⛔️ This has been decommissioned by AWS.
Welcome to the Data Science Capstone: Real World ML Decisions where you’ll build, train, and test a machine learning model from the ground up! Here, you clean data, conduct feature engineering, compare algorithms, and get a firsthand look at how Amazon employees work with machine learning approach ML pipelines.
This project synthesizes the math-based topics you learned in the Machine Learning Data Scientist path, with demonstrations from some of Amazon’s machine learning experts and the chance for you to build it all yourself. You’ll use machine learning to solve a real-life business challenge that the Amazon Studios team faced in the past. Because the Studios team is relied on to generate exquisite, fresh content such as The Amazing Mrs. Mazel, Sneaky Pete, and Manchester by the Sea – and that content needs to resonate with a wide range of viewers – predicting what customers will really enjoy matters.
The main benefit of taking Data Science Capstone: Real World ML Decisions is that it gives students practical knowledge they can use immediately after completing the program. This includes being able to identify potential problems or opportunities where machine learning could be applied effectively; developing algorithms capable of solving those problems; validating results using various metrics; deploying models into production environments leveraging cloud services such as Amazon Web Services (AWS); monitoring model performance over time; troubleshooting issues when needed; optimizing code execution speed through parallelization techniques etc. Furthermore, since all materials are provided at no cost there’s no need for additional investments which makes it an ideal choice if you want to get up-to-date with modern technologies without spending too much money upfront!
In conclusion Data Science Capstone: Real World ML Decisions offers tremendous value not only academically but also professionally. Not only does this program provide participants with valuable insights regarding current trends within data science but also prepares them adequately so they can go out there and start applying what they have learned right away – something which many other courses fail miserably at achieving!
If you have experience building machine learning pipelines and you want to get to it, we suggest you jump right to “I’m Ready to Build”.
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