Machine Learning Algorithms

𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬😍

- Artificial Intelligence (AI)
- Internet Of Things (IoT)
- Machine Learning (ML)
- Data Science

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Interviewer: "What do you know about our company?"
Candidate: "I think you do something related to tech?"

Big mistake! A vague or uncertain response makes you look unprepared & disinterested. Employers want to see that you’ve taken the time to understand their company & why you’d be a great fit.

What NOT to say:
❌ "I don’t know much, but I’m eager to learn" (shows a lack of preparation)
❌ "I just saw the job posting & applied" (feels random & unintentional)
❌ "It’s a big company, so I thought it’d be a good opportunity" (too generic & uninformed)

How to IMPRESS with your answer:
✔️ Shows research & enthusiasm
"Your company is a leader in [industry/product/service] & I was excited to learn about your recent [mention an achievement, innovation or project]. I really admire your commitment to [company value or mission] & that’s one of the reasons I’m drawn to this opportunity"

✔️ Demonstrates genuine interest
"From what I’ve read, your company stands out for [unique aspect: innovation, company culture, impact]. One thing that caught my attention was [specific initiative or milestone] & I’d love the opportunity to contribute to something similar"

✔️ Aligns your goals with the company’s vision
"I’ve been following your company’s growth & I truly respect how you [mention key values, industry influence, sustainability efforts, etc.]. The way you [specific company approach] aligns with my own professional goals & I’m excited about the potential to be part of your team"

Take a few minutes to research before your interview, check their website, social media, recent news & LinkedIn updates. A well-prepared candidate always stands out!

Roadmap to Master Machine Learning in 2025

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

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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👇
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Python Course by University of Waterloo
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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/

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Responsive Web Design Day 65- 70📍
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Advanced JavaScript Day 70- 100📍
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React Day 100 - 145📍
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Git/Github Day 145 - 150📍
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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