This repository contains completed Jupyter Notebook labs from the Cisco Networking Academy, focusing on data analysis, Python programming, and introductory machine learning concepts. Each lab builds essential skills in handling real datasets, working with SQL, and applying basic regression and classification techniques.
| 📁 Folder | 📝 Description |
|---|---|
1.3.2.9 Lab - Take the Python Challenge |
A foundational lab to test and apply Python logic and functions. 🧠 |
2.2.4.5 Lab - San Francisco Crime |
Analyze crime data in San Francisco using pandas and matplotlib 📍 |
2.5.1.4 Lab - Internet Meter Data Analysis |
Clean, analyze, and visualize time-series internet data 📈 |
2.5.2.4 Lab - Working With Python and SQLite |
Learn how to integrate SQL database operations within Python using SQLite 🗃️ |
2.5.2.5 Lab - Internet Meter SQL |
Execute SQL queries on structured internet usage data directly from Python 💾 |
4.1.2.4 Lab - Simple Linear Regression in Python |
Predict numerical outcomes using linear regression with scikit-learn 📐 |
4.1.3.5 Lab - Decision Tree Classification |
Build and interpret a decision tree classifier for labeled datasets 🌳 |
4.2.2.6 Lab - Evaluating Fit Errors in Linear Regression |
Analyze residuals and model accuracy in regression models 📉 |
4.3.1.4 Lab - Internet Traffic Data Linear Regression |
Model traffic data trends and visualize regression outputs 🌐 |
4.3.2.4 Lab - Internet Meter Anomaly Detection |
Detect abnormal data patterns using statistical thresholds and logic |
- 🐍 Python scripting and control structures
- 📊 Data cleaning, analysis, and visualization using
pandasandmatplotlib - 📚 SQLite integration with Python using
sqlite3 - 📈 Linear Regression and model evaluation
- 🌲 Classification using Decision Trees
- 🕵️ Anomaly Detection techniques
- 🧠 Real-world data handling and reporting in Jupyter Notebooks
- Clone the repository:
git clone https://github.com/jcobsntos/netacad-python-labs.git
