Accelerate Your Data Science Learning: Essential Skills for Success
This article is a summary of a YouTube video "👩🏻💻 How to learn Data Science FASTER" by Thu Vu data analytics
TLDR Developing a comprehensive understanding of programming, math, statistics, data wrangling, visualization, regression, EDA, ML algorithms, scraping, databases, software dev, and deployment is essential for becoming a successful data analyst or ML engineer.
Knowing what to learn in data science is key: focus on programming, machine learning, and software.
Learn basic programming, math, and statistics first, then build up your data science skills to solve a complete use case.
Learn programming, data wrangling, statistics, visualization, regression, EDA, ML algorithms, scraping, databases, software dev, and deployment to become a data analyst or ML engineer.
Googling errors is often faster than asking for help when learning web scripting, NLP, network analysis and visualization.
Start small and make learning fun and unique to get feedback!
Create cheat sheets to stay motivated and learn effectively, depending on whether you're a Torah or Kuma learner.
A clipboard manager app and coding productivity tools can help you work faster and smarter.
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