https://github.com/lovnishverma/slidespptspdfs
Pdfs For Learning Python, DBMS, Big Data and Data Science AIML and much more...
https://github.com/lovnishverma/slidespptspdfs
aiml airtificialintelligence bigdata datascience machine-learning nosql-database
Last synced: 5 months ago
JSON representation
Pdfs For Learning Python, DBMS, Big Data and Data Science AIML and much more...
- Host: GitHub
- URL: https://github.com/lovnishverma/slidespptspdfs
- Owner: lovnishverma
- Created: 2025-03-19T19:43:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-07-02T16:33:07.000Z (about 1 year ago)
- Last Synced: 2025-07-19T22:57:10.419Z (12 months ago)
- Topics: aiml, airtificialintelligence, bigdata, datascience, machine-learning, nosql-database
- Homepage: https://github.com/lovnishverma/Slidespptspdfs
- Size: 58.1 MB
- Stars: 16
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🗂️ Slides, PPTs & PDFs Repository
## 📌 For Practicals Colab Notebooks: 🔗 [Visit This Repo](https://github.com/lovnishverma/Python-Getting-Started)
🔗 https://github.com/lovnishverma/Python-Getting-Started
## 📌 MADE WITH ❤️ BY LOVNISH VERMA
Welcome to the **Slidespptspdfs** repository by **Lovnish Verma**. This collection contains categorized PDFs, PowerPoint slides, and resources on a wide range of computer science and data science topics used for workshops, lectures, and student learning.
> 🎯 **Purpose**: Provide well-organized teaching material (slides, notes, PDFs) for students, trainers, and self-learners.
---
## 📁 Repository Structure
| Folder | Description |
| -------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **1 Python** | Contains Python slides and PDFs covering programming basics, functions, loops, data structures, OOP, and exception handling. Ideal for beginner-level sessions. |
| **1DataScience** | Core concepts of data science including data collection, EDA, preprocessing, visualization techniques, and project workflows. |
| **Big Data** | Slides and PDFs focused on Hadoop, Spark, HDFS, MapReduce, and the Big Data ecosystem used in enterprise-level data processing. |
| **DBMS** | Database fundamentals including ER diagrams, normalization, SQL queries, relational models, and transaction management. |
| **Jetson Nano** | Workshop slides and handouts related to Jetson Nano hardware setup, use cases in edge AI, GPIO, and computer vision demos. |
| **Machine Learning** | Covers supervised and unsupervised learning algorithms, model evaluation, training/testing splits, and real-world case studies. |
| **Web Scraping** | Introductory and intermediate-level content on scraping web data using Python (`requests`, `BeautifulSoup`, `Selenium`) with ethical considerations. |
| **Web technologies** | Resources covering HTML, CSS, JavaScript, Bootstrap, and basic web architecture concepts used for frontend development. |
| **miscellaneous** | Misc PDFs like Git & GitHub Basics Presentation, Introduction to APIs with Example, soft skills and resources that don’t fit into other categories but are useful for academic or technical use. |
---
## 📸 Preview
This repository serves as a **one-stop content bank** for:
* Faculty members conducting training/workshops
* Students revising syllabus content
* Beginners exploring Python, ML, and Web technologies
> All materials are carefully prepared and regularly updated.
---
## 🧑🏫 Author
**Lovnish Verma**
Backend Developer | Data Science Instructor | AI & IoT Enthusiast
📧 Email: [princelv84@gmail.com](mailto:princelv84@gmail.com)
🌐 GitHub: [github.com/lovnishverma](https://github.com/lovnishverma)
---
## 📜 License
All files are shared under the **MIT License** unless otherwise noted. You're welcome to use these for educational and non-commercial purposes with attribution.
---
## 🙌 Contributions
Have better slides, corrections, or additions?
Feel free to fork, edit, and raise a pull request with your improvements.
Let’s build a better open learning resource community! 💡
