sijuswamy/PyWorks

Repository for the PyWorks workshop - Ilahia College of Engineering & Technology

Jupyter Notebook

PyWorks-1.0

Repository for the PyWorks workshop - Intel-Unnati Industrial Training

Day-1 Session link

https://colab.research.google.com/drive/1Oo0IQ_RCu5rtQj0wQNDQT-XMiS4c1nvI?usp=sharing

Programs listed in the Lab Manual of the proposed KTU Syllabus of `Python for Statistical Modelling` is available in the following notebook:

https://colab.research.google.com/drive/1skDxawCA6VrAow041NCecPayN4WgqJPv?usp=sharing

Task-2

Copy the row content of the https://github.com/sijuswamy/PyWorks/blob/main/Lab_Manual.tex file and create a new Lab_manual.tex file in the overleaf project created on first day. Update the \input{pythonformat.tex} in the preample with \input{python_format.tex} and recompile the Lab_manual.tex file.
Create new experiments in the Lab maual format and complete the lab manual for the course.

Day-2 Session link

Theme- Scalability of `Python`

Lesson 1: Working with `NumPy` for scientific computing

https://colab.research.google.com/drive/1A-fXkY_gXwF-O9TVJmS0RrZgGekbLFXH?usp=sharing

Lesson 2- Working with `pandas`

https://colab.research.google.com/drive/1siEnygm_xlLRGooQyqzMaTDRzgQ5Vu9x?usp=sharing

link to data:

https://raw.githubusercontent.com/sijuswamy/PyWorks/main/telecom_churn.csv

Lesson 3- Working with `Matplotlib`

https://colab.research.google.com/drive/172tdxPseKU-mI4leA5YFbxKmOHo5e3sr?usp=sharing

Day-3 -Applications of `Python` in Data Analytics

Lesson 1- Decriptive Analysis using `Python`

Link to the colab notebook https://colab.research.google.com/drive/1b-GaNrwo-KyRRFpnFvi-bGYX-E9mYqBV?usp=sharing

Lesson 2- Inferential Analysis with `Python`

Link to the colab notebook: https://colab.research.google.com/drive/1DDv9105HdNrkIgcnZX9CPL6_UcJl-tp_?usp=sharing

Lesson 3- Case Study- Fruit preference Prescriptive Analysis based on sample survey data.

Link to colab notebook: https://colab.research.google.com/drive/1VC8SebResgUoc8oMk7_4FC8trCI35XhR?usp=sharing

Survey link

https://forms.gle/6bhGMTBKaahfEWYE9

Feedback link

https://www.menti.com/alofa611gp5n

Additional Resources:

Feeling signals with `Python`

A fun file to experience Pythonic way of signal processing

https://colab.research.google.com/drive/1iL4Yzyz022pUGaiGlsHkCZzKO94JPKdd?usp=sharing