Python-for-Data-Science-NPTEL-July--Sep-2024

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Python-for-Data-Science-NPTEL-July--Sep-2024

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This 4-week elective course offers undergraduate students a comprehensive introduction to Python programming, focusing on essential tools and techniques used in data science.

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# Python for Data Science (July - September 2024)

![Duration](https://img.shields.io/badge/Duration-4%20weeks-blue)
![Credit Points](https://img.shields.io/badge/Credit%20Points-1-green)
![Start Date](https://img.shields.io/badge/Start%20Date-22%20Jul%2024-blue)
![End Date](https://img.shields.io/badge/End%20Date-16%20Aug%2024-red)
![Exam Date](https://img.shields.io/badge/Exam%20Date-21%20Sep%2024-red)
![Language](https://img.shields.io/badge/Language-Python-brightgreen)

## 📋 Course Overview

This **Python for Data Science** course focuses on equipping students with essential Python programming and data manipulation skills, using popular libraries such as **NumPy**, **Pandas**, **Matplotlib**, and **Seaborn**. It also covers core concepts in data analysis, visualization, and basic machine learning techniques, with practical case studies and datasets.

---

## 🗂️ Course Layout

### **Week 1: Basics of Python and Spyder (Tool)**

- **Introduction to Spyder IDE**
  - Setting working directory
  - Creating and saving script files
  - File execution, clearing console, removing variables from the environment, clearing the environment
- **Python Basics**
  - Variable creation
  - Arithmetic and logical operators
  - Data types and associated operations

---

### **Week 2: Sequence Data Types and NumPy**

- **Sequence Data Types and Operations**
  - Strings
  - Lists
  - Arrays
  - Tuples
  - Dictionaries
  - Sets
  - Range
- **NumPy Basics**
  - Working with `ndArray` and array operations

---

### **Week 3: Pandas DataFrame and Data Visualization**

- **Pandas DataFrame**
  - Dataframe operations on **Toyota Corolla Dataset**
  - Reading files, Exploratory Data Analysis (EDA)
  - Data preparation and preprocessing
- **Data Visualization**
  - Using `Matplotlib` and `Seaborn`
  - Plots: Scatter, Line, Bar, Histogram, Box, and Pair plots
- **Control Structures**
  - if-else family, for loops, while loops
  - Control structure examples using the **Toyota Corolla Dataset**

---

### **Week 4: Case Studies in Regression and Classification**

- **Regression**
  - Predicting the price of pre-owned cars
- **Classification**
  - Classifying personal income based on various features

---

## 📚 Books and References

1. **Introduction to Linear Algebra** - by Gilbert Strang
2. **Applied Statistics and Probability for Engineers** – by Douglas Montgomery
3. **Mastering Python for Data Science** – by Samir Madhavan

---

## 📝 Assignments (2024, 2023, 2022, 2021)

Study materials and assignment solutions from past years (2021-2024) are available. Share these resources with your peers to help them prepare for upcoming exams.

### **Assignment Scores (2024)**

- **Week 1 Assignment**: ![Score: 97.0](https://img.shields.io/badge/Score-97.0-brightgreen)
- **Week 2 Assignment**: ![Score: 90.0](https://img.shields.io/badge/Score-90.0-brightgreen)
- **Week 3 Assignment**: ![Score: 100.0](https://img.shields.io/badge/Score-100.0-brightgreen)
- **Week 4 Assignment**: ![Score: 90.0](https://img.shields.io/badge/Score-90.0-brightgreen)

### **Total Assignment Score Calculation**

The total assignment score is calculated as:

```bash
Total Assignment Percentage = (97 + 90 + 100 ) / 300 * 100 = 94.25% * 0.25 * 100 = 23.91/25 
```

---
# Certifications

## Python for Data Science - Elite Certificate

I successfully completed the **Python for Data Science** course and received an **Elite Certificate** with the following scores:

- **Score**: 23.92/25 (Internal) and 43.5/75 (External)
- **Final Score**: 67

This certification showcases my understanding of Python for Data Science concepts, tools, and techniques.

## 🔗 Connect & Share

- **[Connect on LinkedIn](https://www.linkedin.com/in/farhakousar16)**
- **[Follow on GitHub](https://github.com/FarhaKousar1601)**

Study hard, share the materials, and let's ace the course together! 🎓

Python-for-Data-Science-NPTEL-July--Sep-2024

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