This repository is a large collection of iNeuron class notes, data science practice notebooks, datasets, SQL exercises, Python programs, and machine learning learning material. It brings together hands-on work from the iNeuron Full Stack Data Science Bootcamp, including topics such as Python, OOPs, MySQL, MongoDB, Pandas, NumPy, data visualization, exploratory data analysis, hypothesis testing, machine learning, time series, deep learning, and natural language processing.
If you are searching for iNeuron data science notes, iNeuron full stack data science bootcamp, data science notebooks, Python for data science, machine learning practice, or EDA projects, this repository is designed to be a useful reference.
This repo contains:
584+Jupyter notebooks for data science learning and revision257+data and database files including CSV, Excel, and SQLite resources- topic-wise folders for major data science and analytics subjects
- class tasks, practice files, mini-projects, and reference material
- hands-on learning assets from iNeuron bootcamp sessions
- Python programming
- Control flow, functions, file handling, logging, and exception handling
- Object-oriented programming in Python
- SQL, SQLite, MySQL, and MongoDB
- Pandas and NumPy
- Data visualization with graphs and plotting libraries
- Exploratory data analysis and feature engineering
- Statistics and hypothesis testing
- Machine learning algorithms and model practice
- Time series analysis and forecasting
- Deep learning and computer vision
- Natural language processing
- APIs and web scraping
The root of the repository includes many numbered notebooks that cover Python basics, loops, strings, lists, tuples, dictionaries, functions, OOPs, SQL, MongoDB, Pandas, NumPy, graphs, and Plotly.
This is the main structured course archive and includes:
1. Python 1 - 162. OOPs Class 16-183. MySQL Class 19-204. MongoDB Class 21-225. Pandas Class 23-256. NumPy Class 26-277. Data Visualization Class 28-298. API Class - 30-319. Web Scrapping Class 32-3310. Statistics Class 34-3911. EDA & FE Class 40 - 4112. Hypothesis Class 4213. EDA & FE Class 4314. Machine Learning15. Time Series16. Deep Learning18. Natural Language ProcessingDatasets1Datasets2Certificate
classTask_MongoDB_SQLitefor task-based database and notebook exercisesdatafor supporting databases, images, files, and sample spreadsheetspythonfor additional Python-related work
This repository is helpful for:
- students preparing for data science interviews
- learners revising iNeuron class content
- beginners looking for Python and Pandas notebook examples
- anyone exploring machine learning, statistics, SQL, and deep learning practice material
- developers who want a broad collection of study notebooks and datasets in one place
This GitHub repository contains iNeuron data science notes, iNeuron bootcamp notebooks, Python practice files, SQL and MongoDB examples, Pandas and NumPy exercises, exploratory data analysis projects, machine learning notebooks, time series learning material, deep learning examples, and NLP practice content. It is a practical learning archive for anyone searching for data science resources, iNeuron full stack data science course material, data analytics notebooks, and end-to-end data science study references.
iNeuron, iNeuron data science, iNeuron full stack data science bootcamp, data science, data science notes, Python for data science, Pandas notebooks, NumPy practice, SQL for data science, MongoDB Python, EDA projects, feature engineering, machine learning notebooks, deep learning, NLP, time series analysis, data analytics, Jupyter notebooks
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