The Employee Factory - Invidious

The Employee Factory

The Employee Factory is described as the world’s first integrated career counseling and learning platform designed to help individuals plan their professional journey and target their "dream companies" and "passive online careers"

The Purpose and Mission
The core purpose of the platform is to bridge the gap between raw talent and the specific requirements of the modern job market. Its mission is defined by several key goals:
• Preparing "Floor Ready" Talent: The platform aims to provide candidates who are immediately ready to handle specific project needs within a corporate environment.
• Solving Indecisiveness: Recognizing that many job seekers feel lost, the platform provides the "right guidance" and professional training needed to boost a career path.
• Saving Time for Recruiters: For "Employee Seekers," the platform offers an untapped pool of professionals, saving them valuable time by vetting and training candidates beforehand.

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6:56

Automated Wealth: Build Passive Income Using AI Systems

The Employee Factory

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5:34

4.9 - Lab: Extracting (Unload) Data from Snowflake to S3 📤🧪

The Employee Factory

Shared 9 months ago

308 views

2:42

4.8 - Snowpipe: Billing Estimation & Key Considerations for Data Ingestion 💰📊

The Employee Factory

Shared 9 months ago

34 views

11:08

4.7 - Lab: Create and Implement Snowpipe in Snowflake 🧪📤

The Employee Factory

Shared 9 months ago

54 views

2:02

4.6 - Introduction to Continuous Data Ingestion in Snowflake 🔄🚀

The Employee Factory

Shared 9 months ago

31 views

11:06

4.5 - Lab: Ingest JSON from S3 to Snowflake 🧪📥

The Employee Factory

Shared 9 months ago

33 views

8:28

004 - Lab: Ingest CSV from S3 to Snowflake 🧪🗂️

The Employee Factory

Shared 9 months ago

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7:56

003 - Lab: Create an Integration Object to Connect Snowflake with AWS S3

The Employee Factory

Shared 11 months ago

104 views

0:45

001 - Section Overview: Snowflake - Data Loading, Ingestion, and Extraction

The Employee Factory

Shared 11 months ago

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4:01

5.2 - Data Ingestion Section Overview: Snowflake - Data Loading, Ingestion, and Extraction

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10:58

4.9 - Snowflake Search Optimization Feature: Improve Query Performance

The Employee Factory

Shared 11 months ago

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6:09

4.6 - Lab: Selecting Your Clustering Keys in Snowflake

The Employee Factory

Shared 11 months ago

160 views

7:44

4.8 - Lab: Query Processing and Caching in Snowflake

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Shared 11 months ago

107 views

0:45

5.1 - Data Ingestion Section Overview: Snowflake - Data Loading, Ingestion, and Extraction

The Employee Factory

Shared 11 months ago

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17:32

4.4 - Lab: Micro-partitions and Clustering Keys in Snowflake

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Shared 11 months ago

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4:37

4.7 - Lab: Check Query Profile and History in Snowflake

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Shared 11 months ago

395 views

9:04

4.5 - Understanding Clustering Depth and Cluster Overlap in Snowflake

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Shared 11 months ago

471 views

5:58

4.3 - Benefits of Micro-partitions and Clustering in Snowflake 🌐

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Shared 11 months ago

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8:40

3.2 - Lab: Create Tables in Snowflake

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4:01

3.3 - Snowflake: Views, Materialized Views, and Secure Views

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Shared 11 months ago

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4:35

3.5 - Lab: Create Secure Views in Snowflake

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5:28

3.4 - Lab: Create Views in Snowflake

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4:16

3.1 - Introduction: Different Types of Tables in Snowflake

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3.6 - More About Views in Snowflake

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7:51

4.2 - Introduction to Partitions and Clustering Keys in Snowflake

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2:13

4.1 - Section Overview: Data Warehousing and Engineering with Snowflake

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4:35

2.9 - Snowflake: Resource Monitors

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5:24

2.8 - Snowflake: Track Your Consumption

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10:00

2.7 - Snowflake: Understanding Different Billing Components

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9:49

2.6 - Snowflake Virtual Warehouses: Powering Scalable Compute

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4:51

2.5 - Snowflake Object Hierarchy: Understanding the Structure

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4:02

2.4 - Snowflake Architecture: A Comprehensive Overview

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Shared 11 months ago

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2:21

2.3 - Lab: Setup Snowflake Trial Account

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Shared 11 months ago

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2:26

2.2 - Two Aspects of a Data Ecosystem

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3:24

2.1 - What is a data warehouse

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2:52

Topic 02 - Prerequisites and How to Succeed in This Course

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2:55

Topic 01: Data Warehousing and Engineering Using Snowflake and AWS Cloud - Course Roadmap

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Shared 11 months ago

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9:40

4.5 Building AI agents with CrewAI with LLMs running locally on your computer

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20:43

4.4 - Setting Up CrewAI: Step-by-Step Guide

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4:15

4.3 - Installation and Setup: Open-Source LLMs (Meta’s LLaMA II)

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6:36

4.2 - Installation and Setup: Python for Crew AI

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5:21

4.1 - Introduction to Crew AI: Building Smarter Workflows

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12:57

3.2 Setting Up Social Media Publishing Agent: AI Agent

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3.3 - Testing and Going Live: AI Agent 1 - Social Media Publishing Agent

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3.1 - AI Agent 1: Social Media Publishing Agent

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11:31

2.5 - Zapier Actions: How to Configure and Use Them

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3:46

2.4 - Zapier Introduction: Configuring AI Agents

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10:55

2.3 - CustomGPTs: How to Create and Use Them

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2.2 - AI Agents vs. Large Language Models: Understanding the Difference

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6:17

2.1 - Automation of Tasks with AI Agents: Introduction to AI Agents

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3:10

1 🤖 AI Agents - Build with ChatGPT, Zapier, CrewAI

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Shared 11 months ago

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13:58

40 ❄️ Creating Standalone and Dependent Trees of Tasks in Snowflake

The Employee Factory

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38 ❄️ Demo: Drop and Undrop Table, Schema, and Database in Snowflake

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39 ❄️ Demo: Clone with Time Travel in Snowflake - Step-by-Step Guide

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37 ❄️ Demo: How to Enable Time Travel in Snowflake

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36 ❄️ Time Travel vs Fail-safe in Snowflake: Understanding the Differences

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35 ❄️ Time Travel in Snowflake: A Comprehensive Guide

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34 ❄️ Creating a Dashboard for a COVID-19 Dataset in Snowsight: Step-by-Step Guide

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33 ❄️ Dashboard Filters in Snowsight: Step-by-Step Guide

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Shared 11 months ago

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32 ❄️ Creating Dashboards Using Snowsight in Snowflake: Step-by-Step Guide

The Employee Factory

Shared 11 months ago

606 views