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Flag 04/69 : Only the graph session is done. Today's outcome was not that great but looking for tomorrow to make it happen.

Hoisted the third flag 03/69🏴: 1. Learned about Hibernate query language(HQL) which can be used to perform complex operations on database usin JAVA. 2. Learned about different types storage in AWS 3. Worked on my DSA -> graph skills by learning new

Hoisted the 2nd flag of 69🏴: 1. Learned and implemented bfs and dfs of graph with 2 questions. 2. Learned about the basic cost optimization of AWS and easy deployment with elastic beanstalk. 3. Started my 2 nd learning project using Hibernate(will s

Hoisted the first flag 🏴 01/69: 1.Learned about Hibernate and the relationship between entities 1:1,1:M,M:1,M:M relations 2. Hibernate persistent life cycle: Transient->persistent<->detached And removed state 3. Aws certification modules: Learne

Databases are vital in web development, providing efficient data storage, management, and retrieval. They ensure data consistency, integrity, scalability, and security, making them essential for dynamic applications. 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐃𝐚𝐭𝐚𝐛𝐚𝐬�

What is the difference between data scientist, data engineer, data analyst and business intelligence? 🧑🔬 Data Scientist Focus: Using data to build models, make predictions, and solve complex problems. Cleans and analyzes data Builds machine learn

If your knowledge about quantum computing is limited, here is the medial post to make you understand. I did deep research 🫡🔥⬇️ QUANTUM COMPUTING🖥️ Quantum computing is a rapidly advancing field of computing that utilizes the principles of quantu

Data scientist, Data analyst, AI engineer, or AI agent builder? Which one is best? I've explained below. 1. 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 This field teaches you how to 𝗮𝗻𝗮𝗹𝘆𝘇𝗲 𝗱𝗮𝘁𝗮, 𝗯𝘂𝗶𝗹𝗱 𝗠𝗟 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗮𝗻𝗱 𝗱𝗲𝗽𝗹𝗼𝘆 𝘁𝗵𝗲𝗺 𝗶

Most AI projects fail after deployment. I’ve explained the core problems step by step. 𝗦𝘁𝗲𝗽 1 – 𝗗𝗮𝘁𝗮 • Collects raw information from multiple sources. • Forms the foundation of every AI system. 𝗘.𝗴: APIs, logs, databases, user inputs. 𝗡

The ultimate AI/ML roadmap for beginners 👇 𝗠𝗮𝘁𝗵𝘀 What to learn: • Linear Algebra • Calculus • Statistics Resources: • Practical Statistics for Data Science( https://amzn.to/446czl5 ) • Mathematics for Machine Learning( https://amzn.to/441s