Data Analyst Bootcamp 2024: Get Ready to Be a Data Analyst.

Become a Data Analysis Hero - Learn Python & SQL for Data Analysis and Data Science with Examples, Challenges & Projects

Created by : Rated :4.8 665 views

Last Updated: 2023-12-15 08:12:59 English Course Type: Self Learning

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?

Section 1 : Python Introduction 4 Lectures 00:00:00
Lecture 1 :
Introduction Preview
Lecture 2 :
Environment Preparing for Python
Lecture 3 :
Python2 VS Python3
Lecture 4 :
Understanding Data Types in Python
Section 2 : Python Basics 7 Lectures 00:00:00
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 00:00:00
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 00:00:00
Lecture 1 :
Project Walk through
Lecture 2 :
Project Helpful Notes
Lecture 3 :
Project Solution
Section 5 : Project 2 in Python 4 Lectures 00:00:00
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 00:00:00
Lecture 1 :
Project Walk Through
Lecture 2 :
Project Helpful Notes
Lecture 3 :
Project Solution
Section 7 : Project 4: Twiter Chat Bot 3 Lectures 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
Lecture 1 :
Introduction
Lecture 2 :
PostgreSQL Downloading & Installing
Lecture 3 :
Creating Database
Lecture 4 :
Restoring Database
Section 11 : Airlines Database Overview 3 Lectures 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
Lecture 1 :
CASE Clause
Lecture 2 :
NULLIF()
Lecture 3 :
COALESCE() Function in SQL
Section 17 : SQL Time Data Management 4 Lectures 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
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 00:00:00
Lecture 1 :
Data Visualization of the Scraped Data.
Section 27 : Project 7 Saving the Scraped data to a newly created Database 1 Lectures 00:00:00
Lecture 1 :
Save The Scraped Data to a newly created Database
Section 28 : Project 8 Google Play Store Data Analysis 6 Lectures 00:00:00
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 00:00:00
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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Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic.
Can i play & pause the course as per my convenience?
Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
How do i contact the instructor for any doubts or questions?
Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
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Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly.
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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!