testes

.gitignore

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+exercise_data.json
+docs/
+verify.sh
+venv

README.md

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+# MLOps & Interviews Insper Course
+
+MLOps & Interviews

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content/about.md

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+# About this Course
+
+We will learn how to **Take Machine Learning Models to Production**!
+
+## Schedules
+
+- **Monday**: 09:45 AM - 11:45 AM
+- **Wednesday**: 09:45 AM - 11:45 AM
+- Office hours on **Mondays** 02:00 PM - 03:30 PM (Teams)
+
+## Deliverables
+
+Students will need to submit some assignments:
+
+- `APS`: practical activities developed during and after classes.
+- `INT`: some classes will focus on technical interviews in machine learning. These classes will require previous preparation by the students, who will interview each other during those classes.
+- `PRO`: in the last classes, students will have to apply the knowledge acquired in a project involving the deploy of an ML model.
+
+## Exams
+
+The interview assignments (`INT`) are like exams. Besides that, there will be no exams, neither classes during the intermediate and final assessment week of Insper's calendar.
+
+## Requirements.txt!
+
+In order for you to absorb the most from the course activities, it is mandatory that you have knowledge in:
+
+- Advanced computer programming
+- Cloud computing
+- Basic statistics
+
+The classes require a lot of autonomy. It's a good idea to have already taken the Insper courses of:
+
+- Cloud computing
+- Machine Learning
+
+## Final grade
+
+The final grade is calculated with the following formula
+
+```
+NF = 0.35*APS + 0.30*INT + 0.35*PRO
+```
+
+Some conditions are required for approval:
+
+- Grade average greater than or equal to `5.0` in **APS**, **INT** and **PRO**.
+- A maximum of two assignments (interviews + APS) with a score of zero or not submitted.
+
+If any of these criteria is not met, the student will fail this course!