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8 Best Sites to Buy Verified GitHub Accounts Right Now | Los Angeles
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How do I transition from Data Analyst to Data Scientist?
The shift from Data Analyst to Data Scientist is one of some of the best-known and lucrative career opportunities available in the tech industry. Both roles are dependent on data. The main difference is in the goals of the Data Analyst who provides an explanation of the past (what happened and why) while a Data Scientist predicts the future (what will happen and how to best improve the process).
If you're using SQL, Excel, or Tableau You've got a solid base. However, progressing to Data Science requires a shift away from traditional analytics, and moving towards predictive models and experiments in design. If you reside in a hub of technology and are in the field of data science course in Pune as well as similar cities will offer the structured guidance and local networks needed to facilitate this change.
The Roadmap to The 4-Step Transition
1. Get Your Programming Skills up to date (From engineering to scripting)
The majority of analysts use Python and R to do the basic manipulation of data. As an Data Scientist you must take code in the same way as engineers working within the software. This includes understanding:
Advanced Python: Learning Obscure-Oriented programming (OOP) and decoration as well as writing modular and reuseable code.
The DS Stack: Deep diving into machine learning using Scikit-learn and TensorFlow and PyTorch for deep learning.
production skills: Understanding how to wrap your model into an API (using Flask or FastAPI) to allow other programs to use it.
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