Flow Community Inc.’s Post

As an industry we've made #Linux far easier to use but under the covers the #complexity remains.  This is just party of what we at Red Hat do to help prepare the next generation.

Unlock the secrets of high-performance computing and system design with this curated collection of free online courses. Dive into computer architecture, parallel computing, distributed systems, and more from top institutions. Whether you're a student or seasoned pro, these resources will equip you with the skills to tackle complex systems challenges. Explore the cutting-edge of systems engineering and push the boundaries of what's possible. #Systems #Tutorials #Programming #GetVM

A 2024 Hyperion Research survey commissioned by D-Wave reveals that over a quarter of over 300 surveyed decision makers identified the lack of in-house quantum computing skills as a major hurdle to their quantum optimization plans.     We’re proud to be part of a global movement to upskill today’s workforce with practical, in-demand quantum skills. Today we announced that our two quantum programming courses have experienced a remarkable increase in enrollment, with Foundations for Quantum Programming,” and “Quantum Programming Core" seeing 53% and 85% respectively in the first two quarters of 2024 compared to the same period of 2023.    Our beginner and intermediate quantum programming courses equip learners with little to no coding background with practical skills they need to succeed, covering essential math concepts, Python, problem formulation and more.     Join us for our upcoming trainings July 8-12 and July 29-Aug. 2 to experience why enrollments are greatly accelerating and why nearly 90% of our students recommend our courses.    Read the announcement and register today. https://lnkd.in/gcmYb8KX    #QuantumOptimization

Today's Insight: Essential Courses for Aspiring Software Engineers As a software engineer, these university courses have been invaluable: 1. Data Structures and Algorithms 2. Operating Systems 3. Computer Networks 4. Database Management Systems 5. Software Engineering 6. Object-Oriented Programming 7. Machine Learning 8. Web Development 9. Discrete Mathematics 10. Cybersecurity These courses lay the foundation and provide crucial skills for a successful career. Keep learning and growing! #SoftwareEngineering #CareerGrowth #ContinuousLearning

Great keynote from AWS' Leonardo de Moura about Lean, a functional programming language, which is used for formal mathematics, software and hardware verification, AI for math and code synthesis, and math and computer science education: https://lnkd.in/ezJzqUjK #AutomatedReasoning #FormalVerification #AWS

"The fundamentals and skills themselves are evolving. Most introductory computer science courses focus on code syntax and getting programs to run, and while knowing how to read and write code is still essential, testing and debugging—which aren’t commonly part of the syllabus—now need to be taught more explicitly." #software #computerscience https://lnkd.in/etP-mPtk

If you're trying to teach yourself programming, data analytics, or anything involving computing, I highly recommend spending some time on the fundamentals of how these crazy machines work. You don’t need to become an expert in computer engineering, but having a grasp of the basics will provide crucial context and make everything else you learn easier. At least, that was my experience as a self-taught Python analyst! Here are the top 3 resources that helped me break through the initial learning curve in computer science (in the order I’d recommend approaching them): 1. Crash Course Computer Science 🤖 If you're totally new, this is a great place to start. If you're a STEM student, you're probably familiar with one or more of the "Crash Course" YouTube series. This particular series provides a broad, entertaining overview of major topics in computing. 2. Code: The Hidden Language of Computer Hardware and Software by Charles Petzold 💡 This book walks you through how computers work, starting with simple concepts like Morse Code and Braille to illustrate the basics of communication. It then introduces bits, binary logic, and electrical circuits before diving into logic gates—the building blocks of computing. It shows how logic gates are used to create complex components capable of counting, arithmetic, and storing memory. These building blocks are combined in growing complexity to explain how components like RAM, processors, and operating systems function. It’s a detailed but approachable book, and it cleared up so much confusion for me. Bridging the gap step-by-step between the electrons and silicon at the physical level and the abstractions of logic, systems, and code. 3. The Secret Life of Programs: Understand Computers — Craft Better Code by Jonathan 👨💻 This book serves as an excellent follow-up to Code. While it touches on some of the same hardware concepts, it quickly moves into higher levels of abstraction, focusing more on programming, software design, and performance. It covers practical issues like security, portability, maintenance, and even documentation. Although it doesn’t dive deeply into any one topic, it provides a fantastic overview of how everything connects and fits into the bigger picture. 🧠 These are the resources that helped me the most! 🤔 What resources have you found helpful, or what would you recommend as an accessible introduction to computer science? Please share your thoughts! #Programming #DataAnalytics #ComputerScience #SelfTaught #Coding #TechResources #SoftwareEngineering

Hello everyone, I am currently writing an article on Computer Science vs. Software Engineering. I would love to hear your thoughts on these two different degrees. If you are interested, please comment or DM me with your answers! Many thanks. #Research #Article #ComputerScience #Ai #MachineLearning #Programming #SoftwareEngineering

A formal education in computer science and computer engineering may seem interchangeable, but did you know that the two actually diverge significantly? While both require a strong foundation in math, logic, and basic computer programming skills, the subjects covered in each major differ greatly. In the first half of a formal education, the subjects covered in both majors overlap significantly. However, after this point, the two fields diverge greatly. Computer science majors will focus on topics such as algorithms, data structures, and programming languages, while computer engineering majors will delve into hardware design, computer architecture, and digital logic. So, which major should you pick? It depends on where you want your career to go. If you're interested in software development, computer science may be the better choice. On the other hand, if you're interested in hardware design or computer systems architecture, computer engineering may be the way to go. Remember, both majors are highly valuable and in-demand fields. Choose the path that aligns with your interests and career goals.