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Coding Free Books | Python | AI

Coding Free Books | Python | AI

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Best Channel for Programmers and Hackers All in one channel to learn 👇 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun

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📈 Analytical overview of Telegram channel Coding Free Books | Python | AI

Channel Coding Free Books | Python | AI (@codingwithsagar) in the English language segment is an active participant. Currently, the community unites 30 894 subscribers, ranking 6 259 in the Education category and 13 672 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 30 894 subscribers.

According to the latest data from 19 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 156 over the last 30 days and by -11 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.63%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 120 views. Within the first day, a publication typically gains 0 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as learning, link:-, css, algorithm, sql.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
Best Channel for Programmers and Hackers All in one channel to learn 👇 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun

Thanks to the high frequency of updates (latest data received on 20 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

30 894
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+337 days
+15630 days
Posts Archive
𝗧𝗼𝗽 𝟱 𝗙𝗿𝗲𝗲 𝗞𝗮𝗴𝗴𝗹𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗝𝘂𝗺𝗽𝘀𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁�
𝗧𝗼𝗽 𝟱 𝗙𝗿𝗲𝗲 𝗞𝗮𝗴𝗴𝗹𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗝𝘂𝗺𝗽𝘀𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗮𝗿𝗲𝗲𝗿😍 Want to break into Data Science but not sure where to start?🚀 These free Kaggle micro-courses are the perfect launchpad — beginner-friendly, self-paced, and yes, they come with certifications!👨‍🎓🎊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4l164FN No subscription. No hidden fees. Just pure learning from a trusted platform✅️

SQL Roadmap: From Basics to Advanced 1. Basics Learn SQL syntax: SELECT, WHERE, ORDER BY. Understand data types (INT, VARCHAR, DATE). Use operators (=, <>, >, <), logical operators (AND, OR, NOT), and comparison operators. 2. Filtering & Sorting Filter data with WHERE clause. Sort results using ORDER BY. Use wildcards (LIKE, %). 3. Aggregations Apply aggregation functions: COUNT, SUM, AVG, MAX, MIN. Group data with GROUP BY, filter groups with HAVING. 4. Joins Learn different joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN. Understand when to use each join type. 5. Subqueries Use subqueries in SELECT, WHERE, FROM clauses. Differentiate between correlated and non-correlated subqueries. 6. Set Operations Use UNION, INTERSECT, and EXCEPT to combine results. 7. Data Modification Insert data with INSERT INTO. Update data using UPDATE. Delete data with DELETE. 8. Advanced Queries Use CASE for conditional logic. Learn window functions: ROW_NUMBER, RANK, DENSE_RANK. Use CTEs (Common Table Expressions) for modular queries. 9. Indexes & Performance Create and use indexes. Optimize queries by avoiding SELECT * 10. Transactions Use COMMIT, ROLLBACK, and SAVEPOINT. Understand ACID properties. 11. Stored Procedures & Functions Create and execute stored procedures. Define and use functions for reusable logic. 12. Database Design Learn normalization (1NF, 2NF, 3NF). Understand primary/foreign keys and relationships. I've curated essential SQL Interview Resources👇 https://t.me/DataSimplifier Share with credits: https://t.me/sqlspecialist Hope it helps :)

𝟰 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗦𝗤𝗟 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀😍 Want to break into Data Analytic
𝟰 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗦𝗤𝗟 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀😍 Want to break into Data Analytics?💫 It all starts with SQL — the language every data analyst needs to master. Whether you’re analyzing trends, pulling business reports, or cleaning datasets, SQL is at the heart of it all👨‍💻📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/44oj5Ds Perfect for students, freshers, job seekers, or anyone transitioning into tech✅️

⌨️ JavaScript Neat Tricks you should know
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⌨️ JavaScript Neat Tricks you should know

🎮💰 भाइयों! आप गेम खेलते हो, लेकिन क्या आप जानते हो उससे पैसे भी कमाए जा सकते हैं? सिर्फ प्लेयर मत बनो, विनर बनो! हर गेम का अपना "जैकपॉट पैटर्न" होता है — ट्रिक समझो और रोज़ ₹50000 कमाओ! 🔥 आज मैं एक ट्रिक शेयर कर रहा हूँ जो मैंने खुद आज़माई है और काम करती है! ✅ प्लेटफ़ॉर्म: https://tr.ee/OzYJlt 🎰 गेम: Money Coming मैं इसे कई दिन से खेल रहा हूँ — अब मैं रोज़ लाखों कमा रहा हूँ! 💡 स्टेप्स: 1️⃣ ₹100 रिचार्ज करो — तुरंत 20 बोनस मिलेगा 👉 यानी ₹120 से शुरू! 2️⃣ 10 की ₹10 लगातार बेट लगाओ 👉 10वीं बार के बाद जैकपॉट चांस बहुत बढ़ता है! 3️⃣ जीतते ही गेम से बाहर निकलो और फिर से एंटर करो — सिस्टम तुम्हें नए प्लेयर मानेगा और फिर से जीतने का चांस बढ़ेगा! ✅ मैंने ये ट्रिक कई बार टेस्ट की है — रिज़ल्ट जबरदस्त है! 💰 पहली बार मुनाफा होते ही धीरे-धीरे बेट बढ़ाओ — प्रॉफिट 🎁 रोज़ ₹88888 का फ्री लकी ड्रा है — मैं खुद जीत चुका हूँ! 👥 दोस्तों को इनवाइट करो और 100 बोनस पाओ! 📌 लालच मत करो, पहले इन्वेस्ट की गई अमाउंट निकालो फिर बढ़ाओ! 📢अभी Telegram चैनल जॉइन करें और रोज़ाना 99% जीतने वाले सिग्नल पाएं: https://t.me/gujsrk9

Javascript Reduce method Example. ▫️ Finding the longest word in a given string. function longerWord(a, b) { if (a.length > b.length) {     return a;   } else {     return b; } } const sentence = 'Hey there what are you doing this Wednesday night'; const longest = sentence.split(' ').reduce(longerWord); console.log(longest); // Wednesday #JavaScript

𝟳 𝗥𝗲𝗮𝗱𝘆-𝘁𝗼-𝗨𝘀𝗲 𝗘𝗺𝗮𝗶𝗹 𝗙𝗼𝗿𝗺𝗮𝘁𝘀 𝘁𝗼 𝗜𝗺𝗽𝗿𝗲𝘀𝘀 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗲𝗿𝘀😍 📩 Struggling to write the per
𝟳 𝗥𝗲𝗮𝗱𝘆-𝘁𝗼-𝗨𝘀𝗲 𝗘𝗺𝗮𝗶𝗹 𝗙𝗼𝗿𝗺𝗮𝘁𝘀 𝘁𝗼 𝗜𝗺𝗽𝗿𝗲𝘀𝘀 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗲𝗿𝘀😍 📩 Struggling to write the perfect email to a recruiter?🗣 You’re not alone. The way you write your email can make or break your first impression🤝 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3TtQh64 Having the right email format makes all the difference✅️

+4
Ansible Michael Heap, 2016

𝟰 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗞𝗶𝗰𝗸𝘀𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗝𝗼𝘂𝗿𝗻𝗲𝘆 — 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿-𝗙𝗿𝗶�
𝟰 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗞𝗶𝗰𝗸𝘀𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗝𝗼𝘂𝗿𝗻𝗲𝘆 — 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿-𝗙𝗿𝗶𝗲𝗻𝗱𝗹𝘆 & 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱!😍 Ready to kickstart your career in Data Science—without spending a rupee?💰 These 4 beginner-friendly courses will help you build a strong foundation in data science by teaching you how to gather, clean, analyse, and visualise data📊📌 𝗔𝗽𝗽𝗹𝘆 𝗟𝗶𝗻𝗸𝘀:-👇 https://pdlink.in/45uXCtI An initiative supported by NASSCOM and the Government of India✅️

⌨️ Learn About Python List Methods
⌨️ Learn About Python List Methods

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Essential Math for AI Hala Nelson, 2022

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𝗧𝗼𝗽 𝗧𝗲𝗰𝗵 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 - 𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗡𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄😍 𝗦𝗤𝗟:- https://pdlink.in/3SMHxaZ 𝗣𝘆𝘁𝗵𝗼𝗻 :- https://pdlink.in/3FJhizk 𝗝𝗮𝘃𝗮  :- https://pdlink.in/4dWkAMf 𝗗𝗦𝗔 :- https://pdlink.in/3FsDA8j  𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 :- https://pdlink.in/4jLOJ2a 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 :-  https://pdlink.in/4dFem3o 𝗖𝗼𝗱𝗶𝗻𝗴 :- https://pdlink.in/3F00oMw Get Your Dream Tech Job In Your Dream Company💫

📊Here's a breakdown of SQL interview questions covering various topics: 🔺Basic SQL Concepts: -Differentiate between SQL and NoSQL databases. -List common data types in SQL. 🔺Querying: -Retrieve all records from a table named "Customers." -Contrast SELECT and SELECT DISTINCT. -Explain the purpose of the WHERE clause. 🔺Joins: -Describe types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN). -Retrieve data from two tables using INNER JOIN. 🔺Aggregate Functions: -Define aggregate functions and name a few. -Calculate average, sum, and count of a column in SQL. 🔺Grouping and Filtering: -Explain the GROUP BY clause and its use. -Filter SQL query results using the HAVING clause. 🔺Subqueries: -Define a subquery and provide an example. 🔺Indexes and Optimization: -Discuss the importance of indexes in a database. &Optimize a slow-running SQL query. 🔺Normalization and Data Integrity: -Define database normalization and its significance. -Enforce data integrity in a SQL database. 🔺Transactions: -Define a SQL transaction and its purpose. -Explain ACID properties in database transactions. 🔺Views and Stored Procedures: -Define a database view and its use. -Distinguish a stored procedure from a regular SQL query. 🔺Advanced SQL: -Write a recursive SQL query and explain its use. -Explain window functions in SQL. ✅👀These questions offer a comprehensive assessment of SQL knowledge, ranging from basics to advanced concepts. ❤️Like if you'd like answers in the next post! 👍 👉Be the first one to know the latest Job openings 👇 https://t.me/jobs_SQL

𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀: 𝟱 𝗦𝘁𝗲𝗽𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗝𝗼𝘂𝗿𝗻�
𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀: 𝟱 𝗦𝘁𝗲𝗽𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍 Want to break into Data Science but don’t know where to begin?👨‍💻📌 You’re not alone. Data Science is one of the most in-demand fields today, but with so many courses online, it can feel overwhelming.💫📲 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3SU5FJ0 No prior experience needed!✅️

𝟱 𝗖𝗼𝗱𝗶𝗻𝗴 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗧𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗠𝗮𝘁𝘁𝗲𝗿 𝗙𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 💻 You don’t need to be a LeetCode grandmaster. But data science interviews still test your problem-solving mindset—and these 5 types of challenges are the ones that actually matter. Here’s what to focus on (with examples) 👇 🔹 1. String Manipulation (Common in Data Cleaning) ✅ Parse messy columns (e.g., split “Name_Age_City”) ✅ Regex to extract phone numbers, emails, URLs ✅ Remove stopwords or HTML tags in text data Example: Clean up a scraped dataset from LinkedIn bias 🔹 2. GroupBy and Aggregation with Pandas ✅ Group sales data by product/region ✅ Calculate avg, sum, count using .groupby() ✅ Handle missing values smartly Example: “What’s the top-selling product in each region?” 🔹 3. SQL Join + Window Functions ✅ INNER JOIN, LEFT JOIN to merge tables ✅ ROW_NUMBER(), RANK(), LEAD(), LAG() for trends ✅ Use CTEs to break complex queries Example: “Get 2nd highest salary in each department” 🔹 4. Data Structures: Lists, Dicts, Sets in Python ✅ Use dictionaries to map, filter, and count ✅ Remove duplicates with sets ✅ List comprehensions for clean solutions Example: “Count frequency of hashtags in tweets” 🔹 5. Basic Algorithms (Not DP or Graphs) ✅ Sliding window for moving averages ✅ Two pointers for duplicate detection ✅ Binary search in sorted arrays Example: “Detect if a pair of values sum to 100” 🎯 Tip: Practice challenges that feel like real-world data work, not textbook CS exams. Use platforms like: StrataScratch Hackerrank (SQL + Python) Kaggle Code I have curated the best interview resources to crack Data Science Interviews 👇👇 https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D Like if you need similar content 😄👍

𝐀𝐦𝐚𝐳𝐨𝐧 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 😍 Learn AI for free with Amazon's incredible courses! These
𝐀𝐦𝐚𝐳𝐨𝐧 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 😍 Learn AI for free with Amazon's incredible courses! These courses are perfect to upskill in AI and kickstart your journey in this revolutionary field. 𝐋𝐢𝐧𝐤 👇:- https://bit.ly/3CUBpZw Don’t miss out—enroll today and unlock new career opportunities! 💻📈

+3
Reverse Engineering

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Python Learning Plan in 2025 |-- Week 1: Introduction to Python |   |-- Python Basics |   |   |-- What is Python? |   |   |-- Installing Python |   |   |-- Introduction to IDEs (Jupyter, VS Code) |   |-- Setting up Python Environment |   |   |-- Anaconda Setup |   |   |-- Virtual Environments |   |   |-- Basic Syntax and Data Types |   |-- First Python Program |   |   |-- Writing and Running Python Scripts |   |   |-- Basic Input/Output |   |   |-- Simple Calculations | |-- Week 2: Core Python Concepts |   |-- Control Structures |   |   |-- Conditional Statements (if, elif, else) |   |   |-- Loops (for, while) |   |   |-- Comprehensions |   |-- Functions |   |   |-- Defining Functions |   |   |-- Function Arguments and Return Values |   |   |-- Lambda Functions |   |-- Modules and Packages |   |   |-- Importing Modules |   |   |-- Standard Library Overview |   |   |-- Creating and Using Packages | |-- Week 3: Advanced Python Concepts |   |-- Data Structures |   |   |-- Lists, Tuples, and Sets |   |   |-- Dictionaries |   |   |-- Collections Module |   |-- File Handling |   |   |-- Reading and Writing Files |   |   |-- Working with CSV and JSON |   |   |-- Context Managers |   |-- Error Handling |   |   |-- Exceptions |   |   |-- Try, Except, Finally |   |   |-- Custom Exceptions | |-- Week 4: Object-Oriented Programming |   |-- OOP Basics |   |   |-- Classes and Objects |   |   |-- Attributes and Methods |   |   |-- Inheritance |   |-- Advanced OOP |   |   |-- Polymorphism |   |   |-- Encapsulation |   |   |-- Magic Methods and Operator Overloading |   |-- Design Patterns |   |   |-- Singleton |   |   |-- Factory |   |   |-- Observer | |-- Week 5: Python for Data Analysis |   |-- NumPy |   |   |-- Arrays and Vectorization |   |   |-- Indexing and Slicing |   |   |-- Mathematical Operations |   |-- Pandas |   |   |-- DataFrames and Series |   |   |-- Data Cleaning and Manipulation |   |   |-- Merging and Joining Data |   |-- Matplotlib and Seaborn |   |   |-- Basic Plotting |   |   |-- Advanced Visualizations |   |   |-- Customizing Plots | |-- Week 6-8: Specialized Python Libraries |   |-- Web Development |   |   |-- Flask Basics |   |   |-- Django Basics |   |-- Data Science and Machine Learning |   |   |-- Scikit-Learn |   |   |-- TensorFlow and Keras |   |-- Automation and Scripting |   |   |-- Automating Tasks with Python |   |   |-- Web Scraping with BeautifulSoup and Scrapy |   |-- APIs and RESTful Services |   |   |-- Working with REST APIs |   |   |-- Building APIs with Flask/Django | |-- Week 9-11: Real-world Applications and Projects |   |-- Capstone Project |   |   |-- Project Planning |   |   |-- Data Collection and Preparation |   |   |-- Building and Optimizing Models |   |   |-- Creating and Publishing Reports |   |-- Case Studies |   |   |-- Business Use Cases |   |   |-- Industry-specific Solutions |   |-- Integration with Other Tools |   |   |-- Python and SQL |   |   |-- Python and Excel |   |   |-- Python and Power BI | |-- Week 12: Post-Project Learning |   |-- Python for Automation |   |   |-- Automating Daily Tasks |   |   |-- Scripting with Python |   |-- Advanced Python Topics |   |   |-- Asyncio and Concurrency |   |   |-- Advanced Data Structures |   |-- Continuing Education |   |   |-- Advanced Python Techniques |   |   |-- Community and Forums |   |   |-- Keeping Up with Updates | |-- Resources and Community |   |-- Online Courses (Coursera, edX, Udemy) |   |-- Books (Automate the Boring Stuff, Python Crash Course) |   |-- Python Blogs and Podcasts |   |-- GitHub Repositories |   |-- Python Communities (Reddit, Stack Overflow) Here you can find essential Python Interview Resources👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Like this post for more resources like this 👍♥️