Data Science Skills in Real World
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Data Science Skills in Real World

I see a couple of Challenges, I see in the courses vs. Real-time. The primary focus of the data science should be to provide the Business value. In addition to that, it should not only be just a notebook/ standalone script which cannot be reproducible or scalable. Think of building an end-to-end from data analysis to building a data Product.

Challenges in the real world

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Here is an excellent blog to summarize the ML in production:

Few points for ML in real-world

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Data Science Framework in Industry

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Blog here : https://yashkarwa.github.io/posts/DataScience_Life_Cycle_Industry/

Roles need to play in Data Science

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Repeating - You don't need to be an expert in all the above. But at least good enough to be productive and able to work with the multi-discipline team.

Next Steps

I will summarize the skills by providing links or quick materials required to be productive for Data Science:

  1. Data Analysis
  2. Machine Learning
  3. Business - Analysis & Startegy
  4. Engineering : Software/ DevOps
  5. Data Engineering
  6. Product Manager

Blog here: https://yashkarwa.github.io/posts/Data-Science-in-Real-World/

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