Core 1: Hardware and Network Troubleshooting

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Core 1: Hardware and Network Troubleshooting

Coursera · Intermediate ·🔍 RAG & Vector Search ·3mo ago

Key Takeaways

Hardware and network troubleshooting for IT professionals using CompTIA A+ certification

Original Description

More than 1 million IT professionals have built their IT careers on the CompTIA A+ certification (CompTIA). This Core 1 – Hardware and Network Troubleshooting course from IBM comprehensively prepares you for the first of the two exams required to earn this industry certification employers look for. The course is ideal for professionals looking to kickstart their IT career in IT support. You’ll build practical skills to set up, configure, and troubleshoot devices, networks, and systems in today’s work environments. You’ll gain a strong foundation in hardware and networking concepts, including troubleshooting laptops, mobile devices, video and resolution issues, storage, and printers. Plus, you’ll learn about configurations, power supply basics, and how to identify key motherboard and storage components. Throughout, you’ll get hands-on in online labs and then complete a final project where you’ll apply your knowledge in real-world scenarios. Whether you’re starting your IT career or looking to advance in your current role, this course provides essential exam preparation and job-ready skills employers value. Enroll today and take the next step toward a successful career in IT.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Optimizing RAG at Scale: Chunking, Retrieval, and the Bayesian Search That Cut Latency 40%
Learn how to optimize RAG at scale by implementing chunking, retrieval, and Bayesian search to reduce latency by 40%
Dev.to AI
📰
Why Your Chatbot Feels Dumb — And How RAG Fixes It
Learn how RAG technology can improve your chatbot's performance by addressing its limitations, making it more informative and user-friendly
Medium · RAG
📰
5 RAG Optimization Techniques Every AI Engineer Should Know In 2026
Optimize Retrieval-Augmented Generation (RAG) systems using 5 techniques: metadata filtering, ANN search, embedding caching, async retrieval, and quantization, to improve performance and accuracy
Medium · AI
📰
5 RAG Optimization Techniques Every AI Engineer Should Know In 2026
Optimize RAG models using 5 key techniques for improved performance and efficiency, essential for AI engineers working with Retrieval-Augmented Generation
Medium · Machine Learning
Up next
LLM Wiki vs RAG Explained | Complete LLM Wiki Implementation Guide
Pavithra’s Podcast
Watch →