09-09-2024, 05:54 PM
[center]![[Image: a344af6115c64d6dc89d179fc9e3e3ea.jpg]](https://i124.fastpic.org/big/2024/0908/ea/a344af6115c64d6dc89d179fc9e3e3ea.jpg)
Data Sciense And Ml (sql - Python - Tableau) For Integration
Published 9/2024
Created by Hazem Borham
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 53 Lectures ( 4h 16m ) | Size: 2.1 GB
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[center]
How to combine the three most important tools in data science: Python, SQL, and Tableau
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What you'll learn:
How to use Python, SQL, and Tableau together
Connect Python and SQL to transfer data from Jupyter to Workbench
Apply machine learning
Analysis and interpretation of the exercise outputs in Jupyter and Tableau
Software integration
Create a module for later use of the ML model
Requirements:
Python (Basic)
SQL (Basic)
Tableau (Basic)
Description:
Python, SQL, and Tableau are three of the most essential tools in the data science and business intelligence landscape.Python is the leading programming language, known for its versatility and powerful libraries.SQL is the universal language for communicating with and managing database systems.Tableau is the go-to platform for creating compelling data visualizations.To break it down: SQL helps store and manipulate data, Python enables complex calculations and coding, and Tableau transforms raw data into visually appealing insights. When these three tools are integrated seamlessly, businesses can save millions of dollars annually by automating reporting and analysis tasks.It's no surprise that employers frequently seek candidates skilled in Python, SQL, and Tableau for Data Scientist and Business Intelligence Analyst roles. However, they're not just looking for proficiency in each tool individually-they need professionals who can integrate these tools effectively to automate recurring data analysis tasks.In this course, we'll teach you how to do just that: integrate Python, SQL, and Tableau to create powerful, automated solutions. Mastering this skill will give you a significant advantage in the job market. Unlike many other courses, this one covers a topic that's rarely addressed-meaning you'll acquire a unique skill set that truly differentiates your profile.While many people have a basic understanding of Python, and others might use SQL and Tableau to some extent, few have the expertise to integrate all three and deliver a comprehensive solution. As more businesses move towards automating their reporting and analysis, the ability to implement these techniques will become increasingly valuable-whether you're working within a corporation or as a consultant.Our experience with a major global company has shown that consultants with these skills can command a four-figure hourly rate. And companies are more than willing to pay for this expertise because the long-term efficiencies and insights gained are invaluable.This course begins by introducing the concept of software integration. You'll learn key terms such as servers, clients, requests, and responses, along with data connectivity, APIs, and endpoints.Next, we'll dive into a real-life exercise centered around the 'Absenteeism at Work' dataset. The preprocessing phase will give you a realistic glimpse into the day-to-day work of a BI professional or data scientist-a crucial experience, as preprocessing often constitutes a significant portion of a data scientist's work.Following that, you'll apply Machine Learning techniques to the dataset. You'll learn how to frame the problem from a machine learning perspective, create targets, perform necessary statistical preprocessing, train a model, and evaluate its performance. This is a thorough and practical introduction to machine learning.We'll also cover how to connect Python with SQL-a task that requires careful attention and skill. By the end of this section, you'll know how to transfer data seamlessly between Jupyter and Workbench.Finally, we'll use Tableau to visualize the processed data, creating insightful charts and interpreting the results together.This is a comprehensive and practical data science course that equips you with invaluable skills to stand out in the competitive job market. With our 30-day unconditional money-back guarantee, there's no risk-only the opportunity to significantly boost your career.Don't wait-start now and gain the skills that will make you a standout candidate. Your only regret will be not discovering this course sooner!
Who this course is for:
Individuals interested in a career in Business Intelligence and Data Science
Homepage
Screenshots
Data Sciense And Ml (sql - Python - Tableau) For Integration
Published 9/2024
Created by Hazem Borham
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 53 Lectures ( 4h 16m ) | Size: 2.1 GB
[/center]
[center]
How to combine the three most important tools in data science: Python, SQL, and Tableau
[/center]
What you'll learn:
How to use Python, SQL, and Tableau together
Connect Python and SQL to transfer data from Jupyter to Workbench
Apply machine learning
Analysis and interpretation of the exercise outputs in Jupyter and Tableau
Software integration
Create a module for later use of the ML model
Requirements:
Python (Basic)
SQL (Basic)
Tableau (Basic)
Description:
Python, SQL, and Tableau are three of the most essential tools in the data science and business intelligence landscape.Python is the leading programming language, known for its versatility and powerful libraries.SQL is the universal language for communicating with and managing database systems.Tableau is the go-to platform for creating compelling data visualizations.To break it down: SQL helps store and manipulate data, Python enables complex calculations and coding, and Tableau transforms raw data into visually appealing insights. When these three tools are integrated seamlessly, businesses can save millions of dollars annually by automating reporting and analysis tasks.It's no surprise that employers frequently seek candidates skilled in Python, SQL, and Tableau for Data Scientist and Business Intelligence Analyst roles. However, they're not just looking for proficiency in each tool individually-they need professionals who can integrate these tools effectively to automate recurring data analysis tasks.In this course, we'll teach you how to do just that: integrate Python, SQL, and Tableau to create powerful, automated solutions. Mastering this skill will give you a significant advantage in the job market. Unlike many other courses, this one covers a topic that's rarely addressed-meaning you'll acquire a unique skill set that truly differentiates your profile.While many people have a basic understanding of Python, and others might use SQL and Tableau to some extent, few have the expertise to integrate all three and deliver a comprehensive solution. As more businesses move towards automating their reporting and analysis, the ability to implement these techniques will become increasingly valuable-whether you're working within a corporation or as a consultant.Our experience with a major global company has shown that consultants with these skills can command a four-figure hourly rate. And companies are more than willing to pay for this expertise because the long-term efficiencies and insights gained are invaluable.This course begins by introducing the concept of software integration. You'll learn key terms such as servers, clients, requests, and responses, along with data connectivity, APIs, and endpoints.Next, we'll dive into a real-life exercise centered around the 'Absenteeism at Work' dataset. The preprocessing phase will give you a realistic glimpse into the day-to-day work of a BI professional or data scientist-a crucial experience, as preprocessing often constitutes a significant portion of a data scientist's work.Following that, you'll apply Machine Learning techniques to the dataset. You'll learn how to frame the problem from a machine learning perspective, create targets, perform necessary statistical preprocessing, train a model, and evaluate its performance. This is a thorough and practical introduction to machine learning.We'll also cover how to connect Python with SQL-a task that requires careful attention and skill. By the end of this section, you'll know how to transfer data seamlessly between Jupyter and Workbench.Finally, we'll use Tableau to visualize the processed data, creating insightful charts and interpreting the results together.This is a comprehensive and practical data science course that equips you with invaluable skills to stand out in the competitive job market. With our 30-day unconditional money-back guarantee, there's no risk-only the opportunity to significantly boost your career.Don't wait-start now and gain the skills that will make you a standout candidate. Your only regret will be not discovering this course sooner!
Who this course is for:
Individuals interested in a career in Business Intelligence and Data Science
Homepage
Code:
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