly on your system, making it perfect for development, debugging, and experimenting...
📘 Introduction JSON is one of the most widely used data formats for APIs, configurations, storage, and modern applications. Converting CSV to JSON in Python is incredibly simple using Pandas. In this tutorial, we will walk through the full process: creating a sample CSV file, loading it into a Pandas DataFrame,...
📘 Introduction In this tutorial, you’ll learn how to load data from a Parquet file into a DuckDB database using Python. DuckDB’s native Parquet support makes it fast and efficient to work with columnar data, making it ideal for analytics, ETL pipelines, and Python data projects. You’ll see...
📘 Introduction In modern data workflows, Parquet is a popular columnar storage format for efficient data storage and faster analytics. Converting CSV to Parquet in Python is straightforward using Pandas and PyArrow. In this tutorial, we will walk you through the complete process: from creating a sample CSV file, reading it...
📘 Introduction n8n is a powerful automation platform that gives you the freedom to build workflows, integrate apps, and create AI-powered automations without writing any code. Running n8n locally with Docker Desktop provides a fast, clean, and reliable setup that isolates your environment while keeping your system clutter-free. With Docker Desktop,...
📘 Introduction In this tutorial, you will learn how to insert data from a CSV file into a DuckDB database using Python. DuckDB is a powerful in-process analytical database that makes working with structured data fast, simple, and efficient—perfect for data projects, notebooks, and local analytics. ✅ Prerequisites Before you begin,...
📘 Introduction n8n is a powerful workflow automation platform that lets you connect apps, automate processes, and even build AI agents — all without writing a single line of code. Running n8n locally using Docker Compose gives you a clean, reliable, and easily reproducible environment that’s perfect for development, experimentation, and...
📘 Introduction Choosing the right framework can dramatically shape the experience of building and deploying generative AI applications. Streamlit and Gradio are two of the most popular tools for rapidly creating AI demos, prototypes, and interactive interfaces — but they shine in different scenarios. In this guide, we’ll break down when...
📘 Introduction DuckDB has quickly become a favorite tool among data engineers and analysts because of its speed, simplicity, and ability to run analytical SQL queries directly within Python. Whether you’re prototyping data pipelines, running local analytics, or managing lightweight data storage, knowing how to insert data into DuckDB is...
📘 Introduction Renaming columns is one of the most common transformations you’ll perform when cleaning or standardizing data in PySpark. Whether you’re aligning tables from different systems, preparing data for machine learning, or simply making column names more readable, updating many column names at once can quickly become tedious...
📘 Introduction One of DuckDB’s most useful features is the ability to query CSV files directly—no need to load them into a database first. This tutorial will guide you through running SQL queries on a CSV file using Python. ✅ Prerequisites Before you begin, make sure you have: 🐍☑️ Installed Python...
📘 Introduction If you enjoy working with pandas but wish you could use clean, powerful SQL at any time, then DuckDB is the right tool for you. With DuckDB, you can query your DataFrames instantly without having to set up a database, run a server, or change your workflow. ✅ Prerequisites Before...
📘Introduction In this blog post, we’ll walk through how to install DuckDB, a fast and lightweight analytical database engine designed for modern data workflows. Whether you're working on data analysis, ETL pipelines, or experimenting with in-process SQL queries, DuckDB is incredibly easy to set up and use....
📘 Introduction In many real-world datasets, the same type of information can appear in more than one column. A customer may provide an email address, a phone number, or a backup contact, and different systems may populate different fields. When you want to select the first available non-null value from several...
📘Introduction In this blog post, we’ll explore DuckDB—a lightweight analytics engine that’s transforming the way data professionals and enthusiasts analyze data locally. You’ll learn what it is, why it’s gaining popularity, and how it can make your data workflows faster and simpler. By the end,...
📘Introduction In this hands-on dbt tutorial, you'll learn how to use pre-hooks to automate tasks such as creating backup tables before a model runs. Pre-hooks allow you to execute SQL before your dbt model builds, which is useful for auditing, data quality checks, or preparing the environment. 🎓 Preparing...
📘 Introduction Modern systems produce endless streams of real-time data — from app events and online purchases to sensor readings and transactions. To handle this flow efficiently, applications need a fast, reliable way to move data between services as it happens. That’s where Apache Kafka comes in. Kafka is a distributed...
📘Introduction In this hands-on dbt tutorial, you’ll learn how to configure your sources.yml file to handle multiple environments (DEV and PROD) dynamically using dbt’s powerful target variable. This will ensure that your models always connect to the correct database, based on the environment you are currently working...
📘 Introduction Modern applications generate massive amounts of data — clicks, payments, sensor readings, and more — all happening in real time. To handle this flow efficiently, systems need a reliable way to move data between components instantly. That’s where Apache Kafka comes in. Kafka is a distributed data streaming platform built...
📘 Introduction Real-time data ingestion is a critical part of modern data architectures. Organizations need to process and store continuous streams of information for analytics, monitoring, and machine learning. Databricks, with the combined power of PySpark and Delta Lake, provides an efficient way to build end-to-end streaming pipelines that handle data...
📘Introduction When working with dbt (data build tool), YAML files are the backbone of your project’s configuration. They define how dbt behaves, how your models connect to data sources, and how metadata, documentation, and tests are managed. Understanding these YAML files and knowing where they are located within your...
📘 Introduction When processing massive datasets in PySpark, it’s often necessary to uniquely identify rows or efficiently detect changes across records. Using multiple columns as a composite key can quickly become cumbersome and inefficient — especially during joins or deduplication. A better solution is to generate a single hash value derived...
📘Introduction In this hands-on dbt tutorial, you’ll learn how to switch between development (DEV) and production (PROD) environments using target variables in dbt. You’ll see how to dynamically control where your models are built, and easily run commands against different data warehouses — all without changing a single line...
📘Introduction In this hands-on dbt tutorial, you’ll learn how to configure separate development (DEV) and production (PROD) environments to safely build, test, and deploy your data models. We’ll walk through why environment separation matters and how to configure your profiles.yml so you can switch between environments with...
📘 Introduction If you’re working with modern data stacks and want to transform raw data into clean, analytics-ready tables, then you’ve likely heard of dbt (Data Build Tool). dbt has quickly become the go-to framework for data transformation, modeling, and testing, empowering data teams to treat analytics like software...
📘 Introduction When running Spark jobs, you expect every task to share the workload evenly — but that’s not always the case. Sometimes, a few tasks take far longer than the rest, keeping the entire stage waiting. This imbalance, known as data skew, is one of the most common causes of...
📘 Introduction Every Spark application tells a story — a story of how your code travels from a high-level command in Python or Scala to a fully distributed computation running across dozens or even hundreds of executors. Behind the scenes, Spark organizes this work into jobs, stages, and tasks — the building blocks...
📘Introduction In this dbt tutorial, you’ll learn how to supercharge your dbt models with Jinja, the templating language that brings flexibility, automation, and scalability to your SQL transformations. Understanding Jinja in dbt will unlock a whole new level of productivity — letting you write dynamic, reusable, and DRY (Don’t...
📘Introduction In this hands-on dbt tutorial, you’ll learn how to make your aggregations dynamic and flexible using Jinja loops inside your SQL models. Instead of writing multiple aggregation functions, you’ll see how to dynamically generate aggregation logic — saving time and reducing repetitive SQL code. 🎓 Preparing for dbt Analytics...
📘 Introduction In Apache Spark, performance often hinges on one crucial process — shuffle. Whenever Spark needs to reorganize data across the cluster (for example, during a groupBy, join, or repartition), it triggers a shuffle: a costly exchange of data between executors. Shuffle is what makes distributed computation possible — but it’s...
📘Introduction In this hands-on dbt tutorial, you’ll learn how to make your SQL transformations dynamic and reusable by using Jinja loops inside CASE statements. This approach helps you replace repetitive SQL logic with concise, maintainable code — a valuable skill for any Data Engineer. 🎓 Preparing for dbt Analytics Engineering Certification?...
📘 Introduction Apache Spark is a distributed data processing framework designed for speed and scalability. When you run a Spark job, it doesn’t just run on your laptop — it coordinates multiple machines working together to process massive datasets in parallel. To understand how Spark does this so efficiently, you need...
📘Introduction In this hands-on dbt tutorial, you'll learn how to use Jinja for loops inside your dbt models to make your SQL code more dynamic and automated. Instead of manually repeating similar SQL logic for multiple columns, tables, or conditions — you can use for loops with Jinja to...
📘 Introduction When you run a PySpark job, Spark doesn’t immediately execute each transformation. Instead, it constructs something called a DAG (Directed Acyclic Graph) — a roadmap of all the operations that need to happen. This DAG is the heart of Spark’s execution engine. It tells Spark how your data...
📘 Introduction In this hands-on dbt tutorial, you'll learn how to overwrite project variables at runtime — a powerful feature that lets you dynamically change your dbt model behavior without modifying your code or dbt_project.yml. This is especially useful when you need to run the same transformation logic...
📘 Introduction When working with large datasets in PySpark, joins can easily become performance bottlenecks. This happens because Spark needs to shuffle data across the cluster to match rows between DataFrames — a costly operation when both datasets are big. If one of your DataFrames is small, though, there’s a faster...
📘Introduction In this tutorial, you'll learn how GraphQL and REST differ and why developers choose one over the other. Whether you’re building modern web apps or managing large datasets, understanding these differences is essential for efficient, scalable applications. 🟣 GraphQL GraphQL (Graph Query Language) is a query language...
📘 Introduction In this hands-on dbt tutorial, you'll learn how to use project variables to make your SQL models more dynamic, flexible, and reusable. Instead of hardcoding values directly into your SQL logic, dbt allows you to define variables in your dbt_project.yml file. These variables can be...
📘 Introduction Choosing the right framework can make or break your web app. Streamlit and React are two powerful but very different tools. Streamlit is perfect for quickly building interactive data apps in Python, while React offers unmatched flexibility for large-scale, production-ready web applications. But which one is right for you?...
📘 Introduction Welcome to this hands-on OpenAI Agents tutorial! In this guide, we’ll build a simple but powerful multi-agent system— a coordinated group of small AI agents that work together to handle different tasks. Our system will include one agent for travel suggestions, another for weather updates, and a triage...
📘 Introduction In this hands-on dbt tutorial, you’ll learn how to use Jinja variables inside your dbt models to make your SQL code more dynamic, flexible, and reusable. Instead of hardcoding values directly into your SQL logic, Jinja allows you to define variables that can be adjusted at runtime or...
📘 Introduction Streamlit makes it easy to build interactive apps — and its st.data_editor() widget lets users edit data directly inside your app. But what if a single cell needs multiple selections, like tags, skills, or categories? 🤔 That’s where st.column_config.MultiselectColumn comes in! It allows you to...
📘 Introduction In this hands-on dbt tutorial, you’ll learn step-by-step how to create a singular test to validate custom business rules using SQL. Unlike built-in generic tests (like unique or not_null), singular tests allow you to write fully customizable SQL logic to enforce strict data quality checks. ✅ Prerequisites ☑️ A...
📘 Introduction In this hands-on dbt tutorial, we’ll walk you step-by-step through how to set up data warehouse grants in dbt, ensuring the right users have access to the right layers and models. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts...
📘Introduction In this hands-on dbt tutorial, we’ll walk you step-by-step through how to make your SQL cleaner and more maintainable by using CTEs (Common Table Expressions) instead of deeply nested subqueries. ✅ Prerequisites ☑️ A dbt project set up ☑️ Source data loaded into your data warehouse ☑️ Source configurations defined in sources....
📘Introduction In this hands-on dbt tutorial, we’ll walk step by step through how to apply the Medallion Architecture to a real dataset using dbt. We’ll explore a sample dataset, visualize the dataflow, and move through all layers of the architecture: 1️⃣ 🛬 Landing Layer – Raw data ingestion 2️⃣ 🥉 Bronze...
📘 Introduction The OpenAI Agent Builder is a visual, no-code canvas for creating intelligent workflows powered by AI. It lets you design and connect nodes — modular building blocks that define how your agent processes inputs, performs reasoning, calls external tools, applies safety checks, and produces outputs. Each node has a specific...
📘 Introduction In this hands-on dbt tutorial, we’ll walk you step-by-step through how to create, use, and understand macros — one of dbt’s most powerful features for reusing logic and keeping your SQL clean, modular, and DRY (Don’t Repeat Yourself). By the end, you’ll be able to write...
📘 Introduction Welcome to this hands-on guide to OpenAI Agent Builder — a revolutionary no-code tool that lets you design and deploy multi-agent workflows using a drag-and-drop interface. In this post, we’ll walk you through how to access the Agent Builder and create your first agent workflow step-by-step. 💡 What is OpenAI...
📘 Introduction In the age of data-driven decision making, a well-structured and scalable data architecture is essential. The Medallion Architecture is a proven framework that organizes data into multiple layers of refinement — ensuring clarity, governance, and trust as data flows from raw ingestion to business-ready insights. When combined with Databricks and...
📘 Introduction Streamlit makes it super easy to build interactive data apps in Python — without needing HTML, CSS, or JavaScript. But sometimes, you want your app to look more polished and visually appealing. One simple way to achieve that is by adding a background image. Whether you want to match your...
📘 Introduction Chatbots are becoming smarter and more useful thanks to agent frameworks. Instead of just responding to messages, agents can plan, call tools, and take actions. With the OpenAI Agents SDK, you can build intelligent assistants that do more than just chat—they can search, calculate, and even connect to...
📘 Introduction Chatbots are becoming smarter and more useful thanks to agent frameworks. Instead of just responding to messages, agents can plan, call tools, and take actions. With the OpenAI Agents SDK, you can build intelligent assistants that do more than just chat—they can search, calculate, and even connect to...
📘 Introduction Streamlit makes it super easy to build interactive apps in Python. But as your app grows — loading datasets, running expensive computations, or calling APIs — you might notice it slows down. The good news: Streamlit has a built-in caching system that stores results of expensive operations and reuses them instead...
📘 Introduction Artificial intelligence (AI) has rapidly evolved, and one of its most impactful applications lies in natural language processing (NLP). From search engines to conversational assistants, AI models power many of the tools we use daily. However, not all AI models are created for the same purpose. Two important categories—...
📘 Introduction Welcome to this hands-on LangChain + LangGraph tutorial! In this guide, we’ll build an AI agent with tool-calling capabilities using LangChain, LangGraph, and OpenAI models. Instead of just answering questions, our agent will be able to invoke a Python function when needed. We’ll demonstrate this with a simple...
📘 Introduction Welcome to this hands-on Docusaurus deployment tutorial! In this guide, we’ll walk you step-by-step through deploying your Docusaurus site to GitHub Pages — a simple and free hosting solution for websites. Perfect for open-source projects, documentation sites, or personal projects that you want to share with the world. 💡 What...
📘 Introduction Welcome to this hands-on Docusaurus tutorial! In this guide, we’ll walk you step-by-step through creating your first interactive documentation site using Docusaurus — perfect for developers, startups, or teams who want to provide clean, user-friendly, and dynamic documentation. 💡 What is Docusaurus? Docusaurus is a static site generator built by...
📘 Introduction Welcome to this hands-on LangChain + LangGraph tutorial! In this guide, we’ll walk you step-by-step through creating your first AI agent using LangChain, LangGraph, and OpenAI models — perfect for beginners who want to build intelligent, autonomous assistants with flexible workflows. 💡 What are LangChain and LangGraph? * LangChain is a powerful...
📘 Introduction FastAPI is a powerful Python framework for building APIs that is both fast and modern. But sometimes you want more than just an API—you also want a user-friendly interface. Instead of running React and FastAPI on two separate servers, you can bundle your React frontend inside FastAPI and...
📘 Introduction Streamlit makes it easy to turn Python scripts into interactive web apps — no front-end coding needed. But what if you want to adjust the look and feel? Maybe you want a dark theme, different fonts, or brand colors. The good news: Streamlit has a built-in theme system that lets...
📘 Introduction Welcome to this hands-on tutorial! In this guide, we’ll walk step-by-step through using structured output with the OpenAI Agents SDK — perfect if you want your AI agent responses returned as clean, machine-readable JSON instead of free-form text. 💡 What is Structured Output? Normally, LLM models return natural language text,...
📘 Introduction Welcome to this hands-on tutorial! In this guide, we’ll walk you step-by-step through using structured output with the OpenAI Python SDK — perfect if you want your AI responses returned as clean JSON instead of free-form text. 💡 What is Structured Output? Normally, LLM models return natural language text, which...
📘 Introduction Welcome back to another hands-on OpenAI tutorial! 🚀 In this guide, we’ll show you step-by-step how to add MCP Servers to your AI Agent using the OpenAI Agents SDK. By the end of this tutorial, you’ll know how to extend your agent’s abilities by connecting it to...
📘 Introduction Welcome back to another hands-on OpenAI tutorial! 🚀 In this guide, we’ll show you step-by-step how to add MCP Servers to your LLM using the OpenAI Python SDK. By the end of this tutorial, you’ll know how to extend your model’s abilities by connecting it to external...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we’ll walk you step by step through deploying and testing your first FastMCP server on FastMCP Cloud. Deploying is a crucial step because it makes your FastMCP server accessible, usable, and ready for real-world applications. ✅ Prerequisites Before you begin,...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we'll walk you step-by-step through getting started with FastMCP Cloud. You’ll learn how to sign in, create a workspace, and connect your GitHub account to it. ✅ Prerequisites Before you begin, make sure you have the following: 🐍☑️ Installed...
📘 Introduction Chatbots are no longer just futuristic concepts—they’re now powering customer service, virtual assistants, and productivity tools everywhere. With the OpenAI Python SDK, you can build a powerful conversational model in just a few lines of code. And when paired with Gradio, you get a clean, interactive web...
📘 Introduction In this hands-on dbt tutorial, we’ll walk you step-by-step through how to connect dashboards and reports to your dbt DAG using exposures. This makes your data lineage more transparent, keeps stakeholders aligned, and ensures you know exactly how data assets are being consumed. 📌 This is a must-know topic...
📘Introduction In this guide, we’ll walk through the basics of JSON-RPC, a lightweight protocol for structured communication between systems. It’s widely used in APIs, blockchain, and even newer standards like the Model Context Protocol (MCP). 💡 What is JSON-RPC? JSON-RPC is a remote procedure call (RPC) protocol encoded in...
📘 Introduction Chatbots are no longer just futuristic concepts—they’re now powering customer service, virtual assistants, and productivity tools everywhere. With the OpenAI Python SDK, you can build a powerful conversational model in just a few lines of code. And when paired with Streamlit, you get a clean, interactive web...
📘 Introduction Welcome back to another hands-on OpenAI Agents tutorial! 🚀 In this guide, we’ll show you step-by-step how to add Function Tools to your AI Agent using the OpenAI Agents SDK. By the end of this tutorial, you’ll know how to extend your agent’s abilities by equipping it...
📘 Introduction In this hands-on tutorial, we’ll walk step-by-step through scheduling dbt models with Dagster. By integrating Dagster, you can easily orchestrate your dbt workflows and automating model runs. ✅ Prerequisites 🐍☑️ Installed Python 📦☑️Installed Pip 🌐☑️ Created a virtual environment (venv) 🗂️☑️ A dbt project set up 🧪☑️ Existing dbt models defined in your...
📘 Introduction In this hands-on tutorial, we’ll walk you step-by-step through running dbt models directly from the Dagster UI. By integrating dbt with Dagster, you gain an easy way to orchestrate, run, and monitor your models — all from a clean web interface. ✅ Prerequisites 🐍☑️ Installed Python 📦☑️Installed Pip 🌐☑️ Created a virtual...
📘 Introduction n this hands-on tutorial, we’ll walk you step-by-step through the Dagster UI and show you where to find your dbt models, along with important details such as column descriptions, SQL code, and data lineage. ✅ Prerequisites 🐍☑️ Installed Python 📦☑️Installed Pip 🌐☑️ Created a virtual environment (venv) 🗂️☑️ A dbt project set...
📘 Introduction In this hands-on tutorial, we’ll walk you step-by-step through adding your dbt models as assets to your Dagster projects. Once done, your dbt models will appear in the Dagster UI, making it easy to orchestrate, run, and monitor them. ✅ Prerequisites 🐍☑️ Installed Python 📦☑️Installed Pip 🌐☑️ Created a virtual environment...
📘 Introduction In this hands-on tutorial, we’ll walk you step-by-step through how to run Dagster with your dbt project, so you can orchestrate, monitor, and manage your data pipelines in the Dagster UI. ✅ Prerequisites 🐍☑️ Installed Python 📦☑️Installed Pip 🌐☑️ Created a virtual environment (venv) 🗂️☑️ A dbt project set up 🧪☑️ Existing dbt...
📘 Introduction In this hands-on dbt tutorial, we’ll walk you step-by-step through how to use the dbt retry command to efficiently re-run only failed models after a broken dbt run. Instead of re-executing your entire DAG, you can save time and resources by retrying only what’s necessary. 📌 This is...
📘 Introduction In this hands-on tutorial, we’ll walk you step-by-step through how to orchestrate your dbt workflows using Dagster. Combining Dagster’s robust orchestration capabilities with dbt’s transformation power allows you to build reliable, maintainable, and observable data pipelines. ✅ Prerequisites 🐍☑️ Installed Python 📦☑️Installed Pip 🌐☑️ Created a virtual environment (venv)...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we'll walk you step-by-step through creating a FastMCP Client to interact with a FastMCP Server. By the end, you’ll understand how to connect a client, call server tools, and handle responses asynchronously. ✅ Prerequisites Before you begin, make...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we'll walk you step-by-step through FastMCP's core components and how they interoperate to build powerful MCP servers. By the end, you’ll understand what each component does and how to use them effectively in a Python...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we’ll walk you step-by-step through configuring the transport method for your FastMCP server. By the end, you’ll understand the different transport mechanisms available and how to use them in the run() statement. ✅ Prerequisites Before you begin, make sure...
📘Introduction Welcome to this MCP tutorial! In this guide, we’ll walk step-by-step through the Transport Layer in Model Context Protocol (MCP) architecture. By the end, you’ll understand how the transport layer facilitates efficient and reliable communication between clients and servers. 💡What is the Transport Layer? In the Model...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we’ll walk step-by-step through how to run a FastMCP Server. By the end, you’ll have a fully working server with a custom tool that AI clients can call and interact with. ✅ Prerequisites Before you begin, make sure you...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we’ll walk step-by-step through how to add a tool to your FastMCP Server. By the end, you’ll have a working server with a custom tool that can be called by AI clients. ✅ Prerequisites Before you begin, make sure...
📘 Introduction Welcome to this hands-on OpenAI Agents tutorial! In this guide, we’ll walk you step-by-step through creating your first AI agent using the OpenAI Agents SDK — perfect for beginners who want to build intelligent, autonomous assistants quickly. 💡 What is the OpenAI Agents SDK? The OpenAI Agents SDK is a...
📘 Introduction Welcome to this hands-on OpenAI GPT tutorial! In this guide, we’ll walk you step-by-step through sending your first prompt to a GPT model using the OpenAI Python SDK — perfect for beginners who want to start building AI-powered applications fast. 💡 What is the OpenAI Python SDK? The OpenAI Python...
📘Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we’ll walk you step-by-step through creating your first FastMCP server from scratch — perfect for beginners who want to jump into MCP quickly. ✅ Prerequisites Before you begin, make sure you have the following: 🐍☑️ Installed Python 📦☑️ Installed Pip 🌐☑️ Created and activated...
📘 Introduction In this hands-on dbt tutorial, we’ll walk you step-by-step through generating and serving interactive documentation for your dbt project. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts you one step closer to passing the exam and leveling up your...
📘 Introduction Welcome to this hands-on FastMCP tutorial! In this guide, we’ll take you step-by-step through setting up and using FastMCP to accelerate your AI projects with ease and efficiency. ✅ Prerequisites Before you begin, make sure you have the following: 🐍☑️ Installed Python 📦☑️ Installed Pip 🌐☑️ Created and activated a virtual environment...
📘 Introduction In this hands-on dbt tutorial, we'll walk you through why data contracts are critical for your dbt models — and how to add them to your dbt models step by step. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts...
📘 Introduction In the rapidly evolving world of artificial intelligence, interoperability is emerging as a critical challenge. With multiple agents, tools, memory systems, and models working in tandem, the need for a universal “plug-and-play” protocol is greater than ever. Enter the Model Context Protocol (MCP) — a new standard designed to unify...
📘 Introduction Data is only as useful as your ability to explore and understand it. But building an interface to analyze and visualize your DataFrame often feels like a full-blown front-end project. That’s where Streamlit saves the day. In this tutorial, you’ll learn how to build a data app...
📘 Introduction In this hands-on dbt tutorial, we'll walk you through how to add and run generic data tests in dbt using YAML configuration. These built-in tests help ensure your data quality and integrity, without writing any custom SQL. 📌 This is a must-know topic for the dbt Analytics Engineering...
📘 Introduction In this hands-on dbt tutorial, we'll walk you through how to use Common Table Expressions (CTEs) effectively in dbt models - an essential concept for modular, readable, and testable SQL. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts...
📘Introduction In this hands-on dbt tutorial, we'll walk you through how to describe and document your data models using schema.yml in dbt. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts you one step closer to passing the exam...