victorp

@victorp@techhub.social

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victorp, to datascience

Data science is a subdiscipline of Computer science. Computer science is a much more all-encompassing area of study and includes Data science itself.

🧶 Briefly:
Ⓒⓞⓜⓟⓤⓣⓔⓡ science focuses on the study of computers, including software, hardware, networks, and AI.

Ⓓⓐⓣⓐ science skills center around programming languages like SQL, R, and Python as well as knowledge of statistics, mathematics, and AI.

ℹ️ The study of data science often leads to careers as data scientists, data analysts, data engineerings, and more.

ℹ️ Salaries — about $103,500 per year.

https://fortune.com/education/articles/data-science-vs-computer-science/

#R

victorp, to ai

Low-code/no-code platforms may become more accessible and powerful due to the advancement of artificial intelligence, which may result in more automation in code writing.

Three main ways AI is being incorporated into low-code platforms:

1st - there are generative AI capabilities that are designed to improve the developer experience.

2nd - there are generative AI capabilities targeting the end users of the application created using low code.

3rd - there are features related to process improvement.

https://sdtimes.com/ai/the-promise-of-generative-ai-in-low-code-testing/

victorp, to python

The TIOBE Programming Community index is an indicator of the popularity of programming languages. This ranking is organized according to their popularity as of Sep 2023:
(1) Python
(2) C
(3) C++
(4) Java
(5) C#
(6) JavaScript
(7) Visual Basic
(8) PHP
(9) Assembly Language
(10) SQL
(11) Fortran
(12) Go
(13) MATLAB
(14) Scratch
(15) Delphi/Object Pascal
(16) Swift
(17) Rust
(18) R
(19) Ruby
(20) Kotlin

https://www.tiobe.com/tiobe-index/

#C++ #C# #C #R

victorp, to python

5 Latest Tools You Should Be Using With Python for Data Science.
🗂️ The article provides insightful details on tools like ConnectorX, DuckDB, Optimus, Polars, and Snakemake which could enhance data wrangling, querying, manipulation, and workflow automation capabilities.

  1. 🧰 ConnectorX: Simplifying the Loading of Data
  2. 🧰 DuckDB: Empowering Analytical Query Workloads
  3. 🧰 Optimus: Streamlining Data Manipulation
  4. 🧰 Polars: Accelerating DataFrames
  5. 🧰 Snakemake: Automating Data Science Workflows

https://www.makeuseof.com/latest-python-data-science-tools/

victorp,

@Stark9837 please share later your feedback 🙌

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