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
Here is an excellent blog to summarize the ML in production:
Few points for ML in real-world
Data Science Framework in Industry
Blog here : https://yashkarwa.github.io/posts/DataScience_Life_Cycle_Industry/
Roles need to play in Data Science
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:
- Data Analysis
- Machine Learning
- Business - Analysis & Startegy
- Engineering : Software/ DevOps
- Data Engineering
- Product Manager
Blog here: https://yashkarwa.github.io/posts/Data-Science-in-Real-World/
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