TechP

But if you want to become dangerously good at Data Engineering in 2026, I'd recommend these instead: • Fundamentals of Data Engineering • Designing Data-Intensive Applications • Data Pipelines Pocket Reference • Database Internals • Streaming Systems • The Data Warehouse Toolkit • Learning Spark • Designing Event-Driven Systems • Building Data-Driven Applications • Apache Kafka in Action Software engineering teaches you how to build software. Data engineering teaches you how to build reliable, scalable, and trustworthy data systems.

@vheeorji22 @life_of_demian 😂😂

@life_of_demian Not me oo

Is 39 too late to start a degree at university?

@vheeorji22 Age is just a number. 😅 Which school are you from Vivian?

@vheeorji22 For real Are you in LinkedIn

LinkedIn is not a safe space for me and my emotions. 😭

🚀 Python Basics Part 8 🐍🔥 ✅ Git, GitHub & Python Project Structure for Beginners Writing code is only one part of becoming a Python developer. Professional developers also know how to: ✅ Track code changes ✅ Collaborate with others ✅ Organize projects ✅ Share projects online In this part, you'll learn: ✅ Git Basics ✅ GitHub Basics ✅ Common Git Commands ✅ Python Project Structure ✅ Virtual Environments ✅ Best Practices 🧠 1. What is Git Git is a Version Control System. It helps you: ✔ Track changes in your code ✔ Restore previous versions ✔ Collaborate with other developers ✔ Manage projects efficiently Think of Git as a "save history" for your code. 🌐 2. What is GitHub GitHub is a cloud platform where you can store Git repositories. You can use GitHub to: ✔ Backup your projects ✔ Build your portfolio ✔ Collaborate with developers ✔ Showcase your work to recruiters 💻 3. Initialize a Git Repository Open your project folder and run: git init This creates a Git repository for your project. 📂 4. Check Project Status git status This command shows: ✔ Modified files ✔ New files ✔ Files ready to commit ➕ 5. Add Files Stage all project files: git add . Or stage a specific file: git add app.py 💾 6. Commit Changes Save your work with a message. git commit -m "Initial project setup" A commit is like taking a snapshot of your project. ☁ 7. Push Code to GitHub After connecting your repository: git push origin main This uploads your latest changes to GitHub. 📁 8. Recommended Python Project Structure Example: project/ ├── main.py ├── requirements.txt ├── README.md ├── .gitignore ├── data/ ├── images/ ├── notebooks/ ├── src/ └── tests/ Keeping projects organized makes them easier to maintain. 🌍 9. Virtual Environments A virtual environment creates an isolated workspace for your project. Create one: python -m venv Activate: Windows venv\Scripts\activate macOS / Linux source venv/bin/activate 📦 10. Install Project Dependencies pip install pandas Save installed packages: pip freeze > requirements.txt Install from requirements file: pip install -r requirements.txt 📖 11. Why is README.md Important A good README explains: ✔ Project overview ✔ Features ✔ Installation steps ✔ Usage instructions ✔ Technologies used Every portfolio project should include one. 🛠 Beginner Portfolio Projects ✅ Calculator App ✅ Expense Tracker ✅ Weather App ✅ Password Generator ✅ Student Management System ✅ To-Do List App ✅ File Organizer ✅ API-Based Data Viewer 🔥 Common Beginner Mistakes ❌ Not using Git from the beginning ❌ Uploading unnecessary files to GitHub ❌ Skipping virtual environments ❌ Poor project folder organization ❌ Missing README file 💡 Pro Tip Every project you build should include: ✔ Clean folder structure ✔ Meaningful commit messages ✔ README.md ✔ requirements.txt ✔ .gitignore These small habits make your projects look professional. Keep building projects, practice consistently, and you'll continue improving every day. 💬 Double Tap ❤️ For More

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@vheeorji22 More wins Enjoy my friend

@Tech_p001 Thank you Techp

Congratulations Vivian 🎉

@officialladi_T MySQL

MySQL? PostgreSQL? SQL Server? BigQuery? ​If you're a data beginner, stop stressing over which SQL flavor to learn first. ​The truth? 95% of the core syntax is exactly the same. SELECT, WHERE, GROUP BY, and JOIN work the same everywhere. ​Pick one,like MySQL or Microsoft SQL Server then master the fundamentals, and you can easily switch to any other flavor later. ​Don't let the choice paralyze you. ​Which SQL flavor are you currently learning or using right now?

@TheSpacerr Congratulations 🎉

Day 65. 357K impressions. 300+ new followers. I barely was active because I was busy building my extension. Imagine what's coming next. Thank you! 🚀

@officialladi_T Ai

When you’re stuck on a complex problem, where are you heading first... ​AI or Google?

@e_opore Well structured and simplified roadmap

LLMS ENGINEERING ROADMAP 2026: COMPLETE LEARNING PATH │ ├── 1. AI & LLM Fundamentals │ ├── What are Large Language Models (LLMs) │ ├── Transformers and attention mechanism │ └── Tokens, embeddings, and context windows │ ├── 2. Python for AI │ ├── Python fundamentals │ ├── NumPy and Pandas │ └── Virtual environments and package management │ ├── 3. Machine Learning Basics │ ├── Supervised and unsupervised learning │ ├── Neural networks fundamentals │ └── Model evaluation and optimization │ ├── 4. Deep Learning │ ├── PyTorch or TensorFlow │ ├── Transformers architecture │ └── GPU acceleration and training basics │ ├── 5. Prompt Engineering │ ├── Zero-shot and few-shot prompting │ ├── Chain-of-thought prompting │ └── Structured output generation │ ├── 6. LLM APIs & SDKs │ ├── OpenAI API │ ├── Anthropic Claude API │ └── Google Gemini API and SDKs │ ├── 7. Retrieval-Augmented Generation (RAG) │ ├── Embeddings and vector databases │ ├── Document chunking strategies │ └── Semantic search and retrieval pipelines │ ├── 8. AI Agents & Tool Calling │ ├── Function calling │ ├── Multi-step reasoning │ └── Agent frameworks and orchestration │ ├── 9. Fine-Tuning & Model Optimization │ ├── LoRA and PEFT │ ├── Quantization techniques │ └── Model evaluation and benchmarking │ ├── 10. LLM Deployment │ ├── FastAPI and inference servers │ ├── Docker and Kubernetes │ └── Cloud deployment and scaling │ ├── 11. Monitoring & AI Safety │ ├── Observability and logging │ ├── Guardrails and prompt security │ └── Bias, privacy, and responsible AI │ ├── 12. Real-World LLM Applications │ ├── AI chatbots and assistants │ ├── AI coding assistants │ └── Enterprise AI applications │ └── 13. Portfolio & Career Growth     ├── Build production-ready LLM projects     ├── Open-source contributions and research     └── Interview preparation and continuous learning Recommended Ebook → Grab the LLMs Engineering Handbook → codewithdhanian.gumroad.com/l/haeit

@AKirtesh GitHub

Where do you store your code? GitHub, GitLab, Bitbucket, or Azure DevOps Which one wins?

@vheeorji22 Yh am good 👍🏿

@Tech_p001 Welcome back🤗 Hope you are good

Who else feels behind even though they’re actually making progress?

@vheeorji22 It's going well Vivian.. My skill (Data engineering)set is becoming more versatile every day. But I have to keep going. Tough skills build tough people. 💪

@Tech_p001 How is it going !?

Do you prefer learning from ? A. YouTube B. Books C. Paid courses D. Communities

@vheeorji22 Yh 👍🏿❤️

@Tech_p001 Hi Techp Nice meeting you too

Hi, I’m Vivian Orji I know we haven’t met yet, so let me introduce myself. I’m an aspiring Data Analyst passionate about turning data into meaningful insights that help businesses make better decisions. I’m currently building my skills in Excel, SQL, Power BI and Python, learning how to clean, analyze and visualize data while working on projects that strengthen my problem-solving abilities. I enjoy exploring datasets, finding patterns, asking questions, creating dashboards and continuously improving my analytical skills. I’m documenting my learning journey, sharing what I learn and connecting with others in the data community along the way. If you enjoy talking about data, analytics, or tech or have advice, opportunities or projects you’d like to share, my DMs are always open.

@vheeorji22 Yes Vivian I have not been online for days 😔 But am online now Smiles😊

@Tech_p001 Hi Tech p It’s been long I saw you on my Timeline

Be honest, As a developer, which database is better in the AI era?