🚀 New MySQL Tutorial!
In the previous video, we learned how to add records to a table using INSERT INTO.
Now we will learn how to retrieve and display that data using the SELECT Query.
In this video, you will learn:
✅ SELECT *
✅ Selecting specific columns
✅ Column aliases using AS
✅ Removing duplicates using DISTINCT
✅ Limiting results using LIMIT
✅ Common beginner mistakes
✅ A practical SQL challenge
What would you like to learn first?
1️⃣ SELECT *
2️⃣ Specific columns
3️⃣ DISTINCT
4️⃣ LIMIT
Write your answer in the comments.
Video link: https://youtu.be/PmEPvJ8K1CY
#MySQL #SQL #Database #LearnSQL #CodingForBeginners
In the previous video, we learned how to add records to a table using INSERT INTO.
Now we will learn how to retrieve and display that data using the SELECT Query.
In this video, you will learn:
✅ SELECT *
✅ Selecting specific columns
✅ Column aliases using AS
✅ Removing duplicates using DISTINCT
✅ Limiting results using LIMIT
✅ Common beginner mistakes
✅ A practical SQL challenge
What would you like to learn first?
1️⃣ SELECT *
2️⃣ Specific columns
3️⃣ DISTINCT
4️⃣ LIMIT
Write your answer in the comments.
Video link: https://youtu.be/PmEPvJ8K1CY
#MySQL #SQL #Database #LearnSQL #CodingForBeginners
YouTube
Understanding SELECT Queries in MySQL PART-1 | Database Basics
Learn how to use the MySQL SELECT Query to retrieve data from a database table.
In this beginner-friendly MySQL tutorial, you will learn how to display all records, select specific columns, rename columns using AS, remove duplicate values with DISTINCT,…
In this beginner-friendly MySQL tutorial, you will learn how to display all records, select specific columns, rename columns using AS, remove duplicate values with DISTINCT,…
🚀 Just uploaded: Create Android Emulator (AVD) in 3 Minutes!
Struggling with Android Studio emulator setup? I'll show you the FASTEST way to create a virtual device, choose the right system image, and run your first app — ZERO errors guaranteed!
👉 Watch here: https://youtu.be/--yabhWT24U
💬 Question: Which do you prefer for testing — Emulator or Real Device? Drop your answer!
#AndroidStudio #AVD #AndroidEmulator #AndroidDevelopment #CodingTutorial
Struggling with Android Studio emulator setup? I'll show you the FASTEST way to create a virtual device, choose the right system image, and run your first app — ZERO errors guaranteed!
👉 Watch here: https://youtu.be/--yabhWT24U
💬 Question: Which do you prefer for testing — Emulator or Real Device? Drop your answer!
#AndroidStudio #AVD #AndroidEmulator #AndroidDevelopment #CodingTutorial
YouTube
Create Android Emulator in 3 Minutes ⚡ | AVD Manager Setup 2026 for Beginners
🔥 Learn how to create Android Virtual Device (AVD) in Android Studio 2026 — step by step, NO errors!
In this video, I'll show you how to set up Android Emulator from scratch using AVD Manager, select the right system image, and run your first Android app…
In this video, I'll show you how to set up Android Emulator from scratch using AVD Manager, select the right system image, and run your first Android app…
❤2
CLAUDE CODE seekhna hai YOUTUBE se free me ? then checkout this playlist from my favourite channel🔥
https://youtube.com/playlist?list=PLKnIA16_RmvaYH3poI0oJvbDF4zEvpq8W&si=yk-R9jn4hQpfF_Bk
https://youtube.com/playlist?list=PLKnIA16_RmvaYH3poI0oJvbDF4zEvpq8W&si=yk-R9jn4hQpfF_Bk
*🚀 Complete Roadmap to Become an AI Engineer*
*📌 Phase 1: Programming Fundamentals*
Learn the foundation of programming with Python.
✅ What is Programming?
✅ What is Python?
✅ Installing Python & VS Code
✅ Variables
✅ Data Types
✅ Input & Output
✅ Type Casting
✅ Operators
✅ Conditional Statements (if, else, elif)
✅ Loops (for, while)
✅ Functions
✅ Lambda Functions
✅ Recursion
✅ Strings
✅ Lists
✅ Tuples
✅ Sets
✅ Dictionaries
✅ List & Dictionary Comprehensions
✅ Object-Oriented Programming (OOP)
✅ File Handling
✅ Exception Handling
✅ Modules & Packages
✅ Virtual Environments
✅ pip Package Manager
✅ Git & GitHub
*📌 Phase 2: Python for Data*
Learn how Python is used for data analysis and preprocessing.
✅ NumPy
✅ Pandas
✅ Data Cleaning
✅ Data Transformation
✅ Data Aggregation
✅ Exploratory Data Analysis (EDA)
✅ Matplotlib
✅ Seaborn
✅ Feature Engineering
*📌 Phase 3: SQL*
Master SQL to work with structured data.
✅ Database Fundamentals
✅ SELECT
✅ WHERE
✅ ORDER BY
✅ LIMIT
✅ Aggregate Functions
✅ GROUP BY
✅ HAVING
✅ CASE WHEN
✅ Joins
✅ Subqueries
✅ Common Table Expressions (CTEs)
✅ Window Functions
✅ Views
✅ Stored Procedures
✅ Indexes
*📌 Phase 4: Mathematics*
Build the mathematical foundation required for AI.
✅ Statistics
✅ Probability
✅ Linear Algebra
✅ Vectors
✅ Matrices
✅ Calculus Basics
✅ Gradient Descent
*📌 Phase 5: Machine Learning*
Understand how machines learn from data.
✅ Introduction to Machine Learning
✅ Types of Machine Learning
✅ Regression
✅ Classification
✅ Clustering
✅ Decision Trees
✅ Random Forest
✅ KNN
✅ Support Vector Machines (SVM)
✅ Naive Bayes
✅ XGBoost
✅ Model Evaluation
✅ Cross Validation
✅ Hyperparameter Tuning
✅ Scikit-learn
*📌 Phase 6: Deep Learning*
Learn neural networks and modern AI models.
✅ Neural Networks
✅ Perceptrons
✅ Activation Functions
✅ Backpropagation
✅ TensorFlow
✅ PyTorch
✅ CNN
✅ RNN
✅ LSTM
✅ Transformers
✅ Attention Mechanism
*📌 Phase 7: Natural Language Processing (NLP)*
Teach computers to understand human language.
✅ Text Preprocessing
✅ Tokenization
✅ Stemming
✅ Lemmatization
✅ TF-IDF
✅ Word Embeddings
✅ Word2Vec
✅ Sentence Transformers
✅ BERT
✅ Text Classification
✅ Named Entity Recognition (NER)
*📌 Phase 8: Large Language Models (LLMs)*
Learn how modern AI models work.
✅ What are LLMs?
✅ Tokens
✅ Context Window
✅ GPT
✅ Claude
✅ Gemini
✅ Llama
✅ Mistral
✅ Qwen
✅ Open-source vs Closed-source Models
✅ Temperature
✅ Top-P
✅ Top-K
*📌 Phase 9: Prompt Engineering*
Learn how to communicate effectively with AI.
✅ Zero-shot Prompting
✅ One-shot Prompting
✅ Few-shot Prompting
✅ Chain of Thought
✅ Role Prompting
✅ Structured Prompting
✅ JSON Output
✅ Prompt Templates
✅ Prompt Chaining
*📌 Phase 10: LLM APIs*
Integrate AI models into applications.
✅ OpenAI API
✅ Anthropic API
✅ Gemini API
✅ Hugging Face API
✅ Groq API
✅ Together AI
✅ Ollama
✅ LM Studio
✅ Function Calling
✅ Structured Outputs
*📌 Phase 11: Embeddings*
Learn how AI converts text into vectors.
✅ Embeddings
✅ Embedding Models
✅ Cosine Similarity
✅ Dense Embeddings
✅ Sparse Embeddings
✅ Hybrid Search
*📌 Phase 12: Vector Databases*
Store and retrieve embeddings efficiently.
✅ FAISS
✅ ChromaDB
✅ Pinecone
✅ Weaviate
✅ Milvus
✅ Qdrant
✅ pgvector
*📌 Phase 13: Retrieval-Augmented Generation (RAG)*
Build AI systems that use external knowledge.
✅ Document Loading
✅ Chunking
✅ Embeddings
✅ Indexing
✅ Retrieval
✅ Re-ranking
✅ Metadata Filtering
✅ Hybrid Search
✅ Advanced RAG
✅ Graph RAG
✅ Corrective RAG
✅ Agentic RAG
*📌 Phase 1: Programming Fundamentals*
Learn the foundation of programming with Python.
✅ What is Programming?
✅ What is Python?
✅ Installing Python & VS Code
✅ Variables
✅ Data Types
✅ Input & Output
✅ Type Casting
✅ Operators
✅ Conditional Statements (if, else, elif)
✅ Loops (for, while)
✅ Functions
✅ Lambda Functions
✅ Recursion
✅ Strings
✅ Lists
✅ Tuples
✅ Sets
✅ Dictionaries
✅ List & Dictionary Comprehensions
✅ Object-Oriented Programming (OOP)
✅ File Handling
✅ Exception Handling
✅ Modules & Packages
✅ Virtual Environments
✅ pip Package Manager
✅ Git & GitHub
*📌 Phase 2: Python for Data*
Learn how Python is used for data analysis and preprocessing.
✅ NumPy
✅ Pandas
✅ Data Cleaning
✅ Data Transformation
✅ Data Aggregation
✅ Exploratory Data Analysis (EDA)
✅ Matplotlib
✅ Seaborn
✅ Feature Engineering
*📌 Phase 3: SQL*
Master SQL to work with structured data.
✅ Database Fundamentals
✅ SELECT
✅ WHERE
✅ ORDER BY
✅ LIMIT
✅ Aggregate Functions
✅ GROUP BY
✅ HAVING
✅ CASE WHEN
✅ Joins
✅ Subqueries
✅ Common Table Expressions (CTEs)
✅ Window Functions
✅ Views
✅ Stored Procedures
✅ Indexes
*📌 Phase 4: Mathematics*
Build the mathematical foundation required for AI.
✅ Statistics
✅ Probability
✅ Linear Algebra
✅ Vectors
✅ Matrices
✅ Calculus Basics
✅ Gradient Descent
*📌 Phase 5: Machine Learning*
Understand how machines learn from data.
✅ Introduction to Machine Learning
✅ Types of Machine Learning
✅ Regression
✅ Classification
✅ Clustering
✅ Decision Trees
✅ Random Forest
✅ KNN
✅ Support Vector Machines (SVM)
✅ Naive Bayes
✅ XGBoost
✅ Model Evaluation
✅ Cross Validation
✅ Hyperparameter Tuning
✅ Scikit-learn
*📌 Phase 6: Deep Learning*
Learn neural networks and modern AI models.
✅ Neural Networks
✅ Perceptrons
✅ Activation Functions
✅ Backpropagation
✅ TensorFlow
✅ PyTorch
✅ CNN
✅ RNN
✅ LSTM
✅ Transformers
✅ Attention Mechanism
*📌 Phase 7: Natural Language Processing (NLP)*
Teach computers to understand human language.
✅ Text Preprocessing
✅ Tokenization
✅ Stemming
✅ Lemmatization
✅ TF-IDF
✅ Word Embeddings
✅ Word2Vec
✅ Sentence Transformers
✅ BERT
✅ Text Classification
✅ Named Entity Recognition (NER)
*📌 Phase 8: Large Language Models (LLMs)*
Learn how modern AI models work.
✅ What are LLMs?
✅ Tokens
✅ Context Window
✅ GPT
✅ Claude
✅ Gemini
✅ Llama
✅ Mistral
✅ Qwen
✅ Open-source vs Closed-source Models
✅ Temperature
✅ Top-P
✅ Top-K
*📌 Phase 9: Prompt Engineering*
Learn how to communicate effectively with AI.
✅ Zero-shot Prompting
✅ One-shot Prompting
✅ Few-shot Prompting
✅ Chain of Thought
✅ Role Prompting
✅ Structured Prompting
✅ JSON Output
✅ Prompt Templates
✅ Prompt Chaining
*📌 Phase 10: LLM APIs*
Integrate AI models into applications.
✅ OpenAI API
✅ Anthropic API
✅ Gemini API
✅ Hugging Face API
✅ Groq API
✅ Together AI
✅ Ollama
✅ LM Studio
✅ Function Calling
✅ Structured Outputs
*📌 Phase 11: Embeddings*
Learn how AI converts text into vectors.
✅ Embeddings
✅ Embedding Models
✅ Cosine Similarity
✅ Dense Embeddings
✅ Sparse Embeddings
✅ Hybrid Search
*📌 Phase 12: Vector Databases*
Store and retrieve embeddings efficiently.
✅ FAISS
✅ ChromaDB
✅ Pinecone
✅ Weaviate
✅ Milvus
✅ Qdrant
✅ pgvector
*📌 Phase 13: Retrieval-Augmented Generation (RAG)*
Build AI systems that use external knowledge.
✅ Document Loading
✅ Chunking
✅ Embeddings
✅ Indexing
✅ Retrieval
✅ Re-ranking
✅ Metadata Filtering
✅ Hybrid Search
✅ Advanced RAG
✅ Graph RAG
✅ Corrective RAG
✅ Agentic RAG
*📌 Phase 14: AI Agents*
Build autonomous AI applications.
✅ AI Agent Fundamentals
✅ Tool Calling
✅ Memory
✅ Planning
✅ Reflection
✅ Multi-step Reasoning
✅ Agent Workflows
✅ Multi-Agent Systems
✅ MCP (Model Context Protocol)
✅ A2A Protocol
✅ Human-in-the-loop
*📌 Phase 15: AI Frameworks*
Learn the most popular AI development frameworks.
✅ LangChain
✅ LangGraph
✅ LlamaIndex
✅ CrewAI
✅ Agno
✅ DSPy
✅ OpenAI Agents SDK
✅ AutoGen
*📌 Phase 16: Backend Development*
Create APIs and AI applications.
✅ FastAPI
✅ REST APIs
✅ Authentication
✅ Async Python
✅ WebSockets
*📌 Phase 17: Deployment*
Deploy AI applications to production.
✅ Docker
✅ Docker Compose
✅ Kubernetes Basics
✅ Nginx
✅ CI/CD
✅ GitHub Actions
✅ Render
✅ Railway
✅ AWS
✅ Azure
✅ Google Cloud
*📌 Phase 18: LLMOps & MLOps*
Monitor and manage AI systems.
✅ MLflow
✅ LangSmith
✅ Weights & Biases
✅ Prompt Versioning
✅ Logging
✅ Tracing
✅ Monitoring
✅ Evaluation Pipelines
✅ A/B Testing
*📌 Phase 19: AI Security*
Build secure and reliable AI applications.
✅ Prompt Injection
✅ Jailbreak Attacks
✅ Guardrails
✅ PII Detection
✅ Output Validation
✅ Hallucination Reduction
✅ Content Moderation
✅ Secret Management
*📌 Phase 20: AI Performance Optimization*
Improve speed, cost, and efficiency.
✅ Prompt Optimization
✅ Semantic Caching
✅ Batch Processing
✅ Streaming Responses
✅ Token Optimization
✅ Quantization
✅ Model Routing
✅ Latency Optimization
*📌 Phase 21: Build Real-World Projects*
Apply your knowledge through practical projects.
✅ AI Chatbot
✅ PDF Chat Application
✅ Resume Analyzer
✅ AI Interview Assistant
✅ AI SQL Assistant
✅ AI Code Reviewer
✅ AI Research Assistant
✅ AI Email Assistant
✅ AI Data Analyst
✅ AI Content Generator
✅ Voice Assistant
✅ Multi-Agent Research System
*📌 Phase 22: AI System Design*
Learn to design scalable AI systems.
✅ AI Architecture
✅ Scalable AI Applications
✅ Distributed Systems
✅ Load Balancing
✅ Queue Systems
✅ Event-Driven Architecture
✅ Cost Optimization
*📌 Phase 23: Portfolio*
Build a strong portfolio to showcase your skills.
✅ GitHub Projects
✅ Deploy Live Applications
✅ Technical Blogs
✅ LinkedIn Posts
✅ Open Source Contributions
✅ Case Studies
✅ Personal Portfolio Website
*📌 Phase 24: Interview Preparation*
Prepare for AI Engineer interviews.
✅ Python Interview Questions
✅ SQL Interview Questions
✅ Machine Learning Interview Questions
✅ Deep Learning Interview Questions
✅ LLM Interview Questions
✅ RAG Interview Questions
✅ AI Agent Interview Questions
✅ System Design Interviews
✅ Coding Problems
✅ Behavioral Interview Questions
❤️ *Double tap if you want a detailed explanation of each topic!*
Build autonomous AI applications.
✅ AI Agent Fundamentals
✅ Tool Calling
✅ Memory
✅ Planning
✅ Reflection
✅ Multi-step Reasoning
✅ Agent Workflows
✅ Multi-Agent Systems
✅ MCP (Model Context Protocol)
✅ A2A Protocol
✅ Human-in-the-loop
*📌 Phase 15: AI Frameworks*
Learn the most popular AI development frameworks.
✅ LangChain
✅ LangGraph
✅ LlamaIndex
✅ CrewAI
✅ Agno
✅ DSPy
✅ OpenAI Agents SDK
✅ AutoGen
*📌 Phase 16: Backend Development*
Create APIs and AI applications.
✅ FastAPI
✅ REST APIs
✅ Authentication
✅ Async Python
✅ WebSockets
*📌 Phase 17: Deployment*
Deploy AI applications to production.
✅ Docker
✅ Docker Compose
✅ Kubernetes Basics
✅ Nginx
✅ CI/CD
✅ GitHub Actions
✅ Render
✅ Railway
✅ AWS
✅ Azure
✅ Google Cloud
*📌 Phase 18: LLMOps & MLOps*
Monitor and manage AI systems.
✅ MLflow
✅ LangSmith
✅ Weights & Biases
✅ Prompt Versioning
✅ Logging
✅ Tracing
✅ Monitoring
✅ Evaluation Pipelines
✅ A/B Testing
*📌 Phase 19: AI Security*
Build secure and reliable AI applications.
✅ Prompt Injection
✅ Jailbreak Attacks
✅ Guardrails
✅ PII Detection
✅ Output Validation
✅ Hallucination Reduction
✅ Content Moderation
✅ Secret Management
*📌 Phase 20: AI Performance Optimization*
Improve speed, cost, and efficiency.
✅ Prompt Optimization
✅ Semantic Caching
✅ Batch Processing
✅ Streaming Responses
✅ Token Optimization
✅ Quantization
✅ Model Routing
✅ Latency Optimization
*📌 Phase 21: Build Real-World Projects*
Apply your knowledge through practical projects.
✅ AI Chatbot
✅ PDF Chat Application
✅ Resume Analyzer
✅ AI Interview Assistant
✅ AI SQL Assistant
✅ AI Code Reviewer
✅ AI Research Assistant
✅ AI Email Assistant
✅ AI Data Analyst
✅ AI Content Generator
✅ Voice Assistant
✅ Multi-Agent Research System
*📌 Phase 22: AI System Design*
Learn to design scalable AI systems.
✅ AI Architecture
✅ Scalable AI Applications
✅ Distributed Systems
✅ Load Balancing
✅ Queue Systems
✅ Event-Driven Architecture
✅ Cost Optimization
*📌 Phase 23: Portfolio*
Build a strong portfolio to showcase your skills.
✅ GitHub Projects
✅ Deploy Live Applications
✅ Technical Blogs
✅ LinkedIn Posts
✅ Open Source Contributions
✅ Case Studies
✅ Personal Portfolio Website
*📌 Phase 24: Interview Preparation*
Prepare for AI Engineer interviews.
✅ Python Interview Questions
✅ SQL Interview Questions
✅ Machine Learning Interview Questions
✅ Deep Learning Interview Questions
✅ LLM Interview Questions
✅ RAG Interview Questions
✅ AI Agent Interview Questions
✅ System Design Interviews
✅ Coding Problems
✅ Behavioral Interview Questions
❤️ *Double tap if you want a detailed explanation of each topic!*
❤4
🔥 You can now use Claude Fable 5 — the WORLD'S #1 AI coding model — completely FREE!
I just uploaded a full step-by-step tutorial showing the entire setup:
✅ Get a free API key (no credit card)
✅ Connect everything & start vibe coding
Watch here:https://youtu.be/y-irRmuy-KY
Have you tried Fable 5 yet? What's the first project you'd build with it? Drop your ideas below! 👇
#Fable5 #FreeAI #AICoding #CS CORNER
I just uploaded a full step-by-step tutorial showing the entire setup:
✅ Get a free API key (no credit card)
✅ Connect everything & start vibe coding
Watch here:https://youtu.be/y-irRmuy-KY
Have you tried Fable 5 yet? What's the first project you'd build with it? Drop your ideas below! 👇
#Fable5 #FreeAI #AICoding #CS CORNER
YouTube
Get Claude Fable 5 through API FREE
🚀 Learn how to use Claude Fable 5 for FREE with FreeModel API—no credit card required! In this beginner-friendly tutorial, I'll show you how to get a free API key, set up OpenCode, connect Claude Fable 5, and start AI coding in minutes.
🔗 Links:
Git Installation:…
🔗 Links:
Git Installation:…
{
"env": {
"ANTHROPIC_API_KEY": "YOUR_API_KEY",
"ANTHROPIC_BASE_URL": "https://cc.freemodel.dev",
"ANTHROPIC_DEFAULT_FABLE_MODEL": "claude-fable-5",
"ANTHROPIC_DEFAULT_FABLE_MODEL_NAME": "Fable 5",
"ANTHROPIC_DEFAULT_FABLE_MODEL_DESCRIPTION": "Most Capable Model!",
"CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1",
"CLAUDE_CODE_PACKAGE_MANAGER_AUTO_UPDATE": "0"
},
"permissions": {
"allow": [],
"deny": []
},
"model": "fable",
"theme": "dark"
}
Fable 5 Free 🔥
"env": {
"ANTHROPIC_API_KEY": "YOUR_API_KEY",
"ANTHROPIC_BASE_URL": "https://cc.freemodel.dev",
"ANTHROPIC_DEFAULT_FABLE_MODEL": "claude-fable-5",
"ANTHROPIC_DEFAULT_FABLE_MODEL_NAME": "Fable 5",
"ANTHROPIC_DEFAULT_FABLE_MODEL_DESCRIPTION": "Most Capable Model!",
"CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1",
"CLAUDE_CODE_PACKAGE_MANAGER_AUTO_UPDATE": "0"
},
"permissions": {
"allow": [],
"deny": []
},
"model": "fable",
"theme": "dark"
}
Fable 5 Free 🔥
❤4🔥1