Version history
PyNumSci Lab
37
ASO score
Text
45/100
Reviews
0/100
Graphic
60/100
Other
0/100
App Rating
Votes
App Age
1 year 2m
Last Update
Oct 19, 2025
Compare with Category Top Apps
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Metrics
|
Current App
|
Category Top Average
|
Difference
|
|---|---|---|---|
|
Rating
|
0
|
4.59
|
|
|
Number of Ratings (Voted)
|
0
|
1M
|
|
|
App Age
|
1y 1m
|
7y 10m
|
-86%
|
|
In-app Purchases Price
|
$0
|
$52
|
|
|
Update Frequency
|
82d
|
20d
|
+311%
|
|
Title Length
|
12
|
27
|
-56%
|
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Subtitle Length
|
30
|
28
|
+7%
|
|
Description Length
|
2 401
|
2 982
|
-19%
|
|
Number of Screenshots
|
780
|
1322
|
-41
%
|
|
Size
|
56MB
|
232MB
|
-76
%
|
Category Ranking in United States
7 days
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Last 90 days
Last 180 days
Last year
| Top | Dec 07, 2025 | Dec 14, 2025 |
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| Top | Dec 07, 2025 | Dec 14, 2025 |
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| Top | Dec 07, 2025 | Dec 14, 2025 |
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| Top | Dec 07, 2025 | Dec 14, 2025 |
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No results were found!
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Ranking Keywords in United States
| Keywords | App Rank |
|---|
Analyze this and other apps using Asolytics tools
Text ASO
Title
(
Characters:
12
of 30
)
PyNumSci Lab
Subtitle
(
Characters:
30
of 30
)
Learn NumPy,SciPy & Matplotlib
Description
(
Characters:
2401
of 4000
)
PyNumSci Lab: Mastering Scientific Computing with Python
A comprehensive educational platform designed to help you master scientific computing through structured learning paths focused on Python's powerful scientific libraries including NumPy, SciPy, and Matplotlib.
Program Overview
PyNumSci Lab provides a structured curriculum with 14 detailed learning units covering everything from fundamental concepts to advanced applications in scientific computing. Each unit combines theoretical knowledge with practical implementation, allowing you to gain practical proficiency progressively.
Learning Units
1. Introduction to Scientific Computing with NumPy, SciPy, and Matplotlib
2. Setting Up Your Python Environment for Scientific Research
3. Fundamentals of NumPy for Numerical Computation
4. Advanced Array Operations and Broadcasting in NumPy
5. Overview of SciPy: Enhancing Your Computational Toolkit
6. Linear Algebra and Matrix Computations
7. Numerical Integration and Optimization
8. Solving Differential Equations
9. Data Visualization with Matplotlib
10. Customizing Plots: Styles and Annotations
11. 3D Plotting and Animations with Matplotlib
12. Applying Scientific Computing to Physics Problems
13. Engineering Applications: Modeling and Simulation
14. Advanced Algorithms in Applied Mathematics
Features
* 100 SciPy Programming Units Covering Core Topics from Basics to Essentials
* 70 Challenging Coding Exercises per unit to solidify your understanding
* 15 interface languages supported for global accessibility
* 12 Custom Themes to personalize your learning environment
• Daily Challenges: Regular Python coding challenges to reinforce learning
• Progress Tracking: Visual portfolio showing skill development over time
• Offline Access: Complete availability of all examples without internet connection
• Ad-Free Experience: No advertisements or subscription requirements
Perfect For
• Research scientists and engineers
• Scientific programmers
• Data scientists and analysts
• STEM students
• Technical professionals
What You'll Learn
Master scientific computing concepts through hands-on practice, implementing efficient numerical algorithms, applying optimization techniques, processing scientific data, and building computationally efficient solutions for complex problems.
Transform your scientific computing capabilities with PyNumSci Lab! Practice makes perfect!}
Read more
Other
Additional Information
| Rating: | |
| Voted: | 0 |
| App Store Link: | |
| Website: | - |
| Email: | - |
| Privacy Policy: | |
| Categories: | Education |
| Size: | 55MB |
| App Age: | 1 year 2 months |
| Release Date: | Oct 29, 2024 |
| Last Update: | Oct 19, 2025 |
| Version: | 1.4 |
Version history
1.4
Oct 19, 2025
* Added Python syntax highlighting to the Notes module.
* Performance improvements and bug fixes.
* Updated UI for better user experience.
1.3
Sep 11, 2025
* Mejoras de rendimiento y correcciones de errores
* Se agregaron nuevos temas personalizados
* Se agregaron más unidades de programación que cubren temas avanzados
* Se agregó soporte para nuevos idiomas de interfaz
* Se actualizó la interfaz de usuario para una mejor experiencia de usuario
