Statistics show that 75% of individuals new to data science find valuable answers in community threads. These threads serve as a crucial resource for those entering or transitioning into the field. They cover a wide range of topics, including learning resources like books, tutorials, and videos. Traditional education paths such as schools, degrees, and electives are also discussed. For those interested in alternative education, online courses and bootcamps are frequently mentioned. Job search questions, including resume tips, application strategies, and career prospects, are another key focus. Additionally, the threads address elementary questions about where to start and what steps to take next. While waiting for community responses, newcomers are encouraged to explore the FAQ and Resources pages on the wiki. Past weekly threads also offer a wealth of information for those beginning their data science journey.
Splendor of SQL
@iam_Uchenna
·
Apr 17 An open-source Data Science repository to learn and apply towards solving real world problems.
This is a shortcut path to start studying Data Science.
Find everything you need here: https://github.com/academic/awesome-datascience…
Abefe – the statistics guy
@starboy_abefe
·
Apr 2 If you have a good math and stat background and you want to learn Data Science from scratch, I will recommend this book.
It even have a crash course on python, SQL, math and stat. while touching advance topics like ANN and NLP
Gabby
@thenaijacarguy
·
Feb 27 A simple guide to learning Data Analytics
Begin your Journey here: https://datafrik.co/bootcamp/beginner-data-analytics/…
Gabby
@thenaijacarguy
·
Mar 4 Dreaming of becoming a data analyst? Here’s a peek at the tech stack you’ll need to master! From Python and SQL to data visualization tools, it’s a rewarding journey! #DataAnalyst #TechStack #DataScience #CareerGoals
https://datafrik.co/bootcamp/beginner-data-analytics/…
Aishwarya Nevrekar
@nevrekaraishwa2
·
Mar 11 – Data Science Roadmap
Stage 1 – Python Basics & Data Structures
Stage 2 – Statistics & Probability
Stage 3 – Linear Algebra & Calculus
Stage 4 – Data Wrangling & Cleaning (Pandas, NumPy)
Stage 5 – Data Visualization (Matplotlib, Seaborn)
Stage 6 – Exploratory Data Analysis
Eyo Eyo, PhD
@Eyowhite3
·
Mar 5 Build a strong portfolio as a beginner in Data Science and Analytics using these projects and dataset:
A thread:
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