Today marked another fantastic step in our deep tech journey! Participants in the Data Science & Machine Learning track got a practical class following a nationwide live session. They dived into an interactive introduction to SQL the bedrock of data manipulation. We're not just teaching; we're building the future of tech in Nigeria, covering crucial areas like: Data Science and Machine Learning. Advanced Data Analysis and Visualisation Computer Vision and Natural Language Processing. This week's session was buzzing with real-time problem-solving and query building. Huge props to the learners for their active participation! #DataAnalytics #SQLForDataScience #BrainBuildersIT #3MTT #DataScienceNigeria #DeepLearning #SkillsForFuture @3MTTNigeria @DeepTech_Ready @dsn_ai_network

📜 SQL Cheat Sheet 🔍 Fetching Data (SELECT) SELECT * FROM table_name; SELECT column1, column2 FROM table_name; SELECT DISTINCT column FROM table_name; _____________________________________________________ 🎯 Filtering Data (WHERE) SELECT * FROM users WHERE age > 25; SELECT * FROM orders WHERE status = 'delivered'; _____________________________________________________ 🧩 Multiple Conditions (AND, OR, NOT) SELECT * FROM users WHERE age > 25 AND city = 'Delhi'; SELECT * FROM products WHERE price < 500 OR stock > 50; SELECT * FROM employees WHERE NOT department = 'HR'; _____________________________________________________ 🔢 Sorting Results (ORDER BY) SELECT * FROM employees ORDER BY salary DESC; SELECT * FROM products ORDER BY price ASC, name DESC; _____________________________________________________ 🎛 Limiting & Skipping (LIMIT, OFFSET) SELECT * FROM products LIMIT 5; SELECT * FROM orders LIMIT 10 OFFSET 5; _________________________________________________________ 🏗 Grouping Data (GROUP BY, HAVING) SELECT department, COUNT(*) FROM employees GROUP BY department; SELECT category, AVG(price) FROM products GROUP BY category HAVING AVG(price) > 100; _________________________________________________________ 🏆 Aggregations (COUNT, SUM, AVG, MIN, MAX) SELECT COUNT(*) FROM users; SELECT SUM(price) FROM orders; SELECT AVG(salary) FROM employees; SELECT MIN(age), MAX(age) FROM users; _____________________________________________________ 🔄 Joining Tables (JOIN) 👫 Inner Join SELECT users.name, orders.amount FROM users INNER JOIN orders ON users.id = orders.user_id; _____________________________________________________ 📌 Left Join SELECT users.name, orders.amount FROM users LEFT JOIN orders ON users.id = orders.user_id; _________________________________________________________ 📌 Right Join SELECT users.name, orders.amount FROM users RIGHT JOIN orders ON users.id = orders.user_id; _____________________________________________________ 🔗 Full Join SELECT users.name, orders.amount FROM users FULL JOIN orders ON users.id = orders.user_id; _____________________________________________________ 🏗 Creating & Modifying Tables 🆕 Creating a Table CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), age INT, city VARCHAR(50) ); _____________________________________________________ 🔧 Altering a Table ALTER TABLE users ADD COLUMN email VARCHAR(100); ALTER TABLE users DROP COLUMN city; _____________________________________________________ 📝 Modifying Data ➕ Inserting Data INSERT INTO users (id, name, age) VALUES (1, 'Amit', 30); _____________________________________________________ 🛠 Updating Data UPDATE users SET age = 31 WHERE id = 1; _____________________________________________________ ❌ Deleting Data DELETE FROM users WHERE id = 1; DELETE FROM users; -- Delete all rows _____________________________________________________ 🏛 Indexes & Keys 🔑 Primary Key CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100) ); _____________________________________________________ 🔑 Foreign Key CREATE TABLE orders ( id INT PRIMARY KEY, user_id INT, FOREIGN KEY (user_id) REFERENCES users(id) ); _____________________________________________________ 🚀 Creating Index CREATE INDEX idx_name ON users(name); _____________________________________________________ 📜 Subqueries & Unions 🔄 Subquery SELECT name FROM users WHERE id IN (SELECT user_id FROM orders); _____________________________________________________ 🔗 Union (Combine Results) SELECT name FROM customers UNION SELECT name FROM suppliers; SELECT name FROM customers UNION ALL SELECT name FROM suppliers; -- Includes duplicates _____________________________________________________ 🔥 Transactions BEGIN TRANSACTION; UPDATE accounts SET balance = balance - 500 WHERE id = 1; UPDATE accounts SET balance = balance 500 WHERE id = 2; COMMIT; -- Save changes ROLLBACK; -- Undo changes #SQL #SQLTutorial #LearnSQL #SQLQueries #SQLCheatSheet #Database #DataScience #Programming #Tech #Code #SQLForBeginners #SQLBasics #SQLTraining #LearnToCode #CodingForBeginners #AdvancedSQL #SQLPerformance #SQLOptimization #SQLBestPractices #SQLDatabase #MySQL #PostgreSQL #SQLServer #OracleSQL #NoSQL #DataAnalytics #SQLForDataScience #BusinessIntelligence #BigData #DataVisualization

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Day 16 #100daysofcode #30daysofdata #sqlfordatascience (@DataCamp - Learnt about "self-join"(joining a table to itself) basic calculations using "self-join" - Learnt the use of the "CASE" clause together with the use of the "WHEN", "THEN", "ELSE" AND "END" clauses.

Day 15 #100daysofcode #30daysofdata #sqlfordatascience(@DataCamp) - Learnt the "sorting of single columns" - Learnt the "sorting of multiple columns" - Learnt the use of the "GROUP BY" clause - Introduction to the basics of the "JOIN" keyword to link multiple TABLES contd...

Day 11 #100DaysOfCode #javascripot(@freeCodeCamp ) -Learnt the "iteration of objects" with while loop #sqlfordatascience(@DataCamp) Topics Learnt are: -"Selecting" of "single" and "multiple" columns -"Selecting distinct" -Learning the use and practice of "Count" contd..

Devanan66504151: Devanan66504151: iamerkan: Done with week one, I’m glad that I can still recall CSE 670 - Into to Database Systems class. #SQLforDataScience #SQL #100DaysOfCode #coding

Devanan66504151: iamerkan: Done with week one, I’m glad that I can still recall CSE 670 - Into to Database Systems class. #SQLforDataScience #SQL #100DaysOfCode #coding

Done with week one, I’m glad that I can still recall CSE 670 - Into to Database Systems class. #SQLforDataScience #SQL #100DaysOfCode #coding

Learned SQL For Data Analysts from data36.com. Thanks @data36_com for this great series. Had my first Remote server @digitalocean. It's been a great start toward SQL. #SqlForDataScience #DataScience #LearnByDoing