# course Published articles for course. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Udacity Android Basics Course Alumni Experience DevFeed: [Udacity Android Basics Course Alumni Experience]() Original publisher: [Read original article]() Author: dustin@dustn.dev (Dustin Summers) Published: 2026-09-17T04:13:15.404035Z Content type: article Language: en Sources: [Dustin Summers]() Topics: [Android]() Tags: [android](), [course](), [experience]() ### AI overview The author describes providing input on life after completing Udacity's Android Basics course and on their experience working in Android. ### Source excerpt As an alumni of the Udacity Android Basics course, they reached out for my input in life after the course and my experience working in Android. ## Quiz: Python Debugging With Pdb DevFeed: [Quiz: Python Debugging With Pdb]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-12T12:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Python](), [debugging](), [debug]() Tags: [bugs](), [course](), [debugger](), [debugging](), [how-to](), [learn](), [python](), [resources](), [tool](), [tutorial]() ### AI overview An interactive 10-question quiz that tests practical knowledge of Python's built-in pdb debugger, including inspecting variables, stepping through code, using conditional breakpoints, watching expressions, and interpreting stack traces. ### Source excerpt Practice using pdb, Python's built-in debugger. Check variables, step through code, set conditional breakpoints, and read a stack trace. ## Quiz: Starting With Python IDLE DevFeed: [Quiz: Starting With Python IDLE]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-09T12:00:00Z Content type: article Language: en Sources: [Real Python]() Topics: [Python](), [debug](), [Code]() Tags: [code](), [course](), [debug](), [debugger](), [development](), [learn](), [python](), [workflow]() ### AI overview An eight-question interactive quiz that tests understanding of Python IDLE, including its REPL shell, editing and running Python files, built-in debugging, and customization options. ### Source excerpt Test your grasp of Python IDLE. Run code in the shell, edit and run files, debug with breakpoints, and make the editor look the way you like. ## New Post: A Crash Course in Predicate Logic DevFeed: [New Post: A Crash Course in Predicate Logic]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2026-09-01T18:30:01Z Content type: release Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [Math and Logic]() Tags: [blog](), [course](), [crash](), [free]() ### AI overview The author announces the release of a free second chapter from Logic for Programmers, titled "A Crash Course in Logic," on their blog. The chapter focuses on predicate logic. ### Source excerpt Logic for Programmers has now been out for a month! To celebrate, I'm releasing the entire second chapter, "A Crash Course in Logic", for free on my blog. Read it here! ## The Python print() Function: Go Beyond the Basics DevFeed: [The Python print() Function: Go Beyond the Basics]() Original publisher: [Read original article]() Author: Real Python Published: 2026-08-25T14:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Python](), [coding](), [Terminal](), [User Interfaces]() Tags: [coding](), [course](), [deep-dive](), [learning](), [python](), [q-a](), [resources](), [tutorial](), [video]() ### AI overview A course on Python's print() function that covers lesser-known features, common mistakes, newlines, character encodings, buffering, file output, unit-test mocking, and terminal user interfaces. ### Source excerpt Learn about Python's print() function, discover its lesser-known features, avoid common mistakes, and know when to use a better alternative. ## Announcing new course: AI in Platform Engineering DevFeed: [Announcing new course: AI in Platform Engineering]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [AI Platform](), [agentic-coding](), [GPU](), [observability](), [Inference]() Tags: [agentic-coding](), [ai](), [course](), [gpu](), [inference](), [observability](), [platform-engineering](), [sdlc]() ### AI overview This article announces a course on AI in Platform Engineering. It covers AI-native platforms, platforms for AI workloads, agentic coding, conversational observability, AI reference architectures, compliance, model provenance, and the operational requirements of training and inference at scale. ### Source excerpt Supercharge your SDLC and design the next generation of infrastructure for AI/ML workloads. Learn AI-native platform engineering from Mallory Haigh ## Announcing Jetpack Compose Mechanisms: The Book and Course on How Compose Actually Works DevFeed: [Announcing Jetpack Compose Mechanisms: The Book and Course on How Compose Actually Works]() Original publisher: [Read original article]() Author: Jaewoong Eum Published: 2026-06-21T01:38:50Z Content type: article Language: en Sources: [Stories by Jaewoong Eum on Medium]() Topics: [Compose](), [Jetpack Compose](), [Compiler](), [.env]() Tags: [android](), [android-compose](), [article](), [compiler](), [compose](), [compose-ui](), [course](), [developer](), [jetpack-compose](), [kotlin]() ### AI overview This developer article explains how Jetpack Compose works beneath the @Composable function. It examines compiler-generated function signatures, restart groups and skip checks, and how remember stores values by position in the runtime slot table. It also introduces a book and companion course covering these mechanisms. ### Source excerpt You hit a recomposition that made no sense. You opened the function, read it twice, and still could not see why it ran again. Maybe you added a remember, shuffled a parameter, and it went away, and you never learned why. Every Compose developer has lived some version of that moment. This post is about the question you quietly moved past: what is actually happening under that @Composable function? In this article, you'll look at three of those puzzles up close, the function that is not the function you wrote, a value that survives by position, and a screen that looks clean while it burns frames. Then you'll see what the book built to answer them covers across its four parts, and how the companion course turns that reading into practice. The gap between using and understanding Most developers know how to use Compose. Far fewer know what runs underneath a @Composable function, and that gap stays invisible until the day a screen recomposes more than it should, a type refuses to skip, or a list drops frames during a scroll. At that point the usual advice runs out, and you are left guessing at a system you cannot see. Here is the kind of thing worth being able to see. You write this: https://medium.com/media/24487ffb0b09b137a227ad928968b886/href The compiler rewrites the signature to fun Greeting(name: String, $composer: Composer?, $changed: Int), wraps the body in a restart group, and adds a skip check that can bypass the entire function when name has not changed since the last composition. Every part of that rewrite has a reason. Once you can read the output, recomposition stops being something that happens to you and becomes something you can trace. Where does a remembered value actually go? You call remember { mutableStateOf(0) } dozens of times a day and trust that the value comes back. But where does it actually go? Not into a variable, not into a map, not into a field on your composable. https://medium.com/media/c6aa8065dea93696c4a4bb2e7bbb27ee/href Because remembe ## LFS148: Getting Started with OpenTelemetry DevFeed: [LFS148: Getting Started with OpenTelemetry]() Original publisher: [Read original article]() Published: 2025-11-28T23:00:00Z Content type: opinion Language: en Sources: [Domenico Luciani]() Topics: [OpenTelemetry](), [observability](), [linux foundation](), [Java](), [Python]() Tags: [course](), [foundation](), [getting-started](), [java](), [observability](), [opentelemetry](), [opinion](), [python]() ### AI overview The author reviews the Linux Foundation's LFS148 course, describing it as an introductory OpenTelemetry course with an overview of OpenTelemetry internals and hands-on examples integrating it with Java and Python applications. ### Source excerpt Want to dive-in into OpenTelemetry? This course is for you ## Helping 1,000 small businesses build with AI DevFeed: [Helping 1,000 small businesses build with AI]() Original publisher: [Read original article]() Published: 2025-11-20T06:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [OpenAI Academy](), [AI Strategy]() Tags: [ai](), [ai-adoption](), [communication](), [company](), [course](), [customer](), [marketing](), [openai](), [productivity](), [skills](), [small-business](), [use-cases]() ### AI overview OpenAI Academy is partnering with DoorDash, SCORE, and local business support organizations to host the Small Business AI Jam. The nationwide workshop will give more than 1,000 small business owners hands-on training and help them build AI tools for marketing, customer communication, and everyday business tasks. ### Source excerpt OpenAI is partnering with DoorDash, SCORE, and local organizations to help 1,000 small businesses build with AI. The Small Business AI Jam gives Main Street business owners hands-on tools and training to compete and grow. ## The 2025 AI + Data Engineering Roadmap DevFeed: [The 2025 AI + Data Engineering Roadmap]() Original publisher: [Read original article]() Author: Zach Wilson Published: 2025-10-17T22:35:45Z Content type: tutorial Language: en Sources: [DataExpert.io Newsletter]() Topics: [data-engineering](), [Python](), [SQL](), [Artificial Intelligence](), [airflow](), [BigQuery](), [Orchestration](), [Apache Spark](), [data-modeling](), [Data Quality](), [Embeddings](), [Retrieval Augmented Generation (RAG)]() Tags: [2025](), [ai](), [airflow](), [bigquery](), [count](), [course](), [data-engineering](), [data-modeling](), [data-quality](), [embeddings](), [engineering](), [framer](), [newsletter](), [orchestration](), [python](), [rag](), [real-time](), [right-join](), [spark](), [sql]() ### AI overview A 2025 roadmap for entering data engineering, covering foundational SQL and Python skills, distributed computing, orchestration, data modeling, data quality, AI and data integrations, portfolio projects, and personal branding. ### Source excerpt Getting a data engineering job is complicated. ## Affiliate program launched for the Jetpack Compose Internals course DevFeed: [Affiliate program launched for the Jetpack Compose Internals course]() Original publisher: [Read original article]() Author: Jorge Castillo Published: 2025-09-06T16:13:43Z Content type: opinion Language: en Sources: [Effective Android]() Topics: [Compose](), [Jetpack Compose](), [Android]() Tags: [android](), [compose](), [course](), [jetpack-compose](), [money]() ### AI overview The author announces an affiliate program for the Jetpack Compose Internals course. Participants can share the course and earn up to 20% of each sale, with enrollment currently limited and handled on a first-come, first-served basis. ### Source excerpt Become an affiliate of Jetpack Compose internals. Help me + help others to learn + make some money in the process 🔥 ## Purchasing Power Parity and two-installment payments enabled for the Jetpack Compose internals course DevFeed: [Purchasing Power Parity and two-installment payments enabled for the Jetpack Compose internals course]() Original publisher: [Read original article]() Author: Jorge Castillo Published: 2025-09-04T19:01:29Z Content type: release Language: en Sources: [Effective Android]() Topics: [Compose]() Tags: [compose](), [course]() ### AI overview The author announces that purchasing power parity pricing and an option to pay in two installments have been enabled for the Jetpack Compose internals course. ### Source excerpt Save money if you are physically located in one of the required countries 🫰 also enabled the option to pay in 2 installments 🚀 ## Hands-On MLOps Course Using Databricks Free Edition DevFeed: [Hands-On MLOps Course Using Databricks Free Edition]() Original publisher: [Read original article]() Author: Maria Vechtomova Published: 2025-08-29T13:57:23Z Content type: tutorial Language: en Sources: [MarvelousMLOps]() Topics: [MLOps](), [databricks](), [GitHub Actions](), [GitHub](), [Monitoring]() Tags: [course](), [databricks](), [github-actions](), [mlops]() ### AI overview An overview of a hands-on MLOps course using Databricks Free Edition. It covers moving machine learning prototypes toward production pipelines, including automated deployment with Databricks Asset Bundles and GitHub Actions, plus monitoring with drift detection. ### Source excerpt A full overview of the course ## Introduction to ML monitoring DevFeed: [Introduction to ML monitoring]() Original publisher: [Read original article]() Author: Başak Tuğçe Eskili Published: 2025-08-05T21:56:29Z Content type: tutorial Language: en Sources: [MarvelousMLOps]() Topics: [databricks](), [MLOps](), [Monitoring](), [data]() Tags: [article](), [course](), [data](), [databricks](), [errors](), [introduction](), [latency](), [ml](), [mlops](), [model](), [monitoring](), [performance](), [predictions](), [production](), [workflows]() ### AI overview An introductory lecture in the MLOps with Databricks course explains why machine learning systems require monitoring beyond system health, errors, latency, KPIs, and infrastructure costs. It introduces data drift and concept drift as causes of model performance degradation, even when code and infrastructure remain unchanged. ### Source excerpt Lecture 9 of MLOps with Databricks course ## Introduction to MLOps DevFeed: [Introduction to MLOps]() Original publisher: [Read original article]() Author: Maria Vechtomova Published: 2025-07-28T17:19:47Z Content type: tutorial Language: en Sources: [MarvelousMLOps]() Topics: [MLOps](), [databricks](), [Monitoring](), [Deployment](), [Testing]() Tags: [audit-trail](), [course](), [databricks](), [deployment](), [introduction](), [mlops](), [monitoring](), [production](), [reproducibility](), [testing]() ### AI overview Lecture 1 of a hands-on MLOps with Databricks course explains what production means for machine-learning workflows. It uses a demand-forecasting example to show why scheduled notebooks may lack testing, monitoring, error handling, version control, deployment processes, rollback, and audit trails, and introduces MLOps principles for improving reliability and control. ### Source excerpt Lecture 1 of MLOps with Databricks course ## New Chainguard Academy Course: Getting Started with Chainguard's Dockerfile Converter DevFeed: [New Chainguard Academy Course: Getting Started with Chainguard's Dockerfile Converter]() Original publisher: [Read original article]() Published: 2025-07-25T00:00:00Z Content type: release Language: en Sources: [Chainguard: Unchained]() Topics: [dockerfile converter](), [Dockerfile](), [Containers](), [chainguard containers](), [Command-line interface](), [MCP Server]() Tags: [chainguard](), [chainguard-academy](), [chainguard-containers](), [chainguard-images](), [command-line](), [containers](), [course](), [dockerfile-converter](), [dockerfiles](), [getting-started](), [how-to](), [mcp](), [secure-container-images](), [zero-cve-containers]() ### AI overview Chainguard Academy has launched a hands-on course that teaches developers and DevOps teams how to use Chainguard's Dockerfile Converter to convert existing Dockerfiles into secure, minimal Chainguard container images. The course covers installation, Dockerfile instruction handling, customization, advanced usage, and best practices. ### Source excerpt Discover how to use Chainguard's new Dockerfile Converter tool to close the gap between legacy Dockerfiles and secure containers in our new course. ## Proficient Python: A free interactive online course DevFeed: [Proficient Python: A free interactive online course]() Original publisher: [Read original article]() Author: Pamela Fox (noreply@blogger.com) Published: 2025-06-23T21:17:00Z Content type: tutorial Language: en Sources: [Pamela Fox]() Topics: [Python](), [Learning](), [Programming](), [browser](), [Code]() Tags: [browser](), [course](), [development](), [free](), [learning](), [python]() ### AI overview Pamela Fox introduces ProficientPython.com, a free interactive course for learning introductory Python. The course teaches standard topics using a functions-first approach, with browser-based coding exercises that require no local Python setup. ### Source excerpt There are many ways to learn Python online, but there are also many people out there that want to learn Python for multiple reasons - so hey, why not add one more free Python course into the mix? I'm happy to finally release ProficientPython.com, my own approach to teaching introductory Python. The course covers standard intro topics - variables, functions, logic, loops, lists, strings, dictionaries, files, OOP. However, the course differs in two key ways from most others: It is based on functions from the very beginning (instead of being based on side effects). The coding exercises can be completed entirely in the browser (no Python setup needed). Let's explore those points in more detail. A functions-based approach Many introductory programming courses teach first via "side effects", asking students to either print out values to a console, draw some graphics, manipulate a webpage, that sort of thing. In fact, many of my courses have been side-effects-first, like my Intro to JS on Khan Academy that uses ProcessingJS to draw pictures, and all of our web development workshops for GirlDevelopIt. There's a reason that it's a popular approach: it's fun to watch things happen! But there's also a drawback to that approach: students struggle when it's finally time to abstract their code and refactor it into functions, and tend not to use custom functions even when their code would benefit from them. When I spent a few years teaching Python at UC Berkeley for CS61A, the first course in the CS sequence, I was thrown heads-first into the pre-existing curriculum. That course had originally been taught 100% in Scheme, and it stayed very functions-first when they converted it to Python in the 2000s. (I am explicitly avoiding calling it "functional programming" as functional Python is a bit more extreme than functions-first Python.) Also, CS61A had thousands of students, and functions-based exercises were easier to grade at scale - just add in some doctests! It was my first time ## Astro Solstice Festival DevFeed: [Astro Solstice Festival]() Original publisher: [Read original article]() Author: Matt Kane Published: 2025-06-23T00:00:00Z Content type: news Language: en Sources: [The Astro Blog]() Topics: [Astro](), [Open Source](), [Optimization](), [Security]() Tags: [2025](), [astro](), [community](), [content](), [course](), [deep-dive](), [design](), [events](), [experimental](), [images](), [learn](), [live-stream](), [open-source](), [optimization](), [security]() ### AI overview The Astro Solstice Festival was a week-long Astro celebration held from June 23 to June 27, 2025. It featured live streams, community challenges, educational discussions, Astro image optimization content, experimental live content collections, Content Security Policy features, and a design contest supporting Astro's open source mission. ### Source excerpt The planets have aligned to bring you the Astro Solstice Festival - a week-long celebration of all things Astro ## How Figma helps you learn Figma DevFeed: [How Figma helps you learn Figma]() Original publisher: [Read original article]() Author: Andrew Liebler; Kristen Bates Published: 2025-05-01T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [Template]() Tags: [beginner](), [community](), [course](), [design](), [education](), [examples](), [feature](), [figma](), [free](), [guides](), [learn](), [playground](), [product](), [resources](), [skills](), [tips-and-tricks](), [tutorials]() ### AI overview This Figma article introduces the Product Education team and describes resources for learning Figma, including Help Center guides, YouTube tutorials, interactive playground files, and a beginner course. It explains how community feedback shaped an updated course focused on hands-on practice, clearer explanations, real-world examples, free features, and a usable portfolio website template. ### Source excerpt Want to learn Figma but not sure where to start? Meet our Product Education team--your guides, cheerleaders, and fellow learners helping you discover the joy of creating. ## Foundations of AI and Machine Learning for Java Developers Course Review DevFeed: [Foundations of AI and Machine Learning for Java Developers Course Review]() Original publisher: [Read original article]() Author: vladmihalcea Published: 2025-04-11T08:26:55Z Content type: comparison Language: en Sources: [Vlad Mihalcea]() Topics: [Java](), [Machine Learning & Artificial Intelligence](), [Artificial Intelligence](), [Large Language Model](), [Retrieval Augmented Generation (RAG)]() Tags: [ai](), [course](), [java](), [large-language-models](), [learning](), [machine-learning](), [ml](), [retrieval-augmented-generation-rag](), [review](), [video]() ### AI overview A review of Frank Greco's Foundations of AI and Machine Learning for Java Developers video course. The course introduces AI and machine learning concepts, predictive and generative AI, large language models, RAG, and Java-based examples. ### Source excerpt Introduction In this article, I'm going to review the Foundations of AI and Machine Learning for Java Developers video course from my fellow Java Champion, Frank Greco. If you are new to AI and ML and want to get a great introduction to these topics, then you should definitely join watch the video lessons created by Frank Greco. And, thanks to LinkedIn Learning's generosity, until June 20, you can enroll in this video course for free. Video Course Agenda The course provides one hour and thirty-five minutes of video lessons that are... Read More The post Foundations of AI and Machine Learning for Java Developers Course Review appeared first on Vlad Mihalcea. ## A digital course for starting a front-end development career DevFeed: [A digital course for starting a front-end development career]() Original publisher: [Read original article]() Author: Mads Brodt Published: 2025-03-27T15:01:03Z Content type: release Language: en Sources: [Front-End Focus]() Topics: [Front end](), [Job]() Tags: [career](), [course](), [front-end](), [how-to](), [launch](), [skills]() ### AI overview The author announces a digital course for self-taught and early-career front-end developers. It focuses on in-demand skills, the realities of professional front-end work, and practical advice for finding a first job. The course is offered at 25% off for a limited launch period with a 30-day refund policy. ### Source excerpt How to crush today's crazy job market, grow your skills, and land a front-end job ## How I created my first Course with Datacamp DevFeed: [How I created my first Course with Datacamp]() Original publisher: [Read original article]() Published: 2025-01-22T00:00:00Z Content type: article Language: en Sources: [Mutt0-ds Notes]() Topics: [Microsoft](), [Security](), [Deployment](), [configuration](), [version](), [version-control](), [data analytics]() Tags: [configuration](), [course](), [data-analytics](), [deployment](), [microsoft](), [security](), [version]() ### AI overview The author describes creating and publishing a DataCamp course on advanced Microsoft Fabric topics, including security, configuration, version control, and deployment. The article explains how DataCamp's Fabric sandbox supports hands-on exercises and outlines the course-development process. ### Source excerpt I just published an online course! covering advanced Microsoft Fabric topics like security, deployment, admin settings, and version... ## Announcing Temporal 101 for .NET developers DevFeed: [Announcing Temporal 101 for .NET developers]() Original publisher: [Read original article]() Author: Angela Zhou Published: 2024-12-20T08:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [.NET](), [SDK]() Tags: [course](), [developers](), [free](), [how-to](), [net](), [slack](), [training](), [updates]() ### AI overview Temporal announces that its free, self-paced Temporal 101 course is now available for .NET developers. The hands-on course introduces durable execution, Temporal's core concepts and architecture, Workflows and Activities, and development with the Temporal .NET SDK. ### Source excerpt Take the free, self-paced, introductory course in Temporal for .NET. ## Python for AI DevFeed: [Python for AI]() Original publisher: [Read original article]() Published: 2024-11-16T00:00:00Z Content type: tutorial Language: en Sources: [Kodeco | High quality programming tutorials: iOS, Android, Swift, Kotlin, Unity, and more]() Topics: [Python](), [Programming](), [Artificial Intelligence](), [Data Science](), [Machine learning]() Tags: [ai](), [course](), [data-science](), [learning](), [libraries](), [programming](), [python]() ### AI overview A Python learning path for developers who already understand another programming language and want to prepare for AI programming. It covers Python fundamentals, programming environments, third-party libraries, data structures, file handling, JSON, networking, and AI APIs, with practical examples and JupyterLab. ### Source excerpt Python is the lingua-franca of data science, machine learning and AI. This course will teach you enough Python, based on your pre-existing knowledge of other programming languages, so that you are well-prepared for a journey into learning AI programming. You'll discover the fundamentals of python syntax, learn how to manage programming environments, work with third-party libraries and handle file and networking operations. It is not meant to be an introduction to your first programming language, but if you have a reasonable understanding of any other programming language then this is your fast-track to proficiency in Python. [Next page]()