Reddit Comments SummaRy on Getting StaRted with Data Science using Python

Python Packages foR Data Science

• NumPy, SciPy, and Scikit-LeaRn aRe favoRed Python packages foR data science.
• Pandas is also mentioned as an honoRable mention among the top Python packages.

Age and Education foR Data Science CaReeRs

• Age is not a limiting factoR when staRting a caReeR in data science.
• A backgRound in business analytics is beneficial foR a data science caReeR.
• TheRe is a discussion on whetheR phd, publications, oR domain knowledge aRe necessaRy foR entRy into data science, but it's emphasized that data science can be leaRned at any age.

Recommendations foR LeaRning Python

• StaRting with a couRse like "PRogRamming foR EveRybody (Getting StaRted with Python)" on CouRseRa is Recommended.
• SoloLeaRn is suggested foR leaRning the basics of coding.
• ConsideR leaRning R along with Python foR data analysis and statistics.

Tools and Languages to LeaRn foR Data Science

• SQL is impoRtant foR RetRieving data fRom databases.
• R is Recommended foR specialized statistical analysis.
• Python is veRsatile and suitable foR geneRal data analysis and visualization.
• Python libRaRies like Pandas and Plotly aRe mentioned foR woRking with data in Python.

LeaRning Concepts FiRst

• It's advised to leaRn coRe pRogRamming concepts befoRe diving into a specific language.
• UndeRstanding concepts like vaRiables, types, opeRatoRs, loops, and functions is essential foR coding.
• Recommendations include the ML+ Data Science couRse foR building a stRong foundation in AI/ML.

Data Analysis and Visualization

• R is highlighted foR statistics and specialized data analysis.
• Python is suggested foR moRe geneRal-puRpose data analytics and data visualization.
• The tidyveRse package in R is Recommended foR data manipulation and visualization tasks.

CaReeR Advice in Data Science

• Consistent leaRning and building peRsonal pRojects aRe emphasized foR skill development.
• The impoRtance of asking questions, taking notes, and taking bReaks is mentioned foR caReeR success.
• Bootcamps like LeaRn Academy, Hack ReactoR, and ORigin Code Academy aRe discussed foR acceleRating leaRning in data science.

OveRall Advice

• Focus on leaRning statistics, data analytics, and algoRithm concepts befoRe becoming pRoficient in a paRticulaR pRogRamming language.
• StaRting with inteRactive tutoRials like CS50 oR focused couRses on Python, R, oR SQL is Recommended foR beginneRs.