Technologies Used by Netflix

Here are 10 popular programming languages based on versatile, widely-used, and in-demand languages:

1. Python – Ideal for beginners and professionals; used in web development, data analysis, AI, and more.

2. Java – A classic language for building enterprise applications, Android apps, and large-scale systems.

3. C – The foundation for many other languages; great for understanding low-level programming concepts.

4. C++ – Popular for game development, competitive programming, and performance-critical applications.

5. C# – Widely used for Windows applications, game development (Unity), and enterprise software.

6. Go (Golang) – A modern language designed for performance and scalability, popular in cloud services.

7. Rust – Known for its safety and performance, ideal for system-level programming.

8. Kotlin – The preferred language for Android development with modern features.

9. Swift – Used for developing iOS and macOS applications with simplicity and power.

10. PHP – A staple for web development, powering many websites and applications.

Websites for Every Language, Learn Free: https://t.me/techpsyche/500

100+ Tech YouTube Channels for Every Skill: https://t.me/techpsyche/513

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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)

Python Quick Notes👇
https://t.me/pythonresourcestp/38

71 Python Projects with Source Code👇
https://t.me/pythonresourcestp/36

Python Course by University of Waterloo
https://t.me/pythonresourcestp/29

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SQL in one image

AI here, AI there, AI this, AI that ... Heh! 😹 I'm tired.

Frontend Developer in 150 Days📌

HTML Day 1 - 15📍
◀️ https://w3schools.com/html/

CSS Day 16 - 35📍
◀️ http://css-tricks.com

Basic JavaScript Day 35 - 65📍
◀️ https://learnjavascript.online/

◀️ https://t.me/javascriptresourcestp

Responsive Web Design Day 65- 70📍
◀️ https://t.me/webdevresourcestp

Advanced JavaScript Day 70- 100📍
◀️ https://learn-js.org/

◀️ https://t.me/javascriptresourcestp

React Day 100 - 145📍
◀️ https://react-tutorial.app/

◀️ https://scrimba.com/learn-react-c0e

◀️ https://t.me/javascriptresourcestp

Git/Github Day 145 - 150📍
◀️ http://GitFluence.com

Like for more ❤️

ENJOY LEARNING👍👍

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🔰 Learning the Skills 🔰

Telegram Channel: https://t.me/zerotrusthackers

CS 642: Intro to Computer Security (http://pages.cs.wisc.edu/~ace/cs642-spring-2016.html)
academic content, full semester course, includes assigned readings, homework and github refs for exploit examples. NO VIDEO LECTURES.

CyberSec WTF (https://cybersecurity.wtf/)
CyberSec WTF Web Hacking Challenges from Bounty write-ups

Cybrary (https://www.cybrary.it/)
coursera style website, lots of user-contributed content, account required, content can be filtered by experience level

Free Cyber Security Training (https://www.samsclass.info/)
Academic content, 8 full courses with videos from a quirky instructor sam, links to research, defcon materials and other recommended training/learning

Hak5 (https://www.hak5.org/)
podcast-style videos covering various topics, has a forum, "metasploit-minute" video series could be useful

Hopper's Roppers Security Training (https://hoppersroppers.org/training.html)
Four free self-paced courses on Computing Fundamentals, Security, Capture the Flags, and a Practical Skills Bootcamp that help beginners build a strong base of foundational knowledge. Designed to prepare for students for whatever they need to learn next.

Learning Exploitation with Offensive Computer Security 2.0 (http://howto.hackallthethings.com/2016/07/learning-exploitation-with-offensive.html)
blog-style instruction, includes: slides, videos, homework, discussion. No login required.

Mind Maps (http://www.amanhardikar.com/mindmaps.html)
Information Security related Mind Maps

MIT OCW 6.858 Computer Systems Security (https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-858-computer-systems-security-fall-2014/)
academic content, well organized, full-semester course, includes assigned readings, lectures, videos, required lab files.

OffensiveComputerSecurity (https://www.cs.fsu.edu/~redwood/OffensiveComputerSecurity/lectures.html)
academic content, full semester course including 27 lecture videos with slides and assign readings

OWASP top 10 web security risks (https://www.owasp.org/index.php/Category:OWASP_Top_Ten_Project)
free courseware, requires account

SecurityTube (http://www.securitytube.net/)
tube-styled content, "megaprimer" videos covering various topics, no readable content on site.

Seed Labs (http://www.cis.syr.edu/~wedu/seed/labs.html)
academic content, well organized, featuring lab videos, tasks, needed code files, and recommended readings

TryHackMe (https://tryhackme.com/)
Designed prebuilt challenges which include virtual machines (VM) hosted in the cloud ready to be deployed

WhatsApp Channel:
https://whatsapp.com/channel/0029VaxVv551iUxRku094918

Linux Architecture

Learn DSA Visually

Links to Sites to help you learn Data Structures and Algorithms Visually:

Data Structure Visualisations :
https://www.cs.usfca.edu/~galles/visualization/Algorithms.html

Visualgo:
https://visualgo.net/en

Visualizing Algorithms by Mike Bostock :
https://bost.ocks.org/mike/algorithms/

DSA Interview Questions: https://t.me/techpsyche/545

All the best 👍👍

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DSA INTERVIEW QUESTIONS AND ANSWERS

1. What is the difference between file structure and storage structure?
The difference lies in the memory area accessed. Storage structure refers to the data structure in the memory of the computer system,
whereas file structure represents the storage structure in the auxiliary memory.

2. Are linked lists considered linear or non-linear Data Structures?
Linked lists are considered both linear and non-linear data structures depending upon the application they are used for. When used for
access strategies, it is considered as a linear data-structure. When used for data storage, it is considered a non-linear data structure.

3. How do you reference all of the elements in a one-dimension array?
All of the elements in a one-dimension array can be referenced using an indexed loop as the array subscript so that the counter runs
from 0 to the array size minus one.

4. What are dynamic Data Structures? Name a few.
They are collections of data in memory that expand and contract to grow or shrink in size as a program runs. This enables the programmer
to control exactly how much memory is to be utilized.Examples are the dynamic array, linked list, stack, queue, and heap.

5. What is a Dequeue?
It is a double-ended queue, or a data structure, where the elements can be inserted or deleted at both ends (FRONT and REAR).

6. What operations can be performed on queues?
enqueue() adds an element to the end of the queue
dequeue() removes an element from the front of the queue
init() is used for initializing the queue
isEmpty tests for whether or not the queue is empty
The front is used to get the value of the first data item but does not remove it
The rear is used to get the last item from a queue.

7. What is the merge sort? How does it work?
Merge sort is a divide-and-conquer algorithm for sorting the data. It works by merging and sorting adjacent data to create bigger sorted
lists, which are then merged recursively to form even bigger sorted lists until you have one single sorted list.

8.How does the Selection sort work?
Selection sort works by repeatedly picking the smallest number in ascending order from the list and placing it at the beginning. This process is repeated moving toward the end of the list or sorted subarray.

Scan all items and find the smallest. Switch over the position as the first item. Repeat the selection sort on the remaining N-1 items. We always iterate forward (i from 0 to N-1) and swap with the smallest element (always i).

Time complexity: best case O(n2); worst O(n2)

Space complexity: worst O(1)

9. What are the applications of graph Data Structure?
Transport grids where stations are represented as vertices and routes as the edges of the graph
Utility graphs of power or water, where vertices are connection points and edge the wires or pipes connecting them
Social network graphs to determine the flow of information and hotspots (edges and vertices)
Neural networks where vertices represent neurons and edge the synapses between them

10. What is an AVL tree?
An AVL (Adelson, Velskii, and Landi) tree is a height balancing binary search tree in which the difference of heights of the left
and right subtrees of any node is less than or equal to one. This controls the height of the binary search tree by not letting
it get skewed. This is used when working with a large data set, with continual pruning through insertion and deletion of data.

11. Differentiate NULL and VOID ?
Null is a value, whereas Void is a data type identifier
Null indicates an empty value for a variable, whereas void indicates pointers that have no initial size
Null means it never existed; Void means it existed but is not in effect

All the best 👍👍

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If I were to start Computer Science in 2025 💫🚀

- Harvard
- Stanford
- MIT
- IBM
- Telegram
- Microsoft
- Google

❯ CS50 from Harvard
http://cs50.harvard.edu/x/2023/certificate/

❯ C/C++
http://ocw.mit.edu/courses/6-s096-effective-programming-in-c-and-c-january-iap-2014/

❯ Python
http://cs50.harvard.edu/python/2022/

https://t.me/pythonresourcestp

❯ SQL
http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql

https://t.me/sqlresourcestp

❯ DSA
http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/

https://t.me/techpsyche/544

❯ Java
http://learn.microsoft.com/shows/java-for-beginners/

https://t.me/javaresourcestp

❯ JavaScript
http://learn.microsoft.com/training/paths/web-development-101/

https://t.me/javascriptresourcestp

❯ TypeScript
http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/

❯ C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07

❯ Mathematics (incl. Statistics)
ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum

❯ Data Science
cognitiveclass.ai/courses/data-science-101

https://t.me/datascienceresourcestp

❯ Machine Learning
http://developers.google.com/machine-learning/crash-course

https://t.me/mlresourcestp

❯ Deep Learning
introtodeeplearning.com

❯ Full Stack Web (HTML/CSS)
pll.harvard.edu/course/cs50s-web-programming-python-and-javascript/2023-05

https://t.me/webdevresourcestp

❯ OS, Networking
ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/

❯ Compiler Design
online.stanford.edu/courses/soe-ycscs1-compilers

Learn DSA👇
https://t.me/techpsyche/544

Cyber Security👇
https://t.me/zerotrusthackers/41

100+ YouTube channels👇
https://t.me/techpsyche/513

Make sure to scroll through the above messages 💝 you will definitely find more interesting things 🤠

ENJOY LEARNING 👍👍

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