University of Michigan's Using Databases with Python Course Review

🚀 Day 15 – Python Database Connectivity (PDBC) Today I learned how Python connects with databases like MySQL. 🔹 Used DB-API (PEP 249 standard) 🔹 Performed database operations using cursor 🔹 Learned how to insert and fetch data 💡 Key Learning: Python becomes truly powerful when it interacts with databases — this is where real-world applications begin. 📌 Example: cursor.execute("SELECT * FROM employee") Ajay Miryala 10000 Coders #Python #Database #BackendDevelopment #CodingJourney #100DaysOfCode

📘 Python Learning – Day 13 Highlights 🐍💾 Today’s class was about SQLite & Python Integration — working with real databases! 🔹 SQLite Basics: A lightweight, serverless database stored in a single file 🔹 Python Integration: Used sqlite3 to connect and manage databases 🔹 Core Operations (CRUD): ✔ Create table ✔ Insert data ✔ Read data (SELECT) ✔ Update & Delete records 🔹 Important Concepts: Using cursor, commit(), and closing connections properly 🔹 Bonus: Handled database errors using try-except 💡 Example: sqlite3.connect("students.db") → creates/connects database From simple coding to managing real data like a developer 🚀 #Python #SQLite #Database #Programming #LearningJourney #Beginner #TechSkills

🚀 Python Practice – Standard Library Modules Continuing my Python learning journey by exploring the powerful Standard Library 🐍 In this session, I worked with some commonly used modules: ✔️ array – handling collections of elements ✔️ math – mathematical operations ✔️ random – generating random values ✔️ os – file & directory operations ✔️ json – data conversion (dict ↔ JSON) ✔️ csv – reading and writing CSV files ✔️ datetime & time – working with date and time ✔️ re (Regular Expressions) – pattern matching in text Practiced using these modules to perform real-world tasks like file handling, data conversion, and basic data processing. Understanding the Standard Library is helping me write more efficient code without relying on external libraries 📊 A big thanks to Krish Naik for his amazing guidance and clear explanations 🙌 Documented all my practice in a Jupyter Notebook and shared it as a PDF to track my progress. Learning how to use built-in tools to solve real problems step by step 💡 #Python #StandardLibrary #DataAnalytics #LearningJourney #Coding

🐍🔖 Python Database Tutorials — This section contains all of our tutorials that are related to working with databases in Python https://lnkd.in/gcDxzS6

🚀 Simple Python Project: Contact Feeding Record Book I recently worked on a small project to strengthen my fundamentals in Python and database handling. 📌 Project Overview: Developed a Contact Feeding Record Book using Python, PyMySQL, and dictionary data structures. This application allows users to store, manage, and retrieve contact records efficiently. 🔧 Key Features: • Add and store contact details • Update and delete records • Retrieve contact information quickly • Integration with MySQL database using PyMySQL • Use of Python dictionaries for structured data handling 💡 What I Learned: This project helped me understand how Python interacts with databases, improved my CRUD operation skills, and reinforced the use of dictionaries for data organization. 🎯 A simple project, but a solid step toward building more advanced database-driven applications. #Python #MySQL #PyMySQL #BeginnerProject #Programming #SoftwareDevelopment #LearningJourney

Starting my journey into databases with Python 🐍 One of the first things I’m learning is how to connect Python to a database and begin interacting with data using SQL. To make this easier, I’m using SQLite a simple and lightweight database alongside SQLAlchemy, which helps Python communicate with different types of databases. Here’s what I’ve learned so far: Import create engine from SQLAlchemy Create a database engine by specifying the database type and name. Use the engine to connect and interact with the database. Explore the database by retrieving table names using engine.table_names() It’s a small step, but an important foundation for querying and analyzing data. Small steps, big growth 🚀 #Python #SQL #DataEngineering #LearningJourney #TechGrowth

🚀 Python Learning Journey – Day 26 Today, I learned about PDBC (Python Database Connectivity) and how Python interacts with databases. Here’s what I explored: ✅ What PDBC is and why it is used ✅ Connecting Python with a database ✅ Executing SQL queries using Python ✅ Performing operations like create, insert, update, delete ✅ Using cursor and connection objects This helped me understand how Python works with real-world data stored in databases. Step by step, moving towards building data-driven applications 💪 #Python #LearningJourney #Day26 #PDBC #Database #SQL #Coding #KeepLearning

Built a Student Management System using Python and SQLite Key Features: Add, view, update, delete, and search student records (CRUD operations) Integrated SQL database (SQLite) with Python Implemented real-time data storage and retrieval Used SQL queries like SELECT, INSERT, UPDATE, DELETE with WHERE clause What I learned: How to connect Python with a database using sqlite3 Understanding of conn, cursor, execute, commit Practical implementation of SQL in a real project Currently working on improving the UI and converting it into a web application. #Python #SQL #BackendDevelopment #LearningByDoing

Honored to join the Data Science Institute for this live session on Introduction to Python for Data Analysis. Generative AI and AI assistants can help generate code, but understanding how to code remains essential to truly understand your algorithms, data workflows, and AI models. Looking forward to sharing practical insights on 22 April. #Python #DataScience #AI #DataAnalysis #CPDA

If you want to get better at Python, practice is everything. Reading tutorials is helpful, but real improvement comes when you start solving problems on your own. Some of the best ways to strengthen your Python fundamentals are by practicing programs like: ✔ Arithmetic operations ✔ Prime number checks ✔ Fibonacci sequence ✔ Factorial calculations ✔ Leap year logic ✔ Array and list operations ✔ Matrix calculations ✔ Recursion-based problems These kinds of exercises help you build: • Strong problem-solving skills • Clear programming logic • Confidence for technical interviews 💡 A small tip: Before looking at the solution, try writing the program yourself. Even if it takes time, the learning will stay with you much longer. Every great developer once started with simple programs. Consistency is what makes the difference. 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐚𝐧𝐝 𝐠𝐫𝐨𝐰 𝐰𝐢𝐭𝐡 𝐦𝐲 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲 👇  🔗 𝐖𝐡𝐚𝐭𝐬𝐚𝐩𝐩- https://lnkd.in/d_tQPMS7 🔗 𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦- https://t.me/LK_Data_world 💬 If you found this PDF useful, like, save, and repost it to help others in the community! 🔄 📢 Follow Lovee Kumar 🔔 for more content on Data Engineering, Analytics, and Big Data. #Python #Coding #Programming #PythonProgramming #Developer