Dylan  Iqbal

Dylan Iqbal

1658453413

Learn Apache Cassandra Database – Full Course

Apache Cassandra Database – Full Course for Beginners

Apache Cassandra is an open source NoSQL distributed database. This beginner's Cassandra course has four modules. The first three modules will cover the basics Apache Cassandra data modeling. The final module covers practical applications of Cassandra.

⭐️ Course Contents ⭐️
⌨️ (00:30) Module 1: Cassandra Intro and Background
⌨️ (21:53) Module 2: Collections, User Defined Types, and Counters
⌨️ (31:29) Module 3: Data Modeling
⌨️ (1:04:22) Module 4: Practical Applications

Get Started with Astra DB, built on Apache Cassandra: https://astra.datastax.com/register/ac250/vi-10

#apache #cassandra #database

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Learn Apache Cassandra Database – Full Course
Dylan  Iqbal

Dylan Iqbal

1658453413

Learn Apache Cassandra Database – Full Course

Apache Cassandra Database – Full Course for Beginners

Apache Cassandra is an open source NoSQL distributed database. This beginner's Cassandra course has four modules. The first three modules will cover the basics Apache Cassandra data modeling. The final module covers practical applications of Cassandra.

⭐️ Course Contents ⭐️
⌨️ (00:30) Module 1: Cassandra Intro and Background
⌨️ (21:53) Module 2: Collections, User Defined Types, and Counters
⌨️ (31:29) Module 3: Data Modeling
⌨️ (1:04:22) Module 4: Practical Applications

Get Started with Astra DB, built on Apache Cassandra: https://astra.datastax.com/register/ac250/vi-10

#apache #cassandra #database

Ruth  Nabimanya

Ruth Nabimanya

1620686100

Top 9 SQL and Database Courses to Learn Online

Hello guys, if you are a computer science graduate or new into the programming world and interested in learning Database and, SQL and looking for some awesome resources — e.g. books, courses, and tutorials — to start with, then you have come to the right place.

In the past, I have shared some of the best SQL books and tutorials, and today, I am going to share some of the best SQL and database courses to learn so you can master this useful technology.

If you don’t know what SQL is and why you should learn it, let me give you a brief overview of SQL for everyone’s benefit. SQL is a programming language to work with a database.

You can use SQL to create database objects — e.g. tables, stored procedure, etc. — and also to store and retrieve data from the database.

The SQL is one of the most important skills for any programmer, irrespective of technology, framework, and domain. It is even more popular than a mainstream programming language like Java and Python, and it definitely adds a lot of value to your CV.

SQL allows you to play with data, which is the most important asset of today’s world. By learning SQL, you can get answers to your questions. For example, if you are a course creator for Udemy, a popular online course platform, and want to know which course is the best seller and which course is not selling at all, you can use SQL.

It can help in troubleshooting as well as reporting. Also, SQL is very stable technology and has been around for years, and it will be needed in the future. This means any investment you make in learning SQL will also serve you for a long time in your career.

5 Best Courses to Learn SQL and Database Online

In the past, I have also shared some free SQL courses, which my readers liked, but the feedback was that they want more comprehensive and in-depth material and that’s why I am coming with this list of best SQL and database courses for both beginners and experienced programmers.

In this list, I have included some of the best SQL and Database courses from Udemy and Pluarlsight, two of the leading places for online courses.

These courses will teach you SQL from the ground up. Most of them don’t even need a pre-requisite as long as you know how to operate a computer and download things from the internet, which you know, and that’s why you are reading this article.

#sql-courses-online #database #database-courses #sqlcourses #database-courses-online

Sival Alethea

Sival Alethea

1624316400

SQL Tutorial - Full Database Course for Beginners. DO NOT MISS!!!

In this course, we’ll be looking at database management basics and SQL using the MySQL RDBMS.
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (2:36) What is a Database?
⌨️ (23:10) Tables & Keys
⌨️ (43:31) SQL Basics
⌨️ (52:26) MySQL Windows Installation
⌨️ (1:01:59) MySQL Mac Installation
⌨️ (1:15:49) Creating Tables
⌨️ (1:31:05) Inserting Data
⌨️ (1:38:17) Constraints
⌨️ (1:48:11) Update & Delete
⌨️ (1:56:11) Basic Queries
⌨️ (2:08:37) Company Database Intro
⌨️ (2:14:05) Creating Company Database
⌨️ (2:30:27 ) More Basic Queries
⌨️ (2:26:24) Functions
⌨️ (2:45:13) Wildcards
⌨️ (2:53:53) Union
⌨️ (3:01:36) Joins
⌨️ (3:11:49) Nested Queries
⌨️ (3:21:52) On Delete
⌨️ (3:30:05) Triggers
⌨️ (3:42:12) ER Diagrams Intro
⌨️ (3:55:53) Designing an ER Diagram
⌨️ (4:08:34) Converting ER Diagrams to Schemas
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=HXV3zeQKqGY&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=8
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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#sql #sql tutorial #full database course for beginners #database management basics #sql using the mysql rdbms #sql tutorial - full database course for beginners

Ananya Gupta

Ananya Gupta

1595485129

Pros and Cons of Machine Learning Language

Amid all the promotion around Big Data, we continue hearing the expression “AI”. In addition to the fact that it offers a profitable vocation, it vows to tackle issues and advantage organizations by making expectations and helping them settle on better choices. In this blog, we will gain proficiency with the Advantages and Disadvantages of Machine Learning. As we will attempt to comprehend where to utilize it and where not to utilize Machine learning.

In this article, we discuss the Pros and Cons of Machine Learning.
Each coin has two faces, each face has its property and highlights. It’s an ideal opportunity to reveal the essence of ML. An extremely integral asset that holds the possibility to reform how things work.

Pros of Machine learning

  1. **Effectively recognizes patterns and examples **

AI can survey enormous volumes of information and find explicit patterns and examples that would not be evident to people. For example, for an online business site like Amazon, it serves to comprehend the perusing practices and buy chronicles of its clients to help oblige the correct items, arrangements, and updates pertinent to them. It utilizes the outcomes to uncover important promotions to them.

**Do you know the Applications of Machine Learning? **

  1. No human mediation required (mechanization)

With ML, you don’t have to keep an eye on the venture at all times. Since it implies enabling machines to learn, it lets them make forecasts and improve the calculations all alone. A typical case of this is hostile to infection programming projects; they figure out how to channel new dangers as they are perceived. ML is additionally acceptable at perceiving spam.

  1. **Constant Improvement **

As ML calculations gain understanding, they continue improving in precision and productivity. This lets them settle on better choices. Let’s assume you have to make a climate figure model. As the measure of information you have continues developing, your calculations figure out how to make increasingly exact expectations quicker.

  1. **Taking care of multi-dimensional and multi-assortment information **

AI calculations are acceptable at taking care of information that is multi-dimensional and multi-assortment, and they can do this in unique or unsure conditions. Key Difference Between Machine Learning and Artificial Intelligence

  1. **Wide Applications **

You could be an e-posterior or a social insurance supplier and make ML work for you. Where it applies, it holds the ability to help convey a considerably more close to home understanding to clients while additionally focusing on the correct clients.

**Cons of Machine Learning **

With every one of those points of interest to its effectiveness and ubiquity, Machine Learning isn’t great. The accompanying components serve to confine it:

1.** Information Acquisition**

AI requires monstrous informational indexes to prepare on, and these ought to be comprehensive/fair-minded, and of good quality. There can likewise be times where they should trust that new information will be created.

  1. **Time and Resources **

ML needs sufficient opportunity to allow the calculations to learn and grow enough to satisfy their motivation with a lot of precision and pertinence. It additionally needs monstrous assets to work. This can mean extra necessities of PC power for you.
**
Likewise, see the eventual fate of Machine Learning **

  1. **Understanding of Results **

Another significant test is the capacity to precisely decipher results produced by the calculations. You should likewise cautiously pick the calculations for your motivation.

  1. High mistake weakness

AI is self-governing yet exceptionally powerless to mistakes. Assume you train a calculation with informational indexes sufficiently little to not be comprehensive. You end up with one-sided expectations originating from a one-sided preparing set. This prompts unessential promotions being shown to clients. On account of ML, such botches can set off a chain of mistakes that can go undetected for extensive periods. What’s more, when they do get saw, it takes very some effort to perceive the wellspring of the issue, and significantly longer to address it.

**Conclusion: **

Subsequently, we have considered the Pros and Cons of Machine Learning. Likewise, this blog causes a person to comprehend why one needs to pick AI. While Machine Learning can be unimaginably ground-breaking when utilized in the correct manners and in the correct spots (where gigantic preparing informational indexes are accessible), it unquestionably isn’t for everybody. You may likewise prefer to peruse Deep Learning Vs Machine Learning.

#machine learning online training #machine learning online course #machine learning course #machine learning certification course #machine learning training

Ruth  Nabimanya

Ruth Nabimanya

1620633584

System Databases in SQL Server

Introduction

In SSMS, we many of may noticed System Databases under the Database Folder. But how many of us knows its purpose?. In this article lets discuss about the System Databases in SQL Server.

System Database

Fig. 1 System Databases

There are five system databases, these databases are created while installing SQL Server.

  • Master
  • Model
  • MSDB
  • Tempdb
  • Resource
Master
  • This database contains all the System level Information in SQL Server. The Information in form of Meta data.
  • Because of this master database, we are able to access the SQL Server (On premise SQL Server)
Model
  • This database is used as a template for new databases.
  • Whenever a new database is created, initially a copy of model database is what created as new database.
MSDB
  • This database is where a service called SQL Server Agent stores its data.
  • SQL server Agent is in charge of automation, which includes entities such as jobs, schedules, and alerts.
TempDB
  • The Tempdb is where SQL Server stores temporary data such as work tables, sort space, row versioning information and etc.
  • User can create their own version of temporary tables and those are stored in Tempdb.
  • But this database is destroyed and recreated every time when we restart the instance of SQL Server.
Resource
  • The resource database is a hidden, read only database that holds the definitions of all system objects.
  • When we query system object in a database, they appear to reside in the sys schema of the local database, but in actually their definitions reside in the resource db.

#sql server #master system database #model system database #msdb system database #sql server system databases #ssms #system database #system databases in sql server #tempdb system database