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Complete SQL road map
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1.Intro to SQL
β€’ Definition
β€’ Purpose
β€’ Relational DBs
β€’ DBMS

2.Basic SQL Syntax
β€’ SELECT
β€’ FROM
β€’ WHERE
β€’ ORDER BY
β€’ GROUP BY

3. Data Types
β€’ Integer
β€’ Floating-Point
β€’ Character
β€’ Date
β€’ VARCHAR
β€’ TEXT
β€’ BLOB
β€’ BOOLEAN

4.Sub languages
β€’ DML
β€’ DDL
β€’ DQL
β€’ DCL
β€’ TCL

5. Data Manipulation
β€’ INSERT
β€’ UPDATE
β€’ DELETE

6. Data Definition
β€’ CREATE
β€’ ALTER
β€’ DROP
β€’ Indexes

7.Query Filtering and Sorting
β€’ WHERE
β€’ AND
β€’ OR Conditions
β€’ Ascending
β€’ Descending

8. Data Aggregation
β€’ SUM
β€’ AVG
β€’ COUNT
β€’ MIN
β€’ MAX

9.Joins and Relationships
β€’ INNER JOIN
β€’ LEFT JOIN
β€’ RIGHT JOIN
β€’ Self-Joins
β€’ Cross Joins
β€’ FULL OUTER JOIN

10.Subqueries
β€’ Subqueries used in
β€’ Filtering data
β€’ Aggregating data
β€’ Joining tables
β€’ Correlated Subqueries

11.Views
β€’ Creating
β€’ Modifying
β€’ Dropping Views

12.Transactions
β€’ ACID Properties
β€’ COMMIT
β€’ ROLLBACK
β€’ SAVEPOINT
β€’ ROLLBACK TO SAVEPOINT

13.Stored Procedures
β€’ CREATE PROCEDURE
β€’ ALTER PROCEDURE
β€’ DROP PROCEDURE
β€’ EXECUTE PROCEDURE
β€’ User-Defined Functions (UDFs)

14.Triggers
β€’ Trigger Events
β€’ Trigger Execution and Syntax

15. Security and Permissions
β€’ CREATE USER
β€’ GRANT
β€’ REVOKE
β€’ ALTER USER
β€’ DROP USER

16.Optimizations
β€’ Indexing Strategies
β€’ Query Optimization

17.Normalization
β€’ 1NF(Normal Form)
β€’ 2NF
β€’ 3NF
β€’ BCNF

18.Backup and Recovery
β€’ Database Backups
β€’ Point-in-Time Recovery

19.NoSQL Databases
β€’ MongoDB
β€’ Cassandra etc...
β€’ Key differences

20. Data Integrity
β€’ Primary Key
β€’ Foreign Key

21.Advanced SQL Queries
β€’ Window Functions
β€’ Common Table Expressions (CTEs)

22.Full-Text Search
β€’ Full-Text Indexes
β€’ Search Optimization

23. Data Import and Export
β€’ Importing Data
β€’ Exporting Data (CSV, JSON)
β€’ Using SQL Dump Files

24.Database Design
β€’ Entity-Relationship Diagrams
β€’ Normalization Techniques

25.Advanced Indexing
β€’ Composite Indexes
β€’ Covering Indexes

26.Database Transactions
β€’ Savepoints
β€’ Nested Transactions
β€’ Two-Phase Commit Protocol

27.Performance Tuning
β€’ Query Profiling and Analysis
β€’ Query Cache Optimization

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Some good resources to learn SQL

1.Tutorial & Courses
β€’ Learn SQL: https://bit.ly/3FxxKPz
β€’ Udacity: imp.i115008.net/AoAg7K

2. YouTube Channel's
β€’ FreeCodeCamp:rb.gy/pprz73
β€’ Programming with Mosh: rb.gy/g62hpe

3. Books
β€’ SQL in a Nutshell: https://t.iss.one/DataAnalystInterview/158

4. SQL Interview Questions
https://t.iss.one/sqlanalyst/72?single

Join @free4unow_backup for more free resourses

ENJOY LEARNING πŸ‘πŸ‘
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Machine Learning Algorithms every data scientist should know:

πŸ“Œ Supervised Learning:

πŸ”Ή Regression
∟ Linear Regression
∟ Ridge & Lasso Regression
∟ Polynomial Regression

πŸ”Ή Classification
∟ Logistic Regression
∟ K-Nearest Neighbors (KNN)
∟ Decision Tree
∟ Random Forest
∟ Support Vector Machine (SVM)
∟ Naive Bayes
∟ Gradient Boosting (XGBoost, LightGBM, CatBoost)


πŸ“Œ Unsupervised Learning:

πŸ”Ή Clustering
∟ K-Means
∟ Hierarchical Clustering
∟ DBSCAN

πŸ”Ή Dimensionality Reduction
∟ PCA (Principal Component Analysis)
∟ t-SNE
∟ LDA (Linear Discriminant Analysis)


πŸ“Œ Reinforcement Learning (Basics):
∟ Q-Learning
∟ Deep Q Network (DQN)


πŸ“Œ Ensemble Techniques:
∟ Bagging (Random Forest)
∟ Boosting (XGBoost, AdaBoost, Gradient Boosting)
∟ Stacking

Don’t forget to learn model evaluation metrics: accuracy, precision, recall, F1-score, AUC-ROC, confusion matrix, etc.

Free Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

React ❀️ for more free resources
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SQL beginner to advanced level
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Random Module in Python πŸ‘†
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