Complete SQL road map
ππ
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
------------------ END -------------------
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 ππ
ππ
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
------------------ END -------------------
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 ππ
β€4
Machine Learning Algorithms every data scientist should know:
π Supervised Learning:
πΉ Regression
β Linear Regression
β Ridge & Lasso Regression
β Polynomial Regression
πΉ Classification
β Logistic Regression
β K-Nearest Neighbors (KNN)
β Decision Tree
β Random Forest
β Support Vector Machine (SVM)
β Naive Bayes
β Gradient Boosting (XGBoost, LightGBM, CatBoost)
π Unsupervised Learning:
πΉ Clustering
β K-Means
β Hierarchical Clustering
β DBSCAN
πΉ Dimensionality Reduction
β PCA (Principal Component Analysis)
β t-SNE
β LDA (Linear Discriminant Analysis)
π Reinforcement Learning (Basics):
β Q-Learning
β Deep Q Network (DQN)
π Ensemble Techniques:
β Bagging (Random Forest)
β Boosting (XGBoost, AdaBoost, Gradient Boosting)
β Stacking
Donβt 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 β€οΈ for more free resources
π Supervised Learning:
πΉ Regression
β Linear Regression
β Ridge & Lasso Regression
β Polynomial Regression
πΉ Classification
β Logistic Regression
β K-Nearest Neighbors (KNN)
β Decision Tree
β Random Forest
β Support Vector Machine (SVM)
β Naive Bayes
β Gradient Boosting (XGBoost, LightGBM, CatBoost)
π Unsupervised Learning:
πΉ Clustering
β K-Means
β Hierarchical Clustering
β DBSCAN
πΉ Dimensionality Reduction
β PCA (Principal Component Analysis)
β t-SNE
β LDA (Linear Discriminant Analysis)
π Reinforcement Learning (Basics):
β Q-Learning
β Deep Q Network (DQN)
π Ensemble Techniques:
β Bagging (Random Forest)
β Boosting (XGBoost, AdaBoost, Gradient Boosting)
β Stacking
Donβt 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 β€οΈ for more free resources
β€3