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This video by Simplilearn is based on SQL Tutorial For Beginners. This SQL Full Course 2024 by Simplilearn is designed and curated in collaboration with real-time industry experts with Data analytics knowledge and expertise. This SQL Tutorial for beginners will cover the basics of SQL from the code syntax to all the advanced concepts in SQL like, Sub Queries, Joins, and CTEs in SQL. After completing this course, you can become an expert in SQL Fundamentals or if you are a professional, you can brush up your SQL skills and for beginners, you can proceed with building your personal data analysis portfolio to begin with your training or internship for Real-time operations and job opportunities.

00:00:00 Introduction to SQL Full Course
00:01:08 What is DBMS
00:12:45 Database Vs Data Warehouse
00:31:24 Data Analyst Roadmap
00:33:28 Data Science Vs Data Analyst
00:47:08 What is SQL
03:13:33 SQL Tutorial For Beginners
03:14:22 Business Intelligence Terms For data analyst
03:30:13 Normalization in SQL
03:33:37 Descriptive Analysis Vs Stat
03:51:09 What is ETL
07:16:37 SQL FC
07:30:47 Joining Tables in SQL
07:53:01 Views in SQL
07:55:39 POstgreSQL
09:37:05 SQL CTE(Common Table Expressions
10:40:24 SQL Project for data analysis
11:29:25 EDA(Exploratory Data Analysis) with Python
11:29:35 Data Analytics using Artificial Intelligence
12:02:19 Data Cleaning in Data Mining
12:17:56 Chatgpt and Excel with Data Analytics
12:54:38 SQL Interview Questions and Answers

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What is SQL?
SQL stands from Structured Query Language. It is used to communicate with several relational databases such as MySQL, Oracle and MS SQL Server. Using SQL queries, you can fetch, update, delete and manipulate data that is stored in the form of rows and columns. SQL commands are divided into different types, such as data manipulation language (DML), data definition language (DDL), transaction control language (TCL), and data query language (DQL).

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Boost your career with this Data Analytics Course, in partnership with Purdue University & in collaboration with IBM, which features master classes and follows an applied learning model designed with real-life projects and business case studies.

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- Post Graduate Program certificate and Alumni Association membership
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- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Resume preparation and LinkedIn profile building
- 1:1 mock interview
- Career accelerator webinars

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- Data Analytics
- Statistical Analysis using Excel
- Data Analysis Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
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- Induction Session for Purdue Data Analytics Program
- PG DA - Business Analytics with Excel
- PG DA - SQL
- PG DA - Programming foundation and Data Analytics with Python
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- PG DA - Data Analytics with R
- PG DA - Tableau Training
- PG DA - Data Analytics Capstone
Electives:
- PL-300 Microsoft Power BI Certification Training
- Academic Masterclass by Purdue University Online
- Industry Master Class – Data Analytics
- Generative AI Masterclass

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Summary
If you're new to AI agents, this is the perfect place to start. In just 25 minutes, you'll learn exactly what an AI agent is, how it differs from traditional automations, and how to build one from scratch using n8n — no coding required. We’ll cover the core components of agent systems, how to set up guardrails, how agents interact with APIs, and what kinds of tools they can use. By the end, you'll have a working AI agent that can think, remember, and take action — and a clear understanding of how to build more. This is a hands-on, beginner-friendly guide designed to take you from zero to a working agent with practical, real-world applications.

Chapters
0:00 Intro
0:33 What is an Agent?
0:54 Agents vs. Automations
2:09 3 Main Components
3:29 Types of Systems
4:25 Guardrails
5:05 Resources
6:01 Recap
6:58 APIs and HTTP Requests
9:07 What Can You Build?
9:52 n8n Overview
11:08 Agent Build Overview
12:12 Set Trigger
12:26 AI Agent Node
13:20 Connect the Brain
14:40 Setting up Memory
15:54 Adding Tools
22:48 Testing and Debugging
24:53 Possibilities From Here

Learn how to talk Machine Learning with the best of them. I demystify the magic of deep learning and explain the buzz words