🌐 My Personal AI + Cloud Learning Toolkit (Free Resources I Use Daily) When I started diving deep into AI + Cloud engineering, I realized there’s so much noise out there. These are the free resources that actually made a difference for me: 🔹 Hands-On Labs: AWS Free Tier, Azure Free Account, and GCP Free Trial *Spin up real services without cost. *Great for practicing deployments in production-like environments. *Learn billing awareness & cost management early. 🔹 AI Practice: Google Colab and Notebook LM *Run AI/ML notebooks directly in the cloud. *Experiment with Python, TensorFlow, and PyTorch easily. *Share and collaborate on projects seamlessly. 🔹 Cert & Cloud Labs: KodeKloud (free to start, full access requires subscription) *Hands-on labs for Kubernetes, Docker, DevOps, and cloud. *Guided paths for certification prep. *Real sandbox environments to build muscle memory. 🔹 Structured Paths: Microsoft Learn *Free guided learning modules for AI + Cloud. *Interactive coding sandboxes. *Earn badges to track progress. 🔹 Community Power: *LinkedIn posts, Discord servers, and GitHub repos *Stay updated on real-world projects. *Network with others on the same path. Share progress to keep accountability. ✨ The best part? You don’t need to spend $$$ to start learning — just consistency and curiosity. 👉 What’s ONE free resource you swear by in your AI/Cloud journey? #CloudComputing #ArtificialIntelligence #CloudEngineering #LearningJourney #FreeResources #KodeKloud #NoteBookLM #AWS #Azure

BREAKING: Anthropic just dropped their Learn hub. 11 courses are now available for FREE. Here’s what you can learn: → Claude Code in Action → AI Fluency for Students → Claude on Amazon Bedrock → Anthropic API Fundamentals → Claude on Google Cloud’s Vertex → Teaching AI Fluency (for educators) → AI Fluency: Framework & Foundations → Prompt Engineering: Interactive Tutorial → Model Context Protocol: Getting Started → Tool Use (connect Claude to external tools) → Model Context Protocol: Advanced Concepts To access it: https://lnkd.in/dzBrpgze

BREAKING: Anthropic just dropped their Learn hub. 11 courses are now available for FREE. Here’s what you can learn: → Claude Code in Action → AI Fluency for Students → Claude on Amazon Bedrock → Anthropic API Fundamentals → Claude on Google Cloud’s Vertex → Teaching AI Fluency (for educators) → AI Fluency: Framework & Foundations → Prompt Engineering: Interactive Tutorial → Model Context Protocol: Getting Started → Tool Use (connect Claude to external tools) → Model Context Protocol: Advanced Concepts To access it: https://lnkd.in/dzBrpgze

BREAKING: Anthropic just dropped their Learn hub. 11 courses are now available for FREE. Here’s what you can learn: → Claude Code in Action → AI Fluency for Students → Claude on Amazon Bedrock → Anthropic API Fundamentals → Claude on Google Cloud’s Vertex → Teaching AI Fluency (for educators) → AI Fluency: Framework & Foundations → Prompt Engineering: Interactive Tutorial → Model Context Protocol: Getting Started → Tool Use (connect Claude to external tools) → Model Context Protocol: Advanced Concepts To access it: https://lnkd.in/dzBrpgze

BREAKING: Anthropic just dropped their Learn hub. 11 courses are now available for FREE. Here’s what you can learn: → Claude Code in Action → AI Fluency for Students → Claude on Amazon Bedrock → Anthropic API Fundamentals → Claude on Google Cloud’s Vertex → Teaching AI Fluency (for educators) → AI Fluency: Framework & Foundations → Prompt Engineering: Interactive Tutorial → Model Context Protocol: Getting Started → Tool Use (connect Claude to external tools) → Model Context Protocol: Advanced Concepts To access it: https://lnkd.in/dzBrpgze

Take a look at this FANTASTIC update! 👀 FutureLearn is now an Amazon Web Services (AWS) Select Tier Training Partner! 🎉 This partnership is about much more than launching courses. By bringing Amazon Web Services (AWS) into our ecosystem as a content partner, we’re combining their unrivalled expertise in cloud and AI with FutureLearn’s global platform and enterprise solutions. 🤝 Together, we’re making world-class training accessible at scale, and creating new opportunities for learners, institutions, and industries! Organisations will now be able to embed AWS training into scalable, personalised pathways for their workforce with #FLx, our enterprise learning platform, Through our exciting Content Partnerships, FutureLearn continues to be the bridge between leading institutions, world-class brands, and the learners who need them most. The first three Generative AI courses are already live! Check them out below 👇 🔵 AWS Artificial Intelligence Practitioner - https://lnkd.in/eScwDWvt 🔵 Generative AI for Decision Makers - https://lnkd.in/eViVyUE6 🔵 Generative AI for Developers - https://lnkd.in/eRGmfiUs This is only the start, and I’m looking forward to welcoming more partners who want to shape the future of learning with us. Kudos to Katie Millman and the AWS team for bringing this exciting collaboration to fruition! #AWS #GenerativeAI #FutureLearn #FLx #FutureOfWork

📢 Google Cloud just dropped 6 brand-new AI training courses 📢 Designed to keep your skills sharp and future-proof! Whether you're a Cloud Architect, a Data Scientist, or a developer, there's a course to help you build, deploy, and secure the next generation of AI applications. Here’s a quick look at what you can learn: 🔹 From Prompt to Prototype: Learn to quickly sketch and test ideas using Google AI Studio and the Gemini API. 🔹 Supervised Fine-tuning for Gemini: Take Google's powerful models and customize them for your specific tasks, making them your own. 🔹 Cloud Run for AI Inference: Deploy your AI innovations with the incredible speed and scale of serverless AI. 🔹 Model Armor: Get equipped to protect your generative AI applications from critical risks like prompt injection. 🔹 Build AI Agents with Databases: Learn to securely connect AI agents to your existing enterprise databases on Google Cloud. 🔹 AI Infrastructure mini courses: Master the framework for designing, deploying, and managing high-performance AI. Ready to build for your future? Check out the new courses on Google Cloud Skills Boost today! 👇 https://lnkd.in/eC9cR4uc

🚀 One of the most common questions I get: “Which AI/ML certification should I do?” In my network, I often see people sharing that they’ve completed courses from DeepLearning.ai, Coursera, and other platforms. While I haven’t done those myself (so I don’t have an opinion on them), I do hold all three AWS AI/ML certifications, and here’s what I think, based on my experience. 🔹 First, a key distinction: Unlike most AWS certifications that focus heavily on AWS services, the AI/ML track emphasizes machine learning concepts first, with AWS services layered on top. During my MBA, I took courses in Machine Learning and Statistics, and that foundation helped me a lot in these certifications. If you don’t have that foundation, I’d recommend starting with ML fundamentals (e.g., Andrew Ng, LinkedIn Learning, Udemy, etc.). 📚 Here’s a quick snapshot of each AWS AI/ML cert (in the order I suggest): 1️⃣ AWS Certified AI Practitioner (Foundational) A beginner-friendly certification that introduces you to AWS’s AI/ML services, concepts, and use cases — no heavy prerequisites. 2️⃣ AWS Certified Machine Learning Engineer – Associate Builds on foundational knowledge by covering the end-to-end ML workflow — data prep, model training, tuning, and deployment on AWS. 3️⃣ AWS Certified Machine Learning – Specialty The most advanced level, delving into deep learning, algorithmic optimization, and designing production-scale ML solutions on AWS. ✅ If your aim is to just get started with AWS AI/ML, go with the Practitioner first. From there, move to Associate and then Specialty as you gain more knowledge and hands-on experience. 💬 Which AI/ML certifications or courses have been most helpful in your journey? #AWS #AWSCertified #AWSCertification

I Completed my AWS Course 1. Cloud Exposure Unlike traditional theory-based courses, this program offered practical, cloud-based labs on AWS, where I directly worked with real tools instead of just reading about them. 2. Bridging Cloud + AI Many courses focus either on cloud computing or AI. This program uniquely blends AWS Cloud fundamentals with machine learning foundations, preparing learners to apply AI in scalable, real-world environments. 3. Industry-Backed Learning Being part of AWS Academy, the curriculum is designed in sync with what industries demand today, ensuring that the skills gained are directly employable. 4. Accelerated Learning Journey With 20 hours of intensive content, the course doesn’t just skim the surface — it compresses deep learning concepts, problem-solving exercises, and cloud-based experiments into a structured, career-ready format. 💡 My Key Takeaways A solid foundation in supervised, unsupervised, and reinforcement learning concepts. Confidence in leveraging AWS cloud services to deploy and test ML models. The mindset to innovate by combining cloud infrastructure with intelligent systems. #snsinstitutions #snsdesignthinkers #designthinking

If anyone is interested in developing their skills in Artificial Intelligence (AI), a quick thought based on my experience that might be helpful. 💬 Here are some tips for developing this skill: Dont fully rely on your college start your research online many platforms like coursera, google cloud, ibm, oracle they provide online courses for learning ai ml and deep learning Start your coding journey simple, pick one programming language that you are comfortable with dont mix up with multiple language Pick accordingly and start one by one