Data science is a vast-multidisciplinary field that uses scientific methods, processes, algorithms, mathematics, systems and domain knowledge to extract valuable insights from data. Full-stack data science refers to a comprehensive approach to the field of data science (End-to-End).
This repository contains the code samples { Jupyter notebooks }, datasets, and notes. I am a final year undergraduate computer science engineering student specializing in Artificial Intelligence and Machine learning.
| sl.no | Topics | Link |
|---|---|---|
| 1 | Basic Computer Science & Programming in Python | Here |
| 2 | Data structures and Algorithms | Here |
| 3 | Python for Data Science | Here |
| 4 | Database and DBMS | Here |
| 5 | Data Science - I | Here |
| 6 | Data Science - II | Here |
| 7 | Data Science - III | Here |
| 8 | Advanced Machine Learning & Deep learning | Here |
| 9 | System Designing & Machine Learning System Designing | Here |
| 10 | Machine Learning Operations & AI Operations | Here |
| 11 | Case Studies | Here |
| 12 | Data Engineering & Big Data tools | Here |
Due to the limitation in rendering some mathematical equations (Latex) in github, the current best way to view the content is to clone the repository and view the markdown files locally.
License | Resources | Code of conduct | Contribution guidelines |Project Style guide