jetbrains-academy · kochaika · Feb 4, 2026 · Jan 10, 2026 · Jan 13, 2026 · Jan 13, 2026
diff --git a/NumPy/Introduction/Course View/main.py b/NumPy/Introduction/Course View/main.py
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diff --git a/NumPy/Introduction/Getting to know you/__init__.py b/NumPy/Introduction/Getting to know you/__init__.py
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+if __name__ == "__main__":
+    pass
diff --git a/NumPy/Introduction/Getting to know you/task-info.yaml b/NumPy/Introduction/Getting to know you/task-info.yaml
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+type: theory
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+    visible: true
+  - name: __init__.py
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diff --git a/NumPy/Introduction/Getting to know you/task-remote-info.yaml b/NumPy/Introduction/Getting to know you/task-remote-info.yaml
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+id: 586639688
diff --git a/NumPy/Introduction/Getting to know you/task.md b/NumPy/Introduction/Getting to know you/task.md
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+## Getting to know you
+Thank you for taking our Python Libraries – NumPy course!
+We would be happy to get to know you a bit better, so we’re asking you to fill out [this brief form](https://surveys.jetbrains.com/s3/getting-to-know-the-student-mastering-python-libs-numpy-course).
diff --git a/NumPy/Introduction/Navigating Around/main.py b/NumPy/Introduction/Navigating Around/main.py
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diff --git a/NumPy/Introduction/Task Description/main.py b/NumPy/Introduction/Task Description/main.py
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diff --git a/NumPy/Introduction/Task Description/task-info.yaml b/NumPy/Introduction/Task Description/task-info.yaml
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diff --git a/NumPy/Introduction/lesson-info.yaml b/NumPy/Introduction/lesson-info.yaml
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 content:
+  - Getting to know you
   - Why NumPy
   - Navigating Around
   - Course View

diff --git a/Projects/Conclusion/What You’ve Learned/__init__.py b/Projects/Conclusion/What You’ve Learned/__init__.py
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+id: 1878058376
diff --git a/Projects/Conclusion/What You’ve Learned/task.md b/Projects/Conclusion/What You’ve Learned/task.md
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+Congratulations, you made it to the end of the course! We hope you enjoyed it.
+
+### Summary
+In this course, you learned how to work with NumPy arrays, indexing, slicing, and vectorized operations for matrix and multidimensional data. By applying linear algebra concepts — such as matrix multiplication and SVD — to real image data in the RGB approximation project, you saw how math models work in practice. 
+
+You have gained practical skills in numerical computing that are essential for fields like machine learning, data science, and scientific programming.
+
+### Feedback
+
+We would really appreciate it if you could take a few minutes to answer [our survey](https://surveys.jetbrains.com/s3/course-feedback-mastering-python-libs-numpy). Your feedback helps us improve our content and ensure it remains relevant for future students.
+
+### What next?
+
+Now that you’ve mastered NumPy, move on to [Pandas](https://academy.jetbrains.com/course/22686-gateway-to-pandas) to work with tables, CSV files, and real datasets used in data science and machine learning.
diff --git a/Projects/Conclusion/What You’ve Learned/task.py b/Projects/Conclusion/What You’ve Learned/task.py
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+if __name__ == "__main__":
+    pass
diff --git a/Projects/Conclusion/lesson-info.yaml b/Projects/Conclusion/lesson-info.yaml
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+content:
+  - What You’ve Learned
diff --git a/Projects/Conclusion/lesson-remote-info.yaml b/Projects/Conclusion/lesson-remote-info.yaml
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+id: 988811788
diff --git a/Projects/section-info.yaml b/Projects/section-info.yaml
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 content:
   - SVD
+  - Conclusion
diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-# Python Libraries - NumPy course
+# Mastering Python Libraries – NumPy course
 [![official JetBrains project](http://jb.gg/badges/official.svg)](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
 <a href="https://academy.jetbrains.com/course/18302-python-libraries--numpy?=fromGitHub" target="_blank">
 <img src="https://img.shields.io/static/v1?logo=jetbrains&logoColor=1bd58e&label=&message=Course%20catalog&color=5a5a5a&style=flat" alt="Course%20catalog"></a>