🧠 AIxML-SIT2025 Internship Submissions

Welcome to my repository for the AIxML-SIT2025 Remote Internship.
Here, I have documented and submitted all my assignments completed as part of the internship.

⚙️ This repository is now updated to include my final project submission.

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📚 Current Submissions

✅ ASSIGNMENTx1: College Routine Planner

📅 Date: 20-05-2025
👨‍💻 Author: Somapuram Uday
📌 Objective:
Implement a time-based daily routine planner using Python's if-elif-else ladder. Based on wake-up time input, the assistant suggests appropriate actions like continuing sleep, preparing for college, or joining internship sessions.

🔧 Key Features:

• Time parsing from float format
• Conversion to total minutes since midnight
• Structured decision ladder with context-aware messages

🔗 View on GitHub

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✅ ASSIGNMENTx2: Data Extraction from Mixed List

📅 Date: 21-05-2025
📌 Objective:
Extract and analyze different data types from a mixed Python list consisting of tuples, lists, and dictionaries.

🔧 Key Concepts:

• Type checking using isinstance()
• List comprehension and iteration
• Flattening nested structures
• Summation and odd-value filtering

🔗 View on GitHub

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✅ PROJECT_QUALIFICATION_TASKx1: DataFrame Manipulations

📅 Date: 07-06-2025
📌 Objective:
Practice low-level pandas DataFrame manipulations without using built-in shortcuts like .apply(), .dt, etc. Focuses on logic-building and manual operations.

🔧 Tasks Covered:

1. Logarithmic transformations using loops
2. Conditional replacement based on sign of values
3. Classification of even integers
4. Index column generation without default methods

🔗 View on GitHub

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✅ FINAL PROJECT: EDA × Mobile Device Usage Analysis

📅 Date: 15-06-2025
📌 Objective:
Perform an in-depth Exploratory Data Analysis (EDA) on mobile device usage dataset. Identify user behavior, brand/OS trends, and draw statistical insights.

🔧 Highlights:

• Data preprocessing and cleaning
• Visualizations with seaborn and matplotlib
• User segmentation by behavior class
• OS and brand usage patterns
• App usage, battery, and screen time analysis

🔗 View on GitHub
🔗 View on Colab
🔗 View Original Dataset on Kaggle

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🧪 PROTOTYPE PROJECT: DUMPxPROJECT – Experiment Dump Notebook

📅 Date: 14-06-2025
📌 Objective:
This notebook contains raw experiments, scratchpad code, and testing snippets created while prototyping ideas during the internship.

🔧 Included Snippets:

• Code drafts before final EDA implementation
• Testing alternative data visualizations
• Exploratory functions for preprocessing

🔗 View on GitHub

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🚀 How to Run

To run any of the submitted assignments or tasks:

1. Clone the repository:

   git clone https://github.com/udaycodespace/AIxML-SIT2025-WebBlinders-WisdomWells.git
   cd AIxML-SIT2025-WebBlinders-WisdomWells

2. Open any .ipynb file using Jupyter Notebook, VS Code, or Google Colab:

   • If using Jupyter:

     jupyter notebook

   • Or open files directly on GitHub using the links provided above.

3. Run the notebook cell-by-cell for interactive results.

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🧠 Skills Gained So Far

Throughout the internship, I have gained practical experience in:

• ✅ Python Basics & Logic Building
• ✅ Data Type Handling & List Comprehensions
• ✅ Working with Dictionaries, Tuples, and Lists
• ✅ Basic Data Science with pandas
• ✅ Exploratory Data Analysis (EDA)
• ✅ Data Visualization with matplotlib & seaborn
• 🔜 Machine Learning (coming up next)

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👨‍🎓 About Me

Name: Somapuram Uday
Internship Track: AI/ML SIT2025
Type: Remote Internship

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🏁 Summary

This repository represents my learning journey through structured assignments and practical tasks that enhance foundational skills in Python, data handling, and logic building. It is a part of the AIxML-SIT2025 internship program and includes my final project based on real-world data.

⭐ Feel free to explore, fork, and suggest improvements!