---
title: "Practical Data Science using Python"
url: https://manasdasgupta.com/courses/practical-data-science-using-python/
description: "A 31-hour, project-based course in data science with Python: statistics, exploratory data analysis, NumPy, Pandas and visualisation, then regression…"
author: Manas Dasgupta
last_verified: 2026-09-25
---

# Practical Data Science using Python

> **Bottom line:** A 31-hour, project-based course in data science with Python: statistics, exploratory data analysis, NumPy, Pandas and visualisation, then regression, classification, clustering, PCA, feature engineering and hyperparameter tuning with scikit-learn and statsmodels. It ends with deep neural networks in TensorFlow/Keras and deploying models with FastAPI and Streamlit.

- **Platform:** Udemy
- **For:** Aspiring data science professionals and machine learning engineers.
- **Duration:** 30h 58m
- **Language:** English
- **Rating on Udemy:** 4.8 out of 5 (45+ ratings)
- **Learners enrolled:** 485
- **Enrol:** https://manasdasgupta.com/go/practical-data-science-using-python/

## What you will be able to do
- Data science concepts, use cases, life cycle and methodologies
- Exploratory data analysis (EDA) and statistical techniques
- Python for data science and machine learning
- Linear regression and classification algorithms
- K-means clustering and dimensionality reduction with PCA
- Feature engineering, hyperparameter tuning and grid-search cross-validation
- An introduction to deep neural networks

## Curriculum
### Introduction to Data Science


### Statistical Techniques


### Python for Data Science


### Exploratory Data Analysis (EDA)


### Machine Learning


### Linear Regression


### Logistic Regression


### Unsupervised Learning - K-Mean Clustering


### Naive Bayes Probability Model


### Classification using Decision Trees


## Prerequisites
- Some exposure to a programming language is useful

## Frequently asked questions
### Who is this course for?
Aspiring data science professionals and machine learning engineers.