Ai Prediction by Greg(OpenAi's president)

Happy and productive 2024!

@EmmersiveLearning

Building a Resilient Codebase! 💪

🛠 Focus on error handling
🔄 Build for failure recovery
📈 Plan for scalability
🚀 Embrace continuous deployment
🔍 Regularly update dependencies

Resilient code is key to a reliable application.

How do you make your codebase resilient? 👇

@EmmersiveLearning

start coding today!😍

Diving into a new framework?

Master it with these steps:

- Read the docs thoroughly 📖
- See one shot tutorial
- Start building minor projects
- Gradually move to major ones
- Join the community for support and insights 🤝
- Practice consistently! 💪

Step1 – HTML
Step2– CSS
Step3 – JavaScript
Step4 – Git+GitHub
Step5 – Build Project 👈
Step6 – React
Step7 – React Context
Step8 – Fetch external APIs
Step9 – Build Project 👈
Step10 – Next.js
Step11 – CI/CD
Step12 – Build Project 👈

🏆 – Frontend developer

@EmmersiveLearning

Let's go 2024

Frontend
•HTML + CSS
•Javascript
•React

Backend:
•Nodejs/Express
•Python/Django
•PHP/Laravel
•C#

Database
•MongoDB
•MySQL
•Postgres

Desktop
•Electron
•Tairi
•PyQt

Phones:
•React Native
•Flutter
•Kotlin

System
•Go
•C++
•Rust

Add more 💬👇


@EmmersiveLearning

Master Database Management:

The Database Tree 👇
|
|── Database Systems
| ├── Relational Databases (RDBMS)
| | ├── MySQL
| | ├── PostgreSQL
| | ├── Oracle Database
| | └── Microsoft SQL Server
| |
| ├── NoSQL Databases
| | ├── MongoDB
| | ├── Cassandra
| | ├── Redis
| | └── CouchDB
| |
| └── NewSQL Databases
| ├── Google Spanner
| └── CockroachDB
|
|── Database Models
| ├── Hierarchical Model
| ├── Network Model
| ├── Relational Model
| | ├── Tables
| | ├── Rows (Tuples)
| | └── Columns (Attributes)
| |
| ├── Object-Oriented Model
| ├── Document Model
| └── Graph Model
|
|── SQL (Structured Query Language)
| ├── Data Definition Language (DDL)
| | ├── CREATE TABLE
| | ├── ALTER TABLE
| | └── DROP TABLE
| |
| ├── Data Manipulation Language (DML)
| | ├── SELECT
| | ├── INSERT
| | ├── UPDATE
| | └── DELETE
| |
| ├── Data Control Language (DCL)
| | ├── GRANT
| | └── REVOKE
| |
| └── Transaction Control Language (TCL)
| ├── COMMIT
| ├── ROLLBACK
| └── SAVEPOINT
|
|── Database Design
| ├── Entity-Relationship Model (ERD)
| ├── Normalization
| ├── Denormalization
| └── Indexing
|
|── ACID Properties
| ├── Atomicity
| ├── Consistency
| ├── Isolation
| └── Durability
|
|── Joins
| ├── INNER JOIN
| ├── LEFT JOIN
| ├── RIGHT JOIN
| └── FULL OUTER JOIN
|
|── Transactions
| ├── Concurrent Transactions
| ├── Transaction Isolation Levels
| └── Deadlocks
|
|── Database Storage
| ├── Tablespace
| ├── Data Files
| └── Log Files
|
|── Data Security
| ├── Authentication
| ├── Authorization
| └── Encryption
|
|── Database Indexing
| ├── Types of Indexes
| | ├── B-Tree Index
| | ├── Hash Index
| | └── Bitmap Index
| |
| └── Query Optimization
|
|── Backup and Recovery
| ├── Full Backup
| ├── Incremental Backup
| └── Point-in-Time Recovery
|
|── Database Connectivity
| ├── ODBC (Open Database Connectivity)
| ├── JDBC (Java Database Connectivity)
| └── ORM (Object-Relational Mapping)
|
|── Big Data Databases
| ├── Apache Hadoop
| ├── Apache Cassandra
| └── Amazon DynamoDB
|
|── Data Warehousing
| ├── Star Schema
| ├── Snowflake Schema
| └── ETL (Extract, Transform, Load)
|
|── Database Administration
| ├── DBA Roles and Responsibilities
| ├── Performance Tuning
| └── Monitoring and Logging
|
|── Database Sharding
|
|── Cloud Databases
| ├── Amazon RDS
| ├── Azure SQL Database
| └── Google Cloud SQL
|
|── Time Series Databases
| ├── InfluxDB
| └── Prometheus
|
|── Geospatial Databases
| ├── PostGIS
| └── MongoDB Geospatial Queries
|
|── Mobile Databases
| ├── SQLite
| └── Realm
|
|── NoSQL Data Models
| ├── Document Store
| ├── Key-Value Store
| ├── Column-Family Store
| └── Graph Database
|
|── Database as a Service (DBaaS)
|
|── Graph Databases
| ├── Neo4j
| └── Amazon Neptune
|
|── In-Memory Databases
| ├── Redis
| └── Memcached
|
|── NewSQL Databases
| ├── Google Spanner
| └── CockroachDB
|
|── Data Governance
|
|── Data Migration
| ├── Schema Migration
| └── Data Migration Tools
|
|── Database Testing
|
|── Data Modeling Tools
| ├── ERwin
| ├── IBM Data Architect
| └── Microsoft Visio
|
|── Industry Standards
| ├── ANSI SQL
| └── ACID
|
|__ END ____

@EmmersiveLearning

🎯 Ways to use ChatGPT as a developer:

1. Solve Leetcode-type problems
2. Learn a new programming language
3. Create UI components
4. Use as a debugging tool
5. Generate config files
6. Write code comments
7. Generate regular expressions
8. Refactor code

Have any other ways?

@EmmersiveLearning

Programming languages and their uses

@EmmersiveLearning

what i feel, when i use chatGPT, Bard and copilot for my code.

he will be my side every time.