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Programming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books (@programming_guide) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 56 097 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 379-o'rinni va Hindiston mintaqasida 6 302-o'rinni egallagan.
๐ Auditoriya koโrsatkichlari va dinamika
ะฝะตะฒัะดะพะผะพ sanasidan buyon loyiha tez oโsib, 56 097 obunachiga ega boโldi.
23 Iyun, 2026 dagi oxirgi maโlumotlarga koโra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 63 ga, soโnggi 24 soatda esa -15 ga oโzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oโrtacha 2.11% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.49% ini tashkil etuvchi reaksiyalarni toโplaydi.
- Post qamrovi: Har bir post oโrtacha 1 182 marta koโriladi; birinchi sutkada odatda 273 ta koโrish yigโiladi.
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๐ Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโriflaydi:
โEverything about programming for beginners
* Python programming
* Java programming
* App development
* Machine Learning
* Data Science
Managed by: @love_dataโ
Yuqori yangilanish chastotasi (oxirgi maโlumot 24 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโsir nuqtasiga aylantirishini koโrsatadi.
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| 4 | Quick Python Cheat Sheet for Beginners ๐โ๏ธ
Python is widely used for data analysis, automation, and AIโperfect for beginners starting their coding journey.
Aggregation Functions ๐
โข sum(list) โ Adds all values
๐ sum([1,2,3]) = 6
โข len(list) โ Counts total elements
๐ len([1,2,3]) = 3
โข max(list) โ Highest value
๐ max([4,7,2]) = 7
โข min(list) โ Lowest value
๐ min([4,7,2]) = 2
โข sum(list)/len(list) โ Average
๐ sum([10,20])/2 = 15
Lookup / Searching ๐
โข in โ Check existence
๐ 5 in [1,2,5] = True
โข list.index(value) โ Position of value
๐ [10,20,30].index(20) = 1
โข Dictionary lookup
๐ data = {"name": "John", "age": 25} data["name"] # John
Logical Operations ๐ง
โข if condition: โ Decision making
๐ if x > 10: print("High") else: print("Low")
โข and โ All conditions true
โข or โ Any condition true
โข not โ Reverse condition
Text (String) Functions ๐ค
โข len(text) โ Length
๐ len("hello") = 5
โข text.lower() โ Lowercase
โข text.upper() โ Uppercase
โข text.strip() โ Remove spaces
๐ " hi ".strip() = "hi"
โข text.replace(old, new)
๐ "hi".replace("h","H") = "Hi"
โข String concatenation
๐ "Hello " + "World"
Date Time Functions ๐
โข from datetime import datetime
โข datetime.now() โ Current date time
โข Extract values:
now = datetime.now() now.year now.month now.day
Math Functions โ
โข import math
โข math.sqrt(x) โ Square root
โข math.ceil(x) โ Round up
โข math.floor(x) โ Round down
โข abs(x) โ Absolute value
Conditional Aggregation (Like Excel SUMIF) โก
โข Using list comprehension
nums = [10, 20, 30, 40] sum(x for x in nums if x > 20) # 70
โข Count condition
len([x for x in nums if x > 20]) # 2
Pro Tip for Data Analysts ๐ก
๐ For real-world work, use libraries: pandas & numpy
Example:
import pandas as pd df["salary"].mean()
Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
Double Tap โฅ๏ธ For More | 557 |
| 5 |  ๐ฃ๐ฎ๐ ๐๐ณ๐๐ฒ๐ฟ ๐ฃ๐น๐ฎ๐ฐ๐ฒ๐บ๐ฒ๐ป๐ - ๐๐๐น๐น๐๐๐ฎ๐ฐ๐ธ๐๐ฒ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐ช๐ถ๐๐ต ๐๐ฒ๐ป๐๐ ๐
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| 6 | ๐ 9. SQL Joins
Joins combine data from multiple tables. This is one of the most important SQL concepts.
Types of Joins:
โ INNER JOIN
โ LEFT JOIN
โ RIGHT JOIN
โ FULL JOINย
Example
SELECT Customers.Name, Orders.Order_IDย
FROM Customersย
INNER JOIN Ordersย
ON Customers.Customer_ID = Orders.Customer_ID;
โก 10. Query Optimization
As databases grow, performance becomes important.
Imagine: 100 Records = Fast, 10 Million Records = Slow
Optimization helps retrieve data efficiently.ย
Common Optimization Techniques:
โ Indexing
โ Proper Joins
โ Filtering Early
โ Avoiding Unnecessary Queriesย
๐ Databases Every Developer Should Know
๐ฌ MySQL
Best for: Beginners, Web Applications, Small to Medium Projects
Official Site: MySQL
๐ PostgreSQL
Best for: Enterprise Applications, Analytics, Complex Systems
Official Site: PostgreSQL
๐ MongoDB
Best for: Flexible Data Storage, Modern Applications, NoSQL Projects
Official Site: MongoDB
๐ Beginner Database Projects
Build these projects to strengthen your skills:
โ Student Management System
โ Library Management System
โ Inventory Tracker
โ Expense Tracker
โ Employee Database System
โ E-commerce Databaseย
โ ๏ธ Common Beginner Mistakes
โ Skipping SQL fundamentals
โ Learning NoSQL before SQL
โ Ignoring database design
โ Not practicing joins
โ Memorizing queries without understandingย
๐บ๏ธ Database Learning Roadmap
Week 1 โ Tables, Rows & Columns, CRUD Operations
Week 2 โ Filtering, Sorting, Aggregations
Week 3 โ Joins, Relationships, Primary & Foreign Keys
Week 4 โ Indexes, Optimization, Database Designย
๐ก Why Databases Matter
Almost every software application relies on databases.
Whether you're becoming:
โ Web Developer
โ Data Analyst
โ Data Scientist
โ Backend Engineer
โ AI Engineer
Database skills are essential.ย
๐ Double Tap โค๏ธ For More | 498 |
| 7 | ๐ Learn Databases ๐๏ธ๐พ
Every application stores data.
Think about:
โ Instagram storing user profiles
โ Amazon storing product information
โ Netflix storing movies and subscriptions
โ Banking applications storing transactions
Where is all this data stored?
๐ In Databases
If programming is the brain of an application, then databases are its memory ๐ง ๐พ
๐ง 1. What is a Database?
A Database is an organized collection of data that can be stored, managed, and retrieved efficiently.
Without databases:
โ Data would be lost after closing the application
โ Searching information would be difficult
โ Large applications would be impossible to build
๐ Real-World Examples
Banking System Stores:
โ Customer Information
โ Account Details
โ Transaction History
โ Loan Information
E-Commerce Website Stores:
โ Products
โ Orders
โ Customers
โ Payments
Social Media Platform Stores:
โ Users
โ Posts
โ Comments
โ Messages
๐ 2. Types of Databases
There are two major categories:
๐๏ธ Relational Databases SQL
Data is stored in tables.
Example:
ID Name Age
1 John 25
2 Sarah 30
Popular SQL Databases:
โ MySQL
โ PostgreSQL
โ Microsoft SQL Server
๐ NoSQL Databases
Data is stored in flexible formats.
Example:
{
"name": "John",
"age": 25
}
Popular NoSQL Databases:
โ MongoDB
โ Redis
๐ง 3. Why Learn SQL?
SQL Structured Query Language is used to communicate with databases.
It is one of the most important skills for:
โ Developers
โ Data Analysts
โ Data Scientists
โ Backend Engineers
โ Database Administrators
Many companies ask SQL questions in interviews.
๐ 4. CRUD Operations
CRUD stands for:
Operation Meaning
Create Insert Data
Read Retrieve Data
Update Modify Data
Delete Remove Data
These are the most fundamental database operations.
โ CREATE Insert Data
Example:
INSERT INTO Students VALUES (1, 'John', 22);
Adds a new record.
๐ READ Retrieve Data
Example:
SELECT _ FROM Students;
Displays all records.
โ๏ธ UPDATE Modify Data
Example:
UPDATE Students SET Age = 23 WHERE ID = 1;
Updates existing information.
โ DELETE Remove Data
Example:
DELETE FROM Students WHERE ID = 1;
Removes a record.
๐ 5. Database Tables
Databases organize information using tables.
Example: Employees Table
Employee_ID Name Department
101 Rahul IT
102 Priya HR
103 Amit Finance
Each row is a record. Each column represents an attribute.
๐ 6. Primary Keys
A Primary Key uniquely identifies each row.
Example:
ID Name
1 Rahul
2 Priya
ID acts as the Primary Key.
Rules:
โ Unique
โ Cannot be NULL
๐ 7. Relationships Between Tables
Large databases contain multiple tables. These tables are connected using relationships.
Example
Customers Table
Customer_ID Name
1 Rahul
Orders Table
Order_ID Customer_ID
101 1
Customer_ID connects both tables.
๐ 8. SQL Queries Every Beginner Must Learn
Select Data
SELECT _ FROM Employees;
Filter Data
SELECT _ FROM Employees WHERE Department = 'IT';
Sort Data
SELECT _ FROM Employees ORDER BY Salary DESC;
Count Records
SELECT COUNT(_) FROM Employees;
Group Data
SELECT Department, COUNT(_) FROM Employees GROUP BY Department; | 346 |
| 8 |  ๐๐ฐ๐ฐ๐ฒ๐ป๐๐๐ฟ๐ฒ ๐๐ฅ๐๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ ๐ณ๐ผ๐ฟ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ถ๐๐ต ๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ฒ ๐
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| 9 | COMMON TERMINOLOGIES IN PYTHON - PART 1
Have you ever gotten into a discussion with a programmer before? Did you find some of the Terminologies mentioned strange or you didn't fully understand them?
In this series, we would be looking at the common Terminologies in python.
It is important to know these Terminologies to be able to professionally/properly explain your codes to people and/or to be able to understand what people say in an instant when these codes are mentioned. Below are a few:
IDLE (Integrated Development and Learning Environment) - this is an environment that allows you to easily write Python code. IDLE can be used to execute a single statements and create, modify, and execute Python scripts.
Python Shell - This is the interactive environment that allows you to type in python code and execute them immediately
System Python - This is the version of python that comes with your operating system
Prompt - usually represented by the symbol ">>>" and it simply means that python is waiting for you to give it some instructions
REPL (Read-Evaluate-Print-Loop) - this refers to the sequence of events in your interactive window in form of a loop (python reads the code inputted>the code is evaluated>output is printed)
Argument - this is a value that is passed to a function when called eg print("Hello World")... "Hello World" is the argument that is being passed.
Function - this is a code that takes some input, known as arguments, processes that input and produces an output called a return value. E.g print("Hello World")... print is the function
Return Value - this is the value that a function returns to the calling script or function when it completes its task (in other words, Output). E.g.
>>> print("Hello World")
Hello World
Where Hello World is your return value.
Note: A return value can be any of these variable types: handle, integer, object, or string
Script - This is a file where you store your python code in a text file and execute all of the code with a single command
Script files - this is a file containing a group of python scripts | 442 |
| 10 |  ๐ ๐ง๐ผ๐ฝ ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ฌ๐ผ๐ ๐๐ฎ๐ป ๐๐ฒ๐ฎ๐ฟ๐ป ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐! ๐ผ๐ฅ
These free courses can help you build in-demand tech skills for 2026 ๐
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| 11 | โ
Web development Interview Questions with Answers: Part-1
QUESTION 1
What happens step by step when you enter a URL in a browser and press Enter?
Answer
You trigger a long chain of events.
โข Browser parses the URL and identifies protocol, domain, path
โข Browser checks cache, DNS cache, OS cache, router cache
โข If not found, DNS lookup happens to get the IP address
โข Browser opens a TCP connection with the server
โข HTTPS triggers TLS handshake for encryption
โข Browser sends an HTTP request to the server
โข Server processes request and sends HTTP response
โข Browser downloads HTML, CSS, JS, images
โข HTML parsed into DOM
โข CSS parsed into CSSOM
โข DOM + CSSOM create render tree
โข Layout calculates positions
โข Paint draws pixels on screen
โข JavaScript executes and updates UI
Interview tip
Mention DNS, TCP, TLS, render tree. This separates juniors from seniors.
QUESTION 2
What are the roles of HTML, CSS, and JavaScript in a web application?
Answer
Each layer has a single responsibility.
HTML
โข Structure of the page
โข Content and meaning
โข Headings, forms, inputs, buttons
CSS
โข Presentation and layout
โข Colors, fonts, spacing
โข Responsive behavior
JavaScript
โข Behavior and logic
โข Events, API calls, validation
โข Dynamic updates
Real example
HTML builds a login form
CSS styles it
JavaScript validates input and sends API request
QUESTION 3
What are the main differences between HTML and HTML5?
Answer
HTML5 added native capabilities.
Key differences
โข Semantic tags like header, footer, article
โข Audio and video support without plugins
โข Canvas and SVG for graphics
โข Local storage and session storage
QUESTION 4
What is the difference between block-level and inline elements in HTML?
Answer
Block elements
โข Start on a new line
โข Take full width
โข Respect height and width
โข Examples: div, p, h1
Inline elements
โข Stay in same line
โข Take only content width
โข Height and width ignored
โข Examples: span, a, strong
Inline-block
โข Stays inline
โข Respects height and width
QUESTION 5
What is semantic HTML and why is it important for SEO and accessibility?
Answer
Semantic HTML uses meaningful tags.
Examples
โข header, nav, main, article, section, footer
Benefits
โข Search engines understand content better
โข Screen readers read pages correctly
โข Code becomes readable and maintainable
SEO example
article tag signals main content to search engines.
Accessibility example
Screen readers jump between landmarks.
QUESTION 6
What are meta tags and how do they impact search engines?
Answer
Meta tags provide page metadata.
Common meta tags
โข charset defines encoding
โข viewport controls responsiveness
โข description influences search snippets
โข robots control indexing
SEO impact
โข Description affects click-through rate
โข Robots tag controls indexing behavior
Note: Meta keywords are ignored by modern search engines.
QUESTION 7
What is the difference between class and id attributes in HTML?
Answer
ID
โข Unique
โข Used once per page
โข High CSS specificity
โข Used for anchors and JS targeting
Class
โข Reusable
โข Applied to multiple elements
โข Preferred for styling
QUESTION 8
What is a DOCTYPE declaration and why is it required?
Answer
DOCTYPE tells the browser how to render the page.
Without DOCTYPE
โข Browser enters quirks mode
โข Layout breaks
โข Inconsistent behavior
With DOCTYPE
โข Standards mode
โข Predictable rendering
QUESTION 9
How do HTML forms work and what are common input types?
Answer
Forms collect and send user data.
Process
โข User fills inputs
โข Submit triggers request
โข Data sent via GET or POST
Common input types
โข text, email, password
โข number, date
โข radio, checkbox
โข file
Security note
Always validate on server side.
QUESTION 10
What is web accessibility and what are ARIA roles used for?
Answer
Accessibility ensures usable web apps for everyone.
Who benefits
โข Screen reader users
โข Keyboard users
โข Users with visual or motor impairments
ARIA roles
โข Add meaning when native HTML falls short
โข role, aria-label, aria-hidden
Rule
Use semantic HTML first. Use ARIA only when needed.
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| 13 | Here's a short roadmap to crack an IT job with a non-CS background ๐
1. ๐ Learn basics of CS and programming.
2. ๐ฏ Choose a specialization (e.g., web dev, data analysis).
3. ๐ Complete online courses and certifications.
4. ๐ ๏ธ Build a portfolio of projects.
5. ๐ค Network with professionals.
6. ๐ผ Seek internships for experience.
7. ๐ Keep learning and stay updated.
8. ๐ง Develop soft skills.
9. ๐ Prepare for interviews.
10. ๐ช Stay persistent and positive! Good luck!
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| 14 |  ๐ ๐๐ถ๐๐ฐ๐ผ ๐๐ฅ๐๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป | ๐๐ป๐ฟ๐ผ๐น๐น ๐ก๐ผ๐! ๐
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| 15 | โ
SQL Roadmap: Step-by-Step Guide to Master SQL ๐ง ๐ป
Whether you're aiming to be a backend dev, data analyst, or full-time SQL pro โ this roadmap has got you covered ๐
๐ 1. SQL Basics
โฆย SELECT, FROM, WHERE
โฆย ORDER BY, LIMIT, DISTINCTย
ย ย Learn data retrieval & filtering.
๐ 2. Joins Mastery
โฆย INNER JOIN, LEFT/RIGHT/FULL OUTER JOIN
โฆย SELF JOIN, CROSS JOINย
ย ย Master table relationships.
๐ 3. Aggregate Functions
โฆย COUNT(), SUM(), AVG(), MIN(), MAX()ย
ย ย Key for reporting & analytics.
๐ 4. Grouping Data
โฆย GROUP BY to group
โฆย HAVING to filter groupsย
ย ย Example: Sales by region, top categories.
๐ 5. Subqueries & Nested Queries
โฆย Use subqueries in WHERE, FROM, SELECT
โฆย Use EXISTS, IN, ANY, ALLย
ย ย Build complex logic without extra joins.
๐ 6. Data Modification
โฆย INSERT INTO, UPDATE, DELETE
โฆย MERGE (advanced)ย
ย ย Safely change dataset content.
๐ 7. Database Design Concepts
โฆย Normalization (1NF to 3NF)
โฆย Primary, Foreign, Unique Keysย
ย ย Design scalable, clean DBs.
๐ 8. Indexing & Query Optimization
โฆย Speed queries with indexes
โฆย Use EXPLAIN, ANALYZE to tuneย
ย ย Vital for big data/enterprise work.
๐ 9. Stored Procedures & Functions
โฆย Reusable logic, control flow (IF, CASE, LOOP)ย
ย ย Backend logic inside the DB.
๐ 10. Transactions & Locks
โฆย ACID properties
โฆย BEGIN, COMMIT, ROLLBACK
โฆย Lock types (SHARED, EXCLUSIVE)ย
ย ย Prevent data corruption in concurrency.
๐ 11. Views & Triggers
โฆย CREATE VIEW for abstraction
โฆย TRIGGERS auto-run SQL on eventsย
ย ย Automate & maintain logic.
๐ 12. Backup & Restore
โฆย Backup/restore with tools (mysqldump, pg_dump)ย
ย ย Keep your data safe.
๐ 13. NoSQL Basics (Optional)
โฆย Learn MongoDB, Redis basics
โฆย Understand where SQL ends & NoSQL begins.
๐ 14. Real Projects & Practice
โฆย Build projects: Employee DB, Sales Dashboard, Blogging System
โฆย Practice on LeetCode, StrataScratch, HackerRank
๐ 15. Apply for SQL Dev Roles
โฆย Tailor resume with projects & optimization skills
โฆย Prepare for interviews with SQL challenges
โฆย Know common business use cases
๐ก Pro Tip: Combine SQL with Python or Excel to boost your data career options.
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| 18 | โ
Web Development Mistakes Beginners Should Avoid โ ๏ธ๐ป
1๏ธโฃ Skipping the Basics
โข You rush to frameworks
โข You ignore HTML semantics
โข You struggle with CSS layouts later
โ
Fix this first
2๏ธโฃ Learning Too Many Tools
โข React today, Vue tomorrow
โข No depth in any stack
โ
Pick one frontend and one backend โ Stay consistent
3๏ธโฃ Avoiding JavaScript Fundamentals
โข Weak DOM knowledge
โข Poor async handling
โข Confusion with promises
โ
Master core JavaScript early
4๏ธโฃ Ignoring Git
โข No version history
โข Broken code with no rollback
โข Fear of experiments
โ
Learn Git from day one
5๏ธโฃ Building Without Projects
โข Watching tutorials only
โข No real problem solving
โข Zero confidence in interviews
โ
Build small. Build often
6๏ธโฃ Poor Folder Structure
โข Messy files
โข Hard to debug
โข Hard to scale
โ
Follow simple conventions
7๏ธโฃ No API Understanding
โข Copy-paste fetch code
โข No idea about status codes
โข Weak backend communication
โ
Learn REST and JSON properly
8๏ธโฃ Not Deploying Apps
โข Code stays local
โข No production exposure
โข No live links for resume
โ
Deploy every project
9๏ธโฃ Ignoring Performance
โข Large images
โข Unused JavaScript
โข Slow page loads
โ
Use browser tools to measure
๐ Skipping Debugging Skills
โข Random console logs
โข No breakpoints
โข No network inspection
โ
Learn DevTools seriously
๐ก Avoid these mistakes to double your learning speed.
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| 19 |  ๐๐ฑ ๐๐ฅ๐๐ ๐๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ฎ๐ฌ๐ฎ๐ฒ ๐
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| 20 | Data Analytics Roadmap
|
|-- Fundamentals
|ย ย |-- Mathematics
|ย ย |ย ย |-- Descriptive Statistics
|ย ย |ย ย |-- Inferential Statistics
|ย ย |ย ย |-- Probability Theory
|ย ย |
|ย ย |-- Programming
|ย ย |ย ย |-- Python (Focus on Libraries like Pandas, NumPy)
|ย ย |ย ย |-- R (For Statistical Analysis)
|ย ย |ย ย |-- SQL (For Data Extraction)
|
|-- Data Collection and Storage
|ย ย |-- Data Sources
|ย ย |ย ย |-- APIs
|ย ย |ย ย |-- Web Scraping
|ย ย |ย ย |-- Databases
|ย ย |
|ย ย |-- Data Storage
|ย ย |ย ย |-- Relational Databases (MySQL, PostgreSQL)
|ย ย |ย ย |-- NoSQL Databases (MongoDB, Cassandra)
|ย ย |ย ย |-- Data Lakes and Warehousing (Snowflake, Redshift)
|
|-- Data Cleaning and Preparation
|ย ย |-- Handling Missing Data
|ย ย |-- Data Transformation
|ย ย |-- Data Normalization and Standardization
|ย ย |-- Outlier Detection
|
|-- Exploratory Data Analysis (EDA)
|ย ย |-- Data Visualization Tools
|ย ย |ย ย |-- Matplotlib
|ย ย |ย ย |-- Seaborn
|ย ย |ย ย |-- ggplot2
|ย ย |
|ย ย |-- Identifying Trends and Patterns
|ย ย |-- Correlation Analysis
|
|-- Advanced Analytics
|ย ย |-- Predictive Analytics (Regression, Forecasting)
|ย ย |-- Prescriptive Analytics (Optimization Models)
|ย ย |-- Segmentation (Clustering Techniques)
|ย ย |-- Sentiment Analysis (Text Data)
|
|-- Data Visualization and Reporting
|ย ย |-- Visualization Tools
|ย ย |ย ย |-- Power BI
|ย ย |ย ย |-- Tableau
|ย ย |ย ย |-- Google Data Studio
|ย ย |
|ย ย |-- Dashboard Design
|ย ย |-- Interactive Visualizations
|ย ย |-- Storytelling with Data
|
|-- Business Intelligence (BI)
|ย ย |-- KPI Design and Implementation
|ย ย |-- Decision-Making Frameworks
|ย ย |-- Industry-Specific Use Cases (Finance, Marketing, HR)
|
|-- Big Data Analytics
|ย ย |-- Tools and Frameworks
|ย ย |ย ย |-- Hadoop
|ย ย |ย ย |-- Apache Spark
|ย ย |
|ย ย |-- Real-Time Data Processing
|ย ย |-- Stream Analytics (Kafka, Flink)
|
|-- Domain Knowledge
|ย ย |-- Industry Applications
|ย ย |ย ย |-- E-commerce
|ย ย |ย ย |-- Healthcare
|ย ย |ย ย |-- Supply Chain
|
|-- Ethical Data Usage
|ย ย |-- Data Privacy Regulations (GDPR, CCPA)
|ย ย |-- Bias Mitigation in Analysis
|ย ย |-- Transparency in Reporting
Free Resources to learn Data Analytics skills๐๐
1. SQL
https://mode.com/sql-tutorial/introduction-to-sql
https://t.me/sqlspecialist/738
2. Python
https://www.learnpython.org/
https://t.me/pythondevelopersindia/873
https://bit.ly/3T7y4ta
https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial
3. R
https://datacamp.pxf.io/vPyB4L
4. Data Structures
https://leetcode.com/study-plan/data-structure/
https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513
5. Data Visualization
https://www.freecodecamp.org/learn/data-visualization/
https://t.me/Data_Visual/2
https://www.tableau.com/learn/training/20223
https://www.workout-wednesday.com/power-bi-challenges/
6. Excel
https://excel-practice-online.com/
https://t.me/excel_data
https://www.w3schools.com/EXCEL/index.php
Join @free4unow_backup for more free courses
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