Parallel computing using MPI

*This is the only course you need to become a WordPress front-end developer build a website and blog - all while learning all about the WordPress Dashboard tools.*Why WordPress? Between 470-500 million sites use WordPress – making it the number one website Content Management System (CMS) globally.If you are a beginner that want to master WordPress’ Content Management System?orIf you are looking for training that defines the WordPress Interface and teaches you how to build websites?Then, this course was made for you!Likewise, this course is recommended for you if any of these apply to you:1. You are new to WordPress or an advanced user needing detailed knowledge of WordPress’ interface.2. You own a business and need to design your own website and content.3. You want to build a blog, portfolio, or business website.4. You want to learn all about WordPress technology with hands-on training.5. You want to start your own website design business and build websites for others.Are you ready to build and manage a WordPress website with confidence—without feeling overwhelmed or confused by the WordPress dashboard? If so, then this is the course for you; and you do not have to install any software on your computer.This WordPress Training Course is a step-by-step, beginner-friendly guide designed to help you understand WordPress from the ground up with over 50 hands-on exercises. Whether you’re creating a personal blog, business website, or portfolio, this course walks you through every essential tool, menu, and feature you’ll need to get your site up and running successfully.Starting with the basics, you will learn how WordPress works, what tools are required, and how to choose the right domain and hosting. From there, we dive deep into the WordPress Dashboard, breaking down each menu i

Artificial intelligence ( AI) in its broadest sense, is intelligence exhibited by machines, particularly computer systems. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. Such machines may be called artificial intelligence. High- profile applications of artificial intelligence include advance web search engines example Google search, recommended systems used by YouTube, Amazon, and Netflix. Machine learning is the study of programs that can improve their performance on a given task automatically. It has been a part of artificial intelligence from the beginning. There are several kinds of machine learning. Unsupervised learning analyzes a stream of data and finds patterns and makes predictions without any other guidance. Supervised learning requires labeling the training data with the expected answers and comes in two main varieties. The expression computation intelligence usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly definition of computational intelligence. Artificial intelligence has become mainstream, there is growing concern about how this will influence elections. Potential targets of artificial intelligence include election processes, election offices, election officials and election vendors. Workin together to foster leadership, promote AI literacy, provide guidance build capacity and support innovation, we can ensure that AI enhances education for all students.

This course contains the use of artificial intelligence. Stop Guessing. Start Engineering.Most pilots spend years "tuning" their drones by pure guesswork—downloading random presets, blindly dragging PID sliders, and praying their motors don’t turn into smoke under load.This is not tuning; it's a gamble. Blindly copying configs from the internet only works until you hit your first non-standard payload or a sudden gust of wind. It’s time to move past amateur trial-and-error and master the engineering behind the flight.This course is not a collection of "magic" settings. It is a deep, fundamental dive into the mathematics of flight. We will deconstruct every number in your Betaflight configurator and teach you to read Blackbox data like a pro. Whether you are building a lightning-fast 5-inch freestyle rig or a massive 10-inch heavy-lifter, you will learn to transform your build into a monolithic, predictable, and fail-safe machine that executes commands with surgical precision.And the best part? These engineering principles are universal. The filter logic you master here will become your rock-solid foundation for tackling advanced autonomous systems, including ArduPilot and Mission Planner.What you will master:Professional Analytics: Master Blackbox Explorer and PIDToolbox. Learn to read complex spectrograms, visually isolate noise, and dominate structural resonance.Fundamental Methodologies: Learn the two core schools of tuning: the aggressive P-First method (for telepathic control response) and the D-First method (to ensure maximum hardware longevity).Versatility (5" to 10"+): We’ll squeeze razor-sharp agility out of 5-inch freestyle builds, find the perfect "zen" for 7-inch long-range cruisers, and tame the massive inertia of 10-inch cargo drones—yes, even teaching them to flip with a 4.5kg payload.Hardware Safety Protocol

Prepare for the ISACA® Advanced in AI Risk™ (AAIR™) certification with full-length, exam-realistic practice tests.This course delivers scenario-based questions written to the style and difficulty of the real AAIR exam (90 questions, MOST/BEST judgment format), fully aligned to the three official exam domains and their published weightings:Domain 1 — AI Risk Governance and Framework Integration (37%)Domain 2 — AI Life Cycle Risk Management (21%)Domain 3 — AI Risk Program Management (42%)What makes this course different:An explanation for every option — why the correct answer is right and why each distractor is wrong.Verified official sources on every question, with verbatim citations from NIST AI RMF, ISO/IEC 42001, the EU AI Act, OWASP Top 10 for LLM Applications, MITRE ATLAS and more.Visual explainer diagrams for key concepts (NIST AI RMF functions, EU AI Act risk tiers, the three lines model for AI, the AI life cycle, supply-chain risk, and more).Per-domain score breakdown so you can target your revision.Important — exam eligibility: the official AAIR exam requires candidates to hold an active qualifying certification (e.g., CISA, CISM, CRISC, CGEIT, CDPSE, CISSP, CIA, CPA, PMI-RMP). These practice tests are useful to anyone studying AI risk, but the AAIR credential itself has that prerequisite — please check your eligibility on the ISACA website before booking the exam.Disclaimer: This is an independent, unofficial preparation course. It is not affiliated with, endorsed by, or sponsored by ISACA. ISACA®, AAIR™, CISA®, CISM®, CRISC® and CGEIT® are trademarks of ISACA. All questions are original and were not taken from the real exam.

Kursus ini dirancang untuk memberikan pengetahuan dasar tentang metode numerik dan pembahasan berbagai metode numerik yang bisa diterapkan saat menyelesaikan permasalahan di bidang teknik.Kursus ini akan bermanfaat bagi:Mahasiswa yang ingin berkarir di bidang teknik sebagai engineer.Engineer saat melamar pekerjaan di bidangnya. Penguasaan pengetahuan tentang metode numerik akan memberikan keunggulan saat wawancara pekerjaan.Engineer saat menjalani pekerjaannya yang akan berhadapan dengan berbagai permasalahan yang bisa diselesaikan dengan memakai pengetahuan tentang metode numerik.Topik-topik di dalam kursus ini disampaikan melalui berbagai gambar, tabel, diagram, dan skema; sehingga akan lebih mudah diserap peserta.Kursus ini dikembangkan dari pengalaman instruktur mengajarkan matakuliah Metode Numerik di fakultas Teknik selama bertahun-tahun.Kursus ini membahas tentang:Pengantar metode numerik, model matematika, dan error.Berbagai area permasalahan dimana metode numerik bisa dipakai, seperti: akar fungsi satu variabel bebas, integrasi numerik, interpolasi, sistem persamaan linear, dan regresi.Pembahasan berbagai teknik dalam metode numerik, seperti: metode biseksi dan metode Newton-Raphson untuk mencari akar fungsi satu variabel bebas; aturan trapesium, aturan Simpson 1/3, dan aturan Simpson 3/8 untuk menghitung integral secara numerik; metode Gregory-Newton beda hingga maju dan beda hingga mundur untuk melakukan interpolasi; iterasi Jacobi dan iterasi Gauss-Seidel untuk menyelesaikan sistem persamaan linear; regresi linear polinomial order 1 dan regresi kuadratik polinomial order 2 untuk mencari fungsi regresi dari data tersebar. Hendri Yanto - MathemaNesos

In this course, you will learn Statistical DownScaling Model (SDSM) software. In this modern world as a researcher, we design analysis and explore climate by using software to enhance the best quality analysis. Because of accurate results and analysis by Statistical DownScaling Model (SDSM) software, we are able taking decisions properly to predict the climatic change of the world of different parts.To enhance the proper analysis of rainfall, temperature, humidity, etc, of the different parts of the world, this Statistical DownScaling Model (SDSM) climatic Data Analysis Course will help you perfectly with proper guidelines.With my professional experience, I have created this course with a proper sequence of steps of topics so that you can understand and learn the proper way. Although the course is focused on Statistical DownScaling Model (SDSM), the climatic concepts and steps are used with references to parameters of different climatic data. The course focuses on the analysis and knowledge utilized on a professional level worldwide.After completing this course you will get the following outcomes:Will be able to process data perfectly.Will be able to use SDSM Software confidently.Will be able to analyze rainfall data.Will be able to analyze temperature data.Will be able to analyze humidity data.Will be able to analyze streamflow data.Will be able to take the critical decision on climate change.And Many more...