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Cloud Skills of 2025

Cloud Skills of 2025 top cloud skills required in 2025 , based on emerging trends, enterprise demands, and evolving technologies: 🚀 Core Cloud Skills (Foundational) Cloud Platforms Proficiency: AWS , Microsoft Azure , Google Cloud Platform (GCP) Understand core services: Compute, Storage, Networking, Databases Cloud Architecture & Design: Designing scalable, fault-tolerant systems Multi-cloud and hybrid cloud architecture Cloud-native architecture (microservices, containers, serverless) DevOps & Automation: CI/CD tools: Jenkins, GitHub Actions, Azure DevOps Infrastructure as Code (IaC): Terraform, AWS CloudFormation, Bicep Container orchestration: Docker, Kubernetes 🧠 AI/ML Integration with Cloud Cloud AI Services: Azure AI (OpenAI integration, ML Studio) AWS SageMaker GCP Vertex AI Data Engineering for AI: Cloud-based ETL pipelines: Azure Data Factory, AWS Glue Data lakes and warehouses: BigQuery, Snowflake...

Full 1-Year AI Learning Roadmap

Here’s a full year-wise (12-month) detailed plan to master Artificial Intelligence from scratch — even if you are starting with just basic coding knowledge. 📚 Full 1-Year AI Learning Roadmap Month 1-2: Foundations (Mathematics + Programming) Mathematics for AI: Linear Algebra: Vectors, Matrices, Matrix multiplication Calculus: Derivatives, Chain Rule, Partial Derivatives Probability and Statistics: Bayes' Theorem, Mean, Variance, Standard Deviation Optimization Basics: Gradient Descent Programming: Master Python (focus on data structures, loops, functions, OOP) Learn libraries: NumPy, Pandas, Matplotlib ✅ Mini project : Matrix calculator Simple data visualizations (bar, scatter plots) Month 3-4: Machine Learning (ML) Basics Core ML Concepts: Supervised Learning (Linear Regression, Logistic Regression) Unsupervised Learning (K-Means, PCA) Model Evaluation (Accuracy, Precision, Recall, F1 Score) Important Algorithms: Decision ...

Topics to study for Artificial Intelligence

Topics to study for Artificial Intelligence for Developer, Architect, Mangers Ai is the present and future of technology and it's going to be unfolded in multiple ways. There is no doubt with industry revolution is going taking a new era with the help of AI and to Job markets demand the expertise in this niche technology. Here’s a clear and structured list of important topics you need to study in Artificial Intelligence (AI) : 🧠 Fundamental Topics: Introduction to AI History and Evolution of AI Types of AI (Narrow, General, Super AI) Mathematics for AI Linear Algebra (Vectors, Matrices, Eigenvalues) Calculus (Derivatives, Integrals, Gradient Descent) Probability & Statistics (Bayes’ Theorem, Distributions) Optimization Techniques (Convex optimization) Programming for AI Python basics Libraries (NumPy, Pandas, Matplotlib, Scikit-Learn) 🤖 Core AI Topics: Machine Learning (ML) Supervised Learning (Regression, Classificatio...

AI & ML Programs Worldwide

🌍 Top 39 AI & ML Programs Worldwide United States Massachusetts Institute of Technology (MIT) – Renowned for its cutting-edge AI research and interdisciplinary approach. Carnegie Mellon University (CMU) – Offers specialized AI programs and is a leader in ML research. Stanford University – Known for its contributions to AI and proximity to Silicon Valley. University of California, Berkeley – Home to the Berkeley Artificial Intelligence Research (BAIR) Lab. University of Washington – Active in AI research and applications. University of Illinois at Urbana-Champaign – Notable for AI research and publications. University of Texas at Austin – Offers robust AI and ML curricula. University of California, San Diego – Engaged in diverse AI research areas. Cornell University – Provides comprehensive AI programs. Georgia Institute of Technology – Known for its strong AI and robotics programs. University of Michigan, Ann Arbo...

NVIDIA GeForce RTX 5090

NVIDIA GeForce RTX 5090 🆕 NVIDIA GeForce RTX 5090 – Key Specifications NVIDIA comes up with another marvelous GPU which is flagship of RTX 5090. This GPU is designed for enthusiasts seeking top-tier performance, especially in 4K gaming scenarios. Date and Year of Launch: April' 2025 Architecture: Blackwell CUDA Cores: 21,760 VRAM: 32GB Power Consumption: Up to 575W Recommended PSU: At least 1,000W Price: $1,999 USD Design: Redesigned Founders Edition with a two-slot form factor suitable for small form factor PCs Advanced Cooling: Enhanced cooling system to manage increased power draw Connectivity: Updated DisplayPort and HDMI ports for improved compatibility DLSS 4: Features Multi Frame Generation, delivering significant frame rate boosts—up to 8x in certain scenarios 🚀 Performance Highlights 4K Gaming: The RTX 5090 excels in 4K gaming, offering substantial performance improvements over its predecessors. DLSS 4: The in...

How Human can interact with AI

How Human can interact with AI Let’s dive into AI and human interaction in detail — how it's evolved, how it works, the fields it's transforming, and what the future looks like. 🤝 What is AI-Human Interaction? AI-Human Interaction refers to the way humans and artificial intelligence systems communicate, collaborate, and influence each other . This interaction can be through natural language (like talking to ChatGPT), visual cues (facial recognition, gesture control), or behavioral inputs (how you type, shop, or drive). 🧠 Types of AI-Human Interaction 1. Conversational AI Voice assistants (e.g., Siri, Alexa) Chatbots in customer service (e.g., airlines, banks) Multilingual translation tools Example: Using ChatGPT to generate emails, code, or ideas. 2. Collaborative AI AI acts as a co-pilot rather than a tool. Used in writing , design , coding , data analysis , and more. Example: GitHub Copilot helps programmers write code more efficiently...