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Welcome to the AlgorithmsQuestions wiki!

1.🚀 𝐀𝐰𝐞𝐬𝐨𝐦𝐞 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐭𝐨 𝐬𝐭𝐚𝐫𝐭 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐲𝐨𝐮𝐫 𝐩𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 👨‍💻

Here are 9 Projects that you can add to your portfolio

📌 1. End-To-End From Web Scraping to Tableau https://lnkd.in/ePMw63ge

What you will learn: Python, SQL, Snowflake, Tableau

📌 2. Building Data Model and Writing ETL Job https://lnkd.in/eq-e3_3J

What you will learn: Python, SQL, Building Data Models, Basics of DBMS, Writing ETL Job, Querying Data Programmatically, PostgreSQL

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What you will learn: Python, SQL, Cloud Computing Basics, AWS Services (Athena, Glue, Redshift, S3, IAM), Creating Data Pipeline

📌 4. ETL Project in Azure Data Factory https://lnkd.in/eP8huQW3

What you will learn: Azure Data Factory

📌 5. ETL Pipeline on AWS Cloud https://lnkd.in/ebgNtNRR

What you will learn: Python, SQL, Cloud Computing Basics, AWS Services (Athena, Glue, Redshift, S3, IAM), Creating Data Pipeline

📌 6. Covid Data Analysis Project https://lnkd.in/eWZ3JfKD

What you will learn: Python, SQL, Building Data Model, AWS Services (Athena, Glue, Redshift, S3, IAM), Creating Data Pipeline, PostgreSQL

📌 7. YouTube Data Analysis (End-To-End Data Engineering Project) https://lnkd.in/eYJTEKwF

What you will learn: Python, PySpark, SQL, How to understand the business problem, AWS Services (Athena, Glue, Redshift, S3, IAM, Lambda, Quicksight), Building Data Pipeline and Scheduling it.

📌 8. Twitter Data Pipeline using Airflow https://lnkd.in/eNxHHZbY

What you will learn: Python, Basics of Airflow, Working with Twitter Data and Package (Tweepy), Pandas, Writing ETL job and storing data on S3

📌 9. Sentiment analysis Twitter: Kafka and Spark Structured Streaming https://lnkd.in/esVAaqtU

What you will learn: Spark, Kafka

#python #sql #cloud #data

2. System design:

1. AWS Scalability 101: https://lnkd.in/eU736g9Q

2. Actor Model at PayPal: https://lnkd.in/eqcb7MpP

3. Distributed Counter: https://lnkd.in/eGwaA62J

4. User Online Status Indicator: https://lnkd.in/eW77FXAh

5. Scalability 101 from LinkedIn: https://lnkd.in/eEKMn28h

6. Microservices vs Monolith: https://lnkd.in/e3EBtg_v

7. Rate Limiting at Stripe: https://lnkd.in/g2aM5jxG

8. Gaming Leaderboard: https://lnkd.in/edfTDq5R

9. Real-Time Live Comments: https://lnkd.in/e8g3dZ2i

10. How Uber Computes ETA: https://lnkd.in/eVKV2ePC

11. URL Shortener: https://lnkd.in/evFTZVQq

12. Slack Architecture: https://lnkd.in/eATMDjrK

13. Zoom Architecture: https://lnkd.in/edidhxZw

14. Pastebin: https://lnkd.in/eZpfaVjc

15. Virtual Waiting Room Architecture: https://lnkd.in/eD3kPiPv

16. How Does Netflix Work?: https://lnkd.in/ehqyWMiW

========= when to use which Design Pattern:

𝟭. 𝗖𝗿𝗲𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 🔹 Singleton: Use when a single instance of a class is needed. Some examples are logging and database connections. 🔹 Factory Method: Decouple object creation from usage. For example, you create different types of database connections based on configuration. 🔹 Abstract Factory: Create families of related objects. For example, I build parsers for different file formats (e.g., JSON, XML, CSV). 🔹 Builder: Constructing complex objects step by step. For example, if you need to create a complex domain object. 🔹 Prototype: Creating duplicate objects and reusing cached objects to reduce database calls.

𝟮. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 🔹 Adapter: Make incompatible interfaces compatible. For example, it integrates a new logging library into an existing system that expects a different interface. 🔹 Composite: Represent part-whole hierarchies. For example, graphic objects in a drawing application can be grouped and treated uniformly 🔹 Proxy: Control access to objects. For example, lazy loading of a high-resolution image in a web application. 🔹 Decorator: Dynamically add/remove behavior. For example, we are implementing compression or encryption on top of file streams. 🔹 Bridge: Decouple abstraction from implementation. For example, I am separating platform-specific code from core logic.

𝟯. 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 🔹 Strategy: Define a family of algorithms. For example, they allow users to choose different sorting or compression algorithms. 🔹 Observer: Maintain a consistent state by being notified of changes and, for example, notifying subscribers of events in a messaging system. 🔹 Command: Encapsulate a request as an object. For example, I implement undo/redo functionality in text or image editor. 🔹 State: Encapsulate state-specific behavior. For example, we are handling different states of a user interface element (e.g., enabled, disabled, selected). 🔹 Template Method: Define the skeleton of an algorithm in operation, deferring some steps to subclasses and implementing a base class for unit testing with customizable setup and teardown steps.