Exploring Python’s Built-in Functions
This article introduces Python’s built-in functions for working with math, data types, iterables, and input/output. It also explains when to use each one to write code that feels more natural in Python.
Short, useful summaries of coding, AI, and education news, with a practical next step for learners.
This article introduces Python’s built-in functions for working with math, data types, iterables, and input/output. It also explains when to use each one to write code that feels more natural in Python.
This quiz checks your knowledge of Python’s built-in functions for math, data types, iterables, and input/output. It also helps you learn when to use each function.
The excerpt says AI is becoming a business capability across many sectors, but many organisations still struggle to move beyond experiments. It argues that success depends less on technical tools and more on an AI mindset: curiosity, critical thinking, strategic use, responsible implementation, and change management.
This article explains how NumPy reshape() changes the shape of an array in Python. It shows how to add or remove dimensions and how the data is rearranged when you reshape it.
Khan Academy argues that a correct answer alone does not show how a student understands a problem. Explaining, revising, and reasoning make that thinking visible, which supports more useful feedback and timely intervention. AI should support this process rather than replace it.
This quiz practices NumPy's reshape() method for changing an array's dimensions. It covers adding or removing dimensions and controlling how the values are rearranged.
UNESCO and LG launched a free, nine-hour intermediate AI ethics course on Coursera. It is available in 11 languages, requires no advanced technical knowledge, and uses hands-on projects to examine privacy, transparency, sustainability, and human autonomy.
Google and the University of Waterloo’s Futures Lab is helping students create practical AI tools. The program also aims to prepare students for future jobs by giving them real-world experience.
Teachers see AI as a way to fill subject and language gaps for bilingual students. Researchers are exploring chatbots and multilingual models that can adapt learning materials, support parent-child dialogue, and offer explanations in a child’s home language while keeping core content in English. Experts say the approach could expand access if used well.
Sal Khan says the first version of Khanmigo did not improve learning as the team had hoped. Later iterations placed AI inside practice, prompted students to explain their thinking, avoided simply giving answers, and aimed to multiply teachers’ capacity.
Elizabeth Kennard moved from archaeology into an application support role after completing a coding bootcamp. Full-stack fundamentals, agile teamwork, hackathons, and real projects helped her build experience without a previous technical career.
An Indigenous school’s technology coordinator describes how AI changed teachers’ work from routine support to urgent problem-solving. Teachers felt panic and embarrassment when student writing turned out to be AI-generated, leaving students to succeed without much learning. These incidents showed a broader policy gap the school had to address.
Microsoft’s third AI in Education Report surveyed over 3,000 students, educators, and leaders in six countries. The discussion highlights that while many people have tried AI tools, daily use is still much lower, student optimism has dipped, and leaders and teachers disagree about how much training has happened. It also suggests the cheating concern reflects a broader academic integrity issue, not just AI.
This article explains how to create reusable mixin classes in Python. It also shows how mixins differ from abstract base classes and highlights common mistakes to avoid when using them.
The excerpt says AI and data science are changing how healthcare insights are made, including work on new treatments. It also warns that AI can reflect bias in data or system design. To help students think critically, the DSAIY high school curriculum teaches machine learning, bias, and model evaluation through hands-on activities and an AI-a-thon.
The Experience AI programme works with partners around the world to support AI literacy, with materials in 19+ languages and partners in over 38 countries. The article explains why localisation matters and why Croatian is being treated as simply a language, not a “small” one. It also describes how translating new technology terms can be difficult, even for common concepts like AI.
Code Club is presented as a free, creative space where young people experiment with technology, build projects, and learn by having fun. The excerpt says it helps them grow in confidence, resilience, teamwork, and problem solving, not just programming. Schools, libraries, and community centres can run clubs with existing equipment and access free resources and support.