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Emmersive Learning

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Learn Fullstack Development | Coding. Youtube : https://www.youtube.com/@EmmersiveLearning/ Website : https://emmersivelearning.com/ Contact Admin : @MehammedTeshome

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  • 11 февр. 2025 г.Data Analysis ማለት በ አጭሩ ከ ብዙ መረጃዎች ውስጥ ጠቃሚ ግንዛቤን ማግኜት ማለት ነው። ይህ ፊልድ በተለይ በዚህኛው ዘመን አስፈላጊነቱ ከፍ ያለ ነው። ምክንያቱም በየቀኑ የምናመነጨው የዳታ መጠን ከምንጊዜውም በላይ እየጨመረ ነው። ይህን እጅግ ብዙ መረጃ ለመረዳትና ከዚሁ ሁሉ ውስጥ ጠቃሚ መረጃወቺን ለማውጣት የ ዳታ አናላይሲስ ወሳኝ ነው። ከ ሌሎች ዲሲፕሊኖች ለየት የሚያደርገው ደግሞ ይህ ነገር በሁሉም መረጃ ባለበት ሁሉ አስፈላጊ መሆኑ ነው። ለምሳሌ ፡ - - ንግድ ላይ ላለ ሰው የ ደንበኞችን ባህሪ ፤ የ ገበያ አዝማሚያዎችን እና አጠቃላይ የ ንግድ አፈፃፀምን ለመረዳትና የተሻሉ እና ትክክለኛ ውሳኔዎችን ለማድረግ የ ዳታ ትንተና (analysis) ይጠቀማል። - በተለያዩ የህክምና ምረምሮች ላይ በሺታዎችን ለመረዳት ፤ አዳዲስ ህክምናዎችን ግኜቶችን ለማዘጋጀት እና ውስብስብ ችግሮን ለመፍታት የ ዳታ ትንተና ያስፈልጋቸዋል። - በ ማህበራዊ ጉዳዮች ላይ እንደ ድህነት ፤ ወንጀል ፤የ አየር ንብረት እና መሰል ለውጦችን ለመረዳት እና ለመፍታት የ ዳታ ትንተና አስፈልጊ ነው። እነዚህን እና መሰል ነገሮች ተንትኖ ጠቃሚ እይታና ውሳኔ እንዲኖረን በማድረግ የዳታ ትንተና ( Data Analytics ) ወሳኝ ሚና አለው። የ ዳታ ትንተና ይሄን ያህል አስፈላጊ ከሆነ መሰረታዊ ነገሮቹ እነዚህ ናቸው። 1. መረጃን መሰብሰብ (Data Collection) 2. መረጃ ማፅዳት ( Data Cleaning ) 3. መረጃን ማደራጀት ( Data Organization ) 4. መረጃን መተንተን (Data Analyzing ) 5. መረጃን መተርጎም ( Data Visualizing ) 6. Data Presenting. ....ይቀጥላል... #Data_Analytics1,63%
  • 5 авг.💻 Software Engineer Stage 1: Programming Language Stage 2: Git + GitHub Stage 3: Data Structures & Algorithms Stage 4: OOP Stage 5: Databases Stage 6: APIs Stage 7: System Design Stage 8: Docker Stage 9: Cloud Stage 10: Testing Stage 11: CI/CD Stage 12: Build Real Products 🏆 Software Engineer unlocked 🙌1,40%
  • 26 июл.AI Engineer Learning Roadmap (2026) 🎯 Step 1: Learn Python ✅ Variables & Data Types ✅ Loops & Functions ✅ Object-Oriented Programming ✅ Exception Handling ✅ File Handling ✅ Modules & Packages 🎯 Step 2: Master Python Libraries ✅ NumPy ✅ Pandas ✅ Matplotlib ✅ Scikit-learn 🎯 Step 3: Learn AI Fundamentals ✅ Artificial Intelligence ✅ Machine Learning ✅ Deep Learning ✅ Neural Networks ✅ Generative AI ✅ Large Language Models (LLMs) 🎯 Step 4: Learn Prompt Engineering ✅ Zero-shot Prompting ✅ One-shot Prompting ✅ Few-shot Prompting ✅ Role Prompting ✅ Chain of Thought Prompting 🎯 Step 5: Learn LLMs ✅ Tokenization ✅ Embeddings ✅ Context Window ✅ Temperature ✅ Model Parameters 🎯 Step 6: Learn RAG ✅ Embeddings ✅ Chunking ✅ Vector Databases ✅ Similarity Search ✅ Retrieval Pipeline 🎯 Step 7: Learn AI Agents ✅ Agent Architecture ✅ Memory ✅ Planning ✅ Tool Calling ✅ Multi-Agent Systems 🎯 Step 8: Learn AI Frameworks ✅ LangChain ✅ LangGraph ✅ LlamaIndex ✅ CrewAI 🎯 Step 9: Learn Backend Development ✅ FastAPI ✅ REST APIs ✅ Authentication ✅ Database Integration 🎯 Step 10: Deploy AI Applications ✅ Docker ✅ Git & GitHub ✅ Cloud Platforms (AWS, Azure, or GCP) ✅ Monitoring & Logging 🎯 Step 11: Build Projects ✅ AI Chatbot ✅ PDF Chat Assistant ✅ AI Research Assistant ✅ AI Resume Analyzer ✅ Customer Support Agent ✅ AI Coding Assistant Watch this Ai Roadmap Video 👇 : https://youtu.be/tKO4lOq32p01,34%
  • 13 авг.The most important Meta Skill in the Ai era is : Learning how to learn with AI. Instead of only just reading one book, Ask AI to: - explain it - quiz you - debate you - generate projects - create flashcards - simulate experts - find weaknesses AI becomes your personal university. @ImmersiveAi1,16%
  • 30 июл.Congratulations! to @ImmersiveAi 🎉🎉 😊 Thank you All. 🤍 Subscribe for Ai related Contents. Link : https://www.youtube.com/@ImmersiveAi11,12%
  • 9 авг.New Video : Machine Learning for beginners. https://youtu.be/RoSwoJzgWnY0,97%
  • 26 июн. 2024 г.Data Structures in short : - Primitive: - byte - short - int - float - char - boolean - long - double - Non-Primitive: - Linear: - Array - Stack - Queue - Linked-list - Non-linear: - Trees - Graph - Heap - Hash #datastructure #algorithm @EmmersiveLearning0,95%
  • 29 июл.How to Get a Job as an AI Developer in 6 Months: 🚀 Month 1 🧠 Learn Python basics 📊 Understand math essentials 📚 Learn how models work at a high level ⚙️ Month 2 📘 Learn NumPy, Pandas, Matplotlib 🤖 Start with Machine Learning 🔍 Build 3 ML mini-projects 🛠 Month 3 🧠 Learn PyTorch or TensorFlow 📸 Build a small neural network 🎧 Try 1 NLP project + 1 Computer Vision project 🧪 Understand losses, activations, overfitting 🧠 Month 4 ⚡️ Learn LLM basics 🛠 Use OpenAI/Anthropic 🔗 Build RAG apps, chatbots, agents, and tools 🧩 Learn vector databases 🌍 Month 5 🌐 Launch 3 real projects 🚀 Deploy on Vercel, Render, or AWS ⚡️ Create a polished GitHub + portfolio 💼 Month 6 📄 Build an AI-specific resume 💬 Join AI dev communities & hackathons 📨 Apply to 2–5 AI/ML roles daily 🧠 Prep for interviews If you are on this Journey....Let's Connect here. Share for those who needs this. @ImmersiveAi0,88%
  • 30 июл.Our New Channel is Growing. And now...Look the Synchronicity. ..It's 3-6-9. 😊 It's Manifesting highly. Let's make it 1k today. Subscribe and Share it for those who wants to learn AI. Link : https://www.youtube.com/@ImmersiveAi10,81%
  • 9 сент. 2025 г.без подписи0,73%
  • 29 июл.Most people learning AI make this mistake... They jump straight into Machine Learning, Deep Learning, or LLMs... ...without learning NumPy. That's like trying to build a skyscraper without understanding concrete. Why is NumPy so important? ✅ It's the foundation of Python for Data Science. ✅ It powers fast numerical computation. ✅ It makes working with large datasets efficient. ✅ Libraries like Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, and many others are built on top of it or heavily rely on its array concepts. If you want to become an: • AI Engineer • Data Scientist • Machine Learning Engineer • Data Analyst NumPy isn't optional—it's one of the first tools you should master. Spend a few hours learning it now, and you'll save hundreds of hours later when building AI applications. That's why I created a complete 80-minute NumPy course that takes you from beginner to confident with the fundamentals. Link : https://youtu.be/mIgz-n5vMQY @ImmersiveAI0,71%
  • 1 авг.New Video : Python Pandas Course for Data Analysis. https://youtu.be/GV_pxp4I3280,67%