Udemy - Python for STEM

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[ TutSala.com ] Udemy - Python for STEM
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Welcome
    • 1. Welcome!.mp4 (35.1 MB)
    • 1. Welcome!.srt (2.4 KB)
    2. Introduction
    • 1. Installing Anaconda.mp4 (40.9 MB)
    • 1. Installing Anaconda.srt (5.8 KB)
    • 2. Coding With Spyder.mp4 (36.8 MB)
    • 2. Coding With Spyder.srt (7.0 KB)
    • 3. Coding With Notepad++.mp4 (43.5 MB)
    • 3. Coding With Notepad++.srt (7.6 KB)
    • 4. Coding With JupyterLab.mp4 (63.4 MB)
    • 4. Coding With JupyterLab.srt (14.0 KB)
    3. Building Simulations
    • 1. Monte Carlo Method - Pt. 1.mp4 (21.3 MB)
    • 1. Monte Carlo Method - Pt. 1.srt (3.6 KB)
    • 1.1 sandbox_estimate_pi.ipynb (2.7 KB)
    • 1.2 solution_estimate_pi.ipynb (53.9 KB)
    • 10. Harmonic Oscillator - Pt. 2.mp4 (39.7 MB)
    • 10. Harmonic Oscillator - Pt. 2.srt (7.9 KB)
    • 11. Harmonic Oscillator - Pt. 3.mp4 (50.6 MB)
    • 11. Harmonic Oscillator - Pt. 3.srt (9.7 KB)
    • 12. Satellite Orbit - Pt. 1.mp4 (54.1 MB)
    • 12. Satellite Orbit - Pt. 1.srt (11.8 KB)
    • 12.1 sandbox.ipynb (3.9 KB)
    • 12.2 solution.ipynb (94.4 KB)
    • 13. Satellite Orbit - Pt. 2.mp4 (65.9 MB)
    • 13. Satellite Orbit - Pt. 2.srt (9.6 KB)
    • 14. Satellite Orbit - Pt. 3.mp4 (32.7 MB)
    • 14. Satellite Orbit - Pt. 3.srt (6.2 KB)
    • 15. Satellite Orbit - Pt. 4.mp4 (81.2 MB)
    • 15. Satellite Orbit - Pt. 4.srt (12.5 KB)
    • 16. Brownian Motion - Pt. 1.mp4 (52.4 MB)
    • 16. Brownian Motion - Pt. 1.srt (7.7 KB)
    • 16.1 diffusion coefficient.html (0.1 KB)
    • 16.2 sandbox.ipynb (4.7 KB)
    • 16.3 solution.ipynb (258.8 KB)
    • 17. Brownian Motion - Pt. 2.mp4 (46.8 MB)
    • 17. Brownian Motion - Pt. 2.srt (8.3 KB)
    • 18. Brownian Motion - Pt. 3.mp4 (32.8 MB)
    • 18. Brownian Motion - Pt. 3.srt (5.9 KB)
    • 19. Brownian Motion - Pt. 4.mp4 (74.0 MB)
    • 19. Brownian Motion - Pt. 4.srt (11.9 KB)
    • 2. Monte Carlo Method - Pt. 2.mp4 (41.3 MB)
    • 2. Monte Carlo Method - Pt. 2.srt (6.3 KB)
    • 3. Monte Carlo Method - Pt. 3.mp4 (44.1 MB)
    • 3. Monte Carlo Method - Pt. 3.srt (7.2 KB)
    • 4. Monte Carlo Method - Pt. 4.mp4 (61.5 MB)
    • 4. Monte Carlo Method - Pt. 4.srt (11.0 KB)
    • 5. Monte Carlo Integration - Pt. 1.mp4 (12.3 MB)
    • 5. Monte Carlo Integration - Pt. 1.srt (2.2 KB)
    • 5.1 sandbox_estimate_integral.ipynb (3.8 KB)
    • 5.2 solution_estimate_integral.ipynb (82.1 KB)
    • 6. Monte Carlo Integration - Pt. 2.mp4 (51.1 MB)
    • 6. Monte Carlo Integration - Pt. 2.srt (9.3 KB)
    • 7. Monte Carlo Integration - Pt. 3.mp4 (44.1 MB)
    • 7. Monte Carlo Integration - Pt. 3.srt (5.9 KB)
    • 8. Monte Carlo Integration - Pt. 4.mp4 (80.4 MB)
    • 8. Monte Carlo Integration - Pt. 4.srt (13.5 KB)
    • 9. Harmonic Oscillator - Pt. 1.mp4 (76.1 MB)
    • 9. Harmonic Oscillator - Pt. 1.srt (12.5 KB)
    • 9.1 discrete-time Fourier transform.html (0.1 KB)
    • 9.2 harmonic oscillator.html (0.1 KB)
    • 9.3 sandbox.ipynb (5.0 KB)
    • 9.4 solution.ipynb (144.5 KB)
    4. Analyzing Data
    • 1. Particle Tracking - Pt. 1.mp4 (52.4 MB)
    • 1. Particle Tracking - Pt. 1.srt (8.5 KB)
    • 1.1 brownian_motion.mp4 (63.2 MB)
    • 1.2 info.obj (15.9 KB)
    • 1.3 sandbox.ipynb (4.0 KB)
    • 1.4 solution.ipynb (411.6 KB)
    • 10. Parameter Estimation - Pt. 6.mp4 (22.3 MB)
    • 10. Parameter Estimation - Pt. 6.srt (3.1 KB)
    • 11. Statistics - Pt. 1.mp4 (61.4 MB)
    • 11. Statistics - Pt. 1.srt (11.2 KB)
    • 11.1 kaggle dataset.html (0.1 KB)
    • 11.2 sandbox.ipynb (7.5 KB)
    • 11.3 solution.ipynb (95.8 KB)
    • 12. Statistics - Pt. 2.mp4 (39.3 MB)
    • 12. Statistics - Pt. 2.srt (6.6 KB)
    • 13. Statistics - Pt. 3.mp4 (72.8 MB)
    • 13. Statistics - Pt. 3.srt (11.7 KB)
    • 14. Statistics - Pt. 4.mp4 (77.3 MB)
    • 14. Statistics - Pt. 4.srt (10.0 KB)
    • 15. Statistics - Pt. 5.mp4 (45.4 MB)
    • 15. Statistics - Pt. 5.srt (6.7 KB)
    • 16. Statistics - Pt. 6.mp4 (71.6 MB)
    • 16. Statistics - Pt. 6.srt (11.5 KB)
    • 2. Particle Tracking - Pt. 2.mp4 (32.5 MB)
    • 2. Particle Tracking - Pt. 2.srt (4.8 KB)
    • 3. Particle Tracking - Pt. 3.mp4 (71.2 MB)
    • 3. Particle Tracking - Pt. 3.srt (12.2 KB)
    • 4. Particle Tracking - Pt. 4.mp4 (58.2 MB)
    • 4. Particle Tracking - Pt. 4.srt (9.4 KB)
    • 4.1 generate_video.ipynb (38.8 KB)
    • 4.2 particle_tracking.mp4 (164.9 MB)
    • 5. Parameter Estimation - Pt. 1.mp4 (56.7 MB)
    • 5. Parameter Estimation - Pt. 1.srt (9.5 KB)
    • 5.2 sandbox.ipynb (9.5 KB)
    • 5.3 solution.ipynb (256.6 KB)
    • 6. Parameter Estimation - Pt. 2.mp4 (114.6 MB)
    • 6. Parameter Estimation - Pt. 2.srt (16.1 KB)
    • 7. Parameter Estimation - Pt. 3.mp4 (46.3 MB)
    • 7. Parameter Estimation - Pt. 3.srt (7.3 KB)
    • 8. Parameter Estimation - Pt. 4.mp4 (93.2 MB)
    • 8. Parameter Estimation - Pt. 4.srt (12.4 KB)
    • 9. Parameter Estimation - Pt. 5.mp4 (65.6 MB)
    • 9. Parameter Estimation - Pt. 5.srt (9.3 KB)
      • data ipynb_checkpoints
      • multi_spectrum-checkpoint.txt (18.9 KB)
      • single_spectrum-checkpoint.txt (0.0 KB)
      • multi_spectrum.txt (18.9 KB)
      • multi_spectrum_weighted.txt (19.0 KB)
      • noise_spectrum_0.txt (19.2 KB)
      • noise_spectrum_1.txt (19.2 KB)
      • noise_spectrum_10.txt (19.2 KB)
      • noise_spectrum_11.txt (19.2 KB)
      • noise_spectrum_12.txt (19.2 KB)
      • noise_spectrum_13.txt (19.2 KB)

      • Description

        Python for STEM



        MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
        Genre: eLearning | Language: English + srt | Duration: 51 lectures (6h 45m) | Size: 2.6 GB
        Learn how to solve problems from science & engineering with Python!
        What you'll learn:
        Solving typical problems in the STEM disciplines with Python
        Implementing Monte Carlo methods with NumPy
        Solving differential equations with SciPy
        Simulating & tracking particle diffusion with OpenCV & SciPy
        Estimating parameters and optimization with SciPy
        Performing statistical analysis with Pandas
        Creating high-quality figures with Matplotlib

        Requirements
        Intermediate Python skills (i.e. knowledge of using NumPy, Matplotlib, or SciPy)
        Knowledge of advanced calculus and algebra (i.e. familiar with differential equations, vectors, or matrices)

        Description
        This course teaches you how to approach and solve typical problems that occur in science, technology, engineering, and maths (STEM). You will learn how to master some of the most popular Python packages including

        Numpy



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seeders:19
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Udemy - Python for STEM

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Download torrent
2.8 GB
seeders:19
leechers:7
Udemy - Python for STEM

Torrent hash: 5C9FD92D48C3DC998FCF50207D31895D64F9ACB8