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  • Using Real World PostgreSQL Database Airlines Database.
  • Learn coding in Python by examples.
  • How to Use Python & SQL to Analyze and visualize Data.
  • Use Python to visualize Postgres Data Output and get your Conclusion about Data.
  • Use Python bs4 & Pandas to Scrape a webpage, Analyze and visualize The Scraped Data.
  • Use SQL to perform advanced techniques to retrieve data from databases.
  • Use Python with SQL Postgres database.
  • Use Python to load Postgres Data Output file.

Become a Data Analysis Hero - Learn Python & SQL Programming from Scratch!
 
Discover the career-boosting tools that top companies are looking for. This comprehensive course will give you job-ready skills in Python programming, SQL querying, data analysis, and more.
 
What you'll learn:
 
- Python Programming: Control flow, functions, OOP, pandas, NumPy, data visualization
 
- SQL Databases: PostgreSQL, queries, aggregations, joins, date filtering
 
- Real-World Projects: Analyze datasets, build models, create scripts
 
- Jupyter Notebooks: Practice coding interactively online
 
- Industry Best Practices: Writing efficient code, debugging, commenting
 
 
 
Why Python and SQL?
 
 
 
Python and SQL are essential tools for data analysts and data scientists. This powerful combo allows you to quickly gather, organize, analyze, and visualize data from any source.
 
Python makes data tasks easy with its simplicity and huge ecosystem of data science libraries. SQL enables you to efficiently access data from databases for deeper analysis.
 
These in-demand skills are highly valued by top employers like Google, Facebook, Amazon, and more. With this course, you'll have job-ready data superpowers!
 
Learn from a top-rated instructor with real-world experience. Gain skills to level up your career opportunities and become a data analysis hero!
 
Enroll Now and Get Started! This course is best suited for beginners looking to learn data analysis, as well as intermediate analysts wanting to expand their Python and SQL skills.

  • No primer programming experience needed for this course.
  • Computer and internet.
  • Your enthusiasm to learn Python & SQL For Data Analysis & Data Science.
  • Everything else you need to learn Python Programming is already in this course.
  • Are you want to learn more about SQL, PostgreSQL, or data analysis using Python & SQL?
  • Are you want to learn Python & SQL for data science?
  • Are you ready for upcoming Python & SQL interview questions?
  • Use Python bs4 & Pandas to Scrape a webpage, Analyze and visualize The Scraped Data.
  • Are you welling to learn Python Pandas & Data Visualization?
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  • Section 1 : Python Introduction 4 Lectures

    • Lecture 1 :
    • Lecture 2 :
    • Environment Preparing for Python
    • Lecture 3 :
    • Python2 VS Python3
    • Lecture 4 :
    • Understanding Data Types in Python
  • Section 2 : Python Basics 7 Lectures

    • Lecture 1 :
    • Variables, Operators and Data Types in Python
    • Lecture 2 :
    • String Functions in Python
    • Lecture 3 :
    • Data Structures in Python
    • Lecture 4 :
    • Control Flow VS Loops
    • Lecture 5 :
    • Error Handling in Python
    • Lecture 6 :
    • Functions in Python
    • Lecture 7 :
    • Files and Modules in Python
  • Section 3 : OOP in Python 9 Lectures

    • Lecture 1 :
    • Creating Simple Class.
    • Lecture 2 :
    • Overviewing Constructor.
    • Lecture 3 :
    • Learning How to creating Dunder Methods?
    • Lecture 4 :
    • Learning about Inheritance.
    • Lecture 5 :
    • Knowing What is the Encapsulation?
    • Lecture 6 :
    • Learning also about Multiple Inheritance
    • Lecture 7 :
    • Knowing What is the Overriding?
    • Lecture 8 :
    • Learning about Decorators.
    • Lecture 9 :
    • Learning How to use Build in Decorators?
  • Section 4 : Project 1 in Python 3 Lectures

    • Lecture 1 :
    • Project Walk through
    • Lecture 2 :
    • Project Helpful Notes
    • Lecture 3 :
    • Project Solution
  • Section 5 : Project 2 in Python 4 Lectures

    • Lecture 1 :
    • Project Walk through
    • Lecture 2 :
    • Project Helful Notes
    • Lecture 3 :
    • Project Solution Part 1
    • Lecture 4 :
    • Project Solution Part 2
  • Section 6 : Project 3 in Python 3 Lectures

    • Lecture 1 :
    • Project Walk Through
    • Lecture 2 :
    • Project Helpful Notes
    • Lecture 3 :
    • Project Solution
  • Section 7 : Project 4: Twiter Chat Bot 3 Lectures

    • Lecture 1 :
    • Twiter Chat Bot Part 1
    • Lecture 2 :
    • Twiter Chat Bot Part 2
    • Lecture 3 :
    • Twiter Chat Bot Part 3
  • Section 8 : Project 5: Facebook Chat Bot 4 Lectures

    • Lecture 1 :
    • Python Flask Library Overview
    • Lecture 2 :
    • Facebook Developer App Creating And Downloading Ngrok
    • Lecture 3 :
    • Facebook Chat App & Preset Messaging
    • Lecture 4 :
    • Hooking and Runnig The FB ChatBot App Using Ngrok
  • Section 9 : Numpy Python Library 9 Lectures

    • Lecture 1 :
    • Numpy Intro
    • Lecture 2 :
    • Numpy.shape & Numpy.size
    • Lecture 3 :
    • Creating Numpy nd arrays using Numpy functions
    • Lecture 4 :
    • Numpy.unique( ) & Array slicing.
    • Lecture 5 :
    • Numpy Calculations and Operators.
    • Lecture 6 :
    • Numpy Aggregations.
    • Lecture 7 :
    • Numpy Reshape and Transposing.
    • Lecture 8 :
    • Numpy Comparing.
    • Lecture 9 :
    • Numpy Images processing.
  • Section 10 : SQL Introduction 4 Lectures

    • Lecture 1 :
    • Introduction
    • Lecture 2 :
    • PostgreSQL Downloading & Installing
    • Lecture 3 :
    • Creating Database
    • Lecture 4 :
    • Restoring Database
  • Section 11 : Airlines Database Overview 3 Lectures

    • Lecture 1 :
    • SQL Database Overview Part 1
    • Lecture 2 :
    • SQL Database Overview Part 2
    • Lecture 3 :
    • SQL Data Types
  • Section 12 : SQL Basics Part 1 4 Lectures

    • Lecture 1 :
    • Select Statement
    • Lecture 2 :
    • Select Challenge Solution
    • Lecture 3 :
    • Select Statement For all Airlines Database Tables
    • Lecture 4 :
    • Distinct
  • Section 13 : SQL Basics Part 2 5 Lectures

    • Lecture 1 :
    • Where Clause
    • Lecture 2 :
    • Operators used with Where Clause
    • Lecture 3 :
    • Where Clause + AND & Where Clause + OR
    • Lecture 4 :
    • Where Clause + LIKE
    • Lecture 5 :
    • (Where Clause + BETWEEN & IN) & AS
  • Section 14 : SQL Basics Part 3 5 Lectures

    • Lecture 1 :
    • LIMIT & ORDER BY
    • Lecture 2 :
    • FETCH vs LIMIT
    • Lecture 3 :
    • NOT IN
    • Lecture 4 :
    • ISNULL & IS NOT NULL
    • Lecture 5 :
    • CAST
  • Section 15 : SQL Aggregations 5 Lectures 00:01:08

    • Lecture 1 :
    • COUNT() Function, CREATE TABLE & INSERT INTO TABLE
    • Lecture 2 :
    • SUM() Function
    • Lecture 3 :
    • MIN(), MAX() & AVG() Functions
    • Lecture 4 :
    • GROUP BY & HAVING
    • Lecture 5 :
    • Deep dive in Count
  • Section 16 : SQL Conditional. 3 Lectures

    • Lecture 1 :
    • CASE Clause
    • Lecture 2 :
    • NULLIF()
    • Lecture 3 :
    • COALESCE() Function in SQL
  • Section 17 : SQL Time Data Management 4 Lectures

    • Lecture 1 :
    • Overview of Time Functions in PostgreSQL
    • Lecture 2 :
    • TIMESTAMP EXTRACT()
    • Lecture 3 :
    • DATE_TRUNC() & DATE_PART()
    • Lecture 4 :
    • Double Column + DATE IN PostgreSQL & CURRENT_DATE & now( )
  • Section 18 : Intermediate: SQL Joins 11 Lectures

    • Lecture 1 :
    • INNER JOIN
    • Lecture 2 :
    • Joins Types Overview
    • Lecture 3 :
    • LEFT OUTER JOIN
    • Lecture 4 :
    • Deep understanding of LEFT JOIN
    • Lecture 5 :
    • RIGHT OUTER JOIN
    • Lecture 6 :
    • FULL OUTER JOIN
    • Lecture 7 :
    • CROSS JOIN
    • Lecture 8 :
    • UNION, UNION ALL, INTERSECT & EXCEPT
    • Lecture 9 :
    • SELF JOIN
    • Lecture 10 :
    • USING
    • Lecture 11 :
    • NATURAL JOIN
  • Section 19 : Intermediate: Sub-queries & Common Table Expression in SQL 3 Lectures

    • Lecture 1 :
    • Sub-queries
    • Lecture 2 :
    • SQL Sub-query + EXISTS, ANY OR ALL
    • Lecture 3 :
    • Common Table Expression
  • Section 20 : Advanced: PostgreSQL Math & Window functions. 5 Lectures

    • Lecture 1 :
    • Math Functions
    • Lecture 2 :
    • Window Functions OVER()
    • Lecture 3 :
    • Window Functions RANK() + OVER() & NTILE() + OVER()
    • Lecture 4 :
    • Window Functions OVER() + LEAD()
    • Lecture 5 :
    • Window Functions OVER() + LAG()
  • Section 21 : Advanced: PostgreSQL String Functions 5 Lectures

    • Lecture 1 :
    • PostgreSQL POSITION Function
    • Lecture 2 :
    • STRPOS() & REPLACE() in PostgreSQL
    • Lecture 3 :
    • PostgreSQL LEFT(), RIGHT(), BTRIM() & SPLIT_PART() Functions
    • Lecture 4 :
    • PostgreSQL CONCAT Function
    • Lecture 5 :
    • PostgreSQL LOWER(), UPPER() & INITCAP() Functions
  • Section 22 : Advanced: Other SQL Functions 3 Lectures

    • Lecture 1 :
    • GROUPING SETS(), ROLLUP(), CUBE()
    • Lecture 2 :
    • SELECT Statement + INTO & SELECT Statement + INTO + IN
    • Lecture 3 :
    • VIEW()
  • Section 23 : Data Analysis Process Overview 1 Lectures

    • Lecture 1 :
    • Data Analysis Process Overview
  • Section 24 : Project 6: Using Python Pandas in Data Analysis of PostgreSQL Data output 0 Lectures

  • Section 25 : Project 5 Scraping The Web Using Python 3 Lectures 00:05:03

    • Lecture 1 :
    • How to Scrape a website part 1 ??
    • Lecture 2 :
    • How to Scrape a website part 2 ??
    • Lecture 3 :
    • Using Pandas and LXML Python Modules to scrape a webpage
  • Section 26 : Project 6 Data Analysis _ Data Visualization of the Scraped Data 1 Lectures

    • Lecture 1 :
    • Data Visualization of the Scraped Data.
  • Section 27 : Project 7 Saving the Scraped data to a newly created Database 1 Lectures

    • Lecture 1 :
    • Save The Scraped Data to a newly created Database
  • Section 28 : Project 8 Google Play Store Data Analysis 6 Lectures

    • Lecture 1 :
    • Exploratory Data Analysis (EDA) of Google App Store Data
    • Lecture 2 :
    • Resorces
    • Lecture 3 :
    • Data Visualization Techniques.
    • Lecture 4 :
    • Statistical Analysis and Hypothesis Testing.
    • Lecture 5 :
    • Data Storytelling.
    • Lecture 6 :
    • Conclusion.
  • Section 29 : Project 11: Using Pandas + Automation to Manage a Business Email List 3 Lectures

    • Lecture 1 :
    • Using Pandas + Automation to Manage a Business Email List Part 1
    • Lecture 2 :
    • Using Pandas + Automation to Manage a Business Email List Part 2
    • Lecture 3 :
    • Using Pandas + Automation to Manage a Business Email List Part 3
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Hello there! With over 350,000 happy students enrolled in my courses, I'm thrilled to be sharing my programming and data science expertise with you. As a programmer and data scientist, I've mastered several programming languages, including Python, SQL, JavaScript, R Programming, as well as tools like Excel, Tableau, Jupyter Notebook, Apache Cassandra, Apache Spark, Apache Airflow, Apache Kafka, AWS, and R Studio. I'm passionate about teaching and sharing my knowledge with the community. When I'm not coding, you can usually find me hiking or reading a good book. I believe that lifelong learning is essential for personal development, and my courses are designed to encourage students to continue learning outside of formal education. I update my courses every month to add new sections based on your feedback and requests. So don't wait – enroll in my courses now and start your journey towards mastering programming, web development, data science, data Engineering and Machine Learning!
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