Data Science 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
ML in Production
Read more here: https://pythonawesome.com/a-guide-to-production-level-deep-learning/
Few points for ML in real-world
Data Science Framework in Industry
Previous blog post detail: https://yashkarwa.github.io/posts/DataScience_Life_Cycle_Industry/
Roles need to play in Data Science
Next Steps
I will summarize the skills by providing links or quick materials into primary ones:
- Data Analysis
- Machine Learning
- Business Analysis
Also, the required skills set for real-world:
- Engineering -Software/ DevOps
- Data Engineering
- Product Manager
Again as highlighted, you don’t need to be an expert in each of the fields. You should be good enough to be productive. More to come…
