Twitter Sentiment Analysis (Using Python)

IntermediateLevel
14873+Students Enrolled
30 MinsDuration
4.8Average Rating

About
Learning Outcomes
Who Should Enroll
Course Curriculum
Instructors

About this Course

Learn how sentiment analysis interprets emotions in text and helps extract opinions, attitudes, and meaningful insights from Twitter data.
Understand sentiment analysis as a classification task where tweets are labeled as positive, negative, or neutral using NLP techniques.
Explore how to perform sentiment analysis of Twitter data in Python and discover real industry applications across marketing, customer service, and trend analysis.

Learning Outcomes

Sentiment Analysis

Understand and apply sentiment analysis techniques for text.

Twitter Data

Analyze and extract insights from Twitter data using Python.

Python Implementation

Build and evaluate sentiment analysis models in Python.

Who Should Enroll

Individuals interested in Natural Language Processing and text sentiment analysis. for real-world scenarios.
Data scientists and professionals wanting to learn sentiment analysis and its real-world applications.
Anyone looking to analyze social media data and understand public opinion for real-world scenarios.

Course Curriculum

Learn tweet preprocessing, text cleaning, tokenization, feature engineering, NLP models, and sentiment classification in Python using real Twitter datasets for accurate, data-driven sentiment insights.

1. Overview of the Course
2. Understand Problem Statement
3. Table of Contents
4. Loading Libraries & Data
5. Data Inspection
6. Data Cleaning
7. Story Generation & Visualization
8. Bag-of-Words Features
9. TF-IDF Features
10. Word2Vec Features
11. Modeling Understanding
12. Logistic Regression
13. Support Vector Machine (SVM)
14. RandomForest
15. XGBoost Algorithm
16. FineTuning XGBoost + Word2Vec
17. Summary of the Project

Meet the instructor

Our instructor and mentors carry years of experience in data industry

Kunal Jain

CEO, Analytics Vidhya

Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- the world's 2nd largest Data Science community.

Get this Course Now

With this course you’ll get

30 Mins
Duration
Kunal Jain
Instructor
Intermediate
Level

Certificate of completion

Earn a professional certificate upon course completion

Industry-Recognized Credential
Career Advancement Credential
Shareable Achievement

Frequently Asked Questions

Looking for answers to other questions?

Sentiment analysis identifies emotional tone in tweets to understand public opinion. It classifies text into categories such as positive, negative, or neutral, helping businesses and researchers analyze trends, reactions, and audience behavior at scale.

Tweets contain slang, sarcasm, abbreviations, emojis, and fast-evolving trends. These inconsistencies make it challenging for models to interpret emotions accurately, requiring robust preprocessing and advanced NLP techniques for reliable results.

Twitter data is cleaned using steps like removing URLs, mentions, emojis, stopwords, punctuation, and repeated characters. Tokenization, stemming, lemmatization, and lowercasing ensure tweets become structured and ready for accurate sentiment classification.

Popular models include Logistic Regression, Naive Bayes, SVMs, and deep learning models like LSTMs, Bi-LSTMs, and Transformers. These models process tweet embeddings to classify sentiments as positive, negative, or neutral with high accuracy.

Python offers powerful NLP libraries like NLTK, SpaCy, scikit-learn, and transformers. These help with preprocessing, feature extraction, modeling, and evaluation, enabling end-to-end sentiment analysis pipelines for real Twitter datasets.

Yes. Deep learning models like LSTMs, GRUs, CNNs, and Transformers capture context, sequence patterns, and complex linguistic nuances in tweets. They outperform traditional models, especially when large annotated datasets are available.

Related courses

Expand your knowledge with these related courses and expand way beyond

1 Hour1 Lesson4.5

No Code Predictive Analytics with Orange

30 Minutes 1 Lesson4.8

Loan Prediction Practice Problem (Using Python)

30 Minutes 1 Lesson4.6

Big Mart Sales Prediction Using R

Popular free courses

Discover our most popular courses to boost your skills

12 Hours10 Lessons 10

Data Analyst Learning Path

4.7

9 Hours5 Lessons 5

Vibe Coding Learning Path

4.6

9 Hours7 Lessons 7

GenAI Learning Path

4.6

30 Hours9 Lessons 9

Data Science Learning Path

4.7

40 Minutes 0

NotebookLM Essentials to Pro: The Complete Practical Guide

4.7

40 Minutes 0

Foundations of Vector Database

4.7

1 Hour5 Lessons 5

Gemini 3: The AI That Thinks, Sees and Creates

4.7

1 Hour1 Lesson1

RIP Data Scientists

4.7

2 Hours1 Lesson1

Building Multi Agent Systems with Strands Agents

4.7

1 Hour2 Lessons 2

Vibe Coding with Cursor

4.8

1 Hour 30 Minutes 1 Lesson1

Advanced Strands Agents with MCP

4.7

2 Hours4 Lessons 4

GenAI to Build Exciting Games

4.9

1 Hour1 Lesson1

MCP: Unlock AI integrations with real-world demos

4.8

1 Hour2 Lessons 2

ChatGPT as Your Assistant

4.6

2 Hours6 Lessons 6

Ace a Data Scientist Interview in 2025

4.5

2 Hours 30 Minutes 4 Lessons 4

LangChain Fundamentals

4.5

50 Minutes 2 Lessons 2

Introduction to CrewAI: Building a Researcher Assistant Agent

4.7

2 Hours2 Lessons 2

Understanding the working of Neural Networks

4.7

1 Hour2 Lessons 2

Vibe Coding with Replit

4.8

2 Hours6 Lessons 6

Excel : From Beginner to Expert

4.6

2 Hours1 Lesson1

A Complete MLops Journey

4.6

2 Hours3 Lessons 3

Data Analysis with Apache Hive

4.7

1 Hour1 Lesson1

No Code Predictive Analytics with Orange

4.5

45 Minutes 1 Lesson1

Building Intelligent Chatbots using AI

4.5

1 Hour2 Lessons 2

GenAI for Everyone

4.6

4 Hours5 Lessons 5

A B C of Coding to Build AI Agents

4.9

30 Minutes 1 Lesson1

Getting Started with Kimi K2

4.7

2 Hours2 Lessons 2

Getting Started with Tableau

4.5

40 Minutes 2 Lessons 2

How to Build an Image Generator Web App with Zero Coding

4.7

2 Hours2 Lessons 2

Building and Evaluating RAG System

4.6

40 Minutes 1 Lesson1

Guide to Vibe Coding in Windsurf

4.8

30 Minutes 1 Lesson1

Build Products 10x Faster with GenAI

4.8

30 Minutes 1 Lesson1

Building a Collaborative Multi-Agent system

4.7

2 Hours4 Lessons 4

Building Smarter LLMs with Mamba and State Space Model

4.6

1 Hour2 Lessons 2

Nano Banana : Image Magic with Gemini 2.5 Flash

4.8

1 Hour1 Lesson1

n8n - A Complete Guide to Automation Tool

4.8

2 Hours6 Lessons 6

Building ML Pipelines using MLflow & DVC

4.9

1 Hour6 Lessons 6

Generative AI on AWS

4.7

1 Hour3 Lessons 3

Model Deployment using FastAPI

4.5

30 Minutes 6 Lessons 6

Demystifying OpenAI Agents SDK

4.7

30 Minutes 1 Lesson1

Build a Document Retriever Search Engine with LangChain

1 Hour1 Lesson1

Exploring Stability. AI

4.9

45 Minutes 6 Lessons 6

Knowledge Bases & Memory for Agentic AI

4.5

1 Hour1 Lesson1

Building Data Analyst AI Agent

4.6

40 Minutes 1 Lesson1

Building Scalable Industry Applications with RAG and Agents

4.8

1 Hour2 Lessons 2

OpenEngage: Build a complete AI Driven Marketing Engine

4.5

1 Hour1 Lesson1

Building a Deep Research AI Agent

4.5

5 Hours4 Lessons 4

Mastering Multimodal RAG & Embeddings with Amazon Nova & Bedrock

4.8

60 Minutes 3 Lessons 3

Frameworks for effective Problem Solving

4.7

1 Hour6 Lessons 6

Framework to Choose the Right LLM For your Business

4.5

1 Hour3 Lessons 3

Introduction to AI & ML

4.9

3 Hours6 Lessons 6

Microsoft Excel Formulas & Functions

4.8

15 Minutes 7 Lessons 7

Tableau for Beginners

4.7

5 Hours4 Lessons 4

Introduction to Natural Language Processing

4.6

1 Hour20 Lessons 20

Introduction to Python

4.9

1 Hour 15 Minutes 3 Lessons 3

Docker for Absolute Beginners

4.8

1 Hour3 Lessons 3

Foundations of Data Science

4.8

1 Hour 20 Minutes 1 Lesson1

Building Agentic AI System with Bedrock

4.5

3 Hours9 Lessons 9

Build Data Pipelines with Apache Airflow

1 Hour1 Lesson1

Building a Sentiment Classification Pipeline with DistilBert and Airflow

4.6

3 Hours3 Lessons 3

Introduction to Transformers and Attention Mechanisms

4.6

40 Minutes 1 Lesson1

Mastering Agentic Conversation Pattern with AG2

4.6

1 Hour1 Lesson1

Coding a ChatGPT-style Language Model From Scratch in Pytorch

4.6

30 Minutes 1 Lesson1

Navigating LLM Tradeoffs Techniques for Speed & Accuracy

4.8

1 Hour1 Lesson1

Data Preprocessing on a Real-World Problem

4.5

1 Hour 20 Minutes 6 Lessons 6

Getting Started With Large Language Models

4.6

4 Hours4 Lessons 4

Exploring-natural-language processing using deep learning

4.5

30 Minutes 5 Lessons 5

Ensemble Learning and Ensemble Learning Techniques

4.8

2 Hours4 Lessons 4

Evaluation Metrics for Machine Learning Models

4.6

1 Hour3 Lessons 3

Exploring OpenAI o3 and o4-mini

4.7

1 Hour1 Lesson1

Deep Dive Into QwQ-32B

4.8

30 Minutes 1 Lesson1

Build a Resume Review Agentic System with CrewAI

4.8

1 Hour 30 Minutes 3 Lessons 3

Getting Started with OpenAI o3-mini

4.8

30 Minutes 30 Lessons 30

Reimagining GenAI: Common Mistakes and Best Practices for Success

4.8

2 Hours3 Lessons 3

Building LLM Applications using Prompt Engineering

4.7

1 Hour6 Lessons 6

Bagging and Boosting ML Algorithms

4.5

1 Hour 20 Minutes 1 Lesson1

Understanding Linear Regression

4.7

1 Hour1 Lesson1

The A to Z of Unsupervised ML

4.8

2 Hours3 Lessons 3

Build your first RAG system using LlamaIndex

4.9

9 Hours4 Lessons 4

Getting Started with Deep Learning

4.8

1 Hour2 Lessons 2

Dreambooth: Stable DIffusion for Custom Images

4.8

1 Hour2 Lessons 2

Nano Course: Building Large Language Models for Code

4.7

9 Hours 30 Minutes 5 Lessons 5

Building Data Stories using Excel and Tableau

4.7

30 Minutes 2 Lessons 2

Naive Bayes from Scratch

4.5

3 Hours2 Lessons 2

Building Agent using AutoGen

4.5

3 Hours 30 Minutes 2 Lessons 2

Analyzing Data with Power BI

4.5

30 Minutes 1 Lesson1

Foundations of Model Context Protocol

4.8

30 Minutes 1 Lesson1

Revolutionizing Query Resolution with a RAG System Assisted by Agents

4.6

20 Minutes 6 Lessons 6

xAI Grok 3: Smartest AI on Earth

4.5

1 Hour1 Lesson1

DeepSeek from Scratch

4.6

34 Minutes 2 Lessons 2

Getting Started with DeepSeek-AI

4.9

30 Minutes 1 Lesson1

End to end RAG Application Development with LangChain and Streamlit

4.5

1 Hour1 Lesson1

Learning Autonomous Driving Behaviors with LLMs and RL

1 Hour1 Lesson1

GenAI for Quantitative Finance & Control Implementation

4.8

1 Hour1 Lesson1

Creating Problem-Solving Agents with GenAI for Actions

4.5

4 Hours3 Lessons 3

Generative AI - A Way of Life

4.5

30 Minutes 5 Lessons 5

K-Nearest Neighbors (KNN) Algorithm in Python and R

4.8

1 Hour 30 Minutes 9 Lessons 9

Fundamentals of Regression Analysis

4.9

1 Hour9 Lessons 9

Pandas for Data Analysis in Python

4.8

45 Minutes 1 Lesson1

Building a Customized Newsletter AI Agent

4.6

2 Hours4 Lessons 4

Agentic AI Design Patterns

4.5

30 Minutes 1 Lesson1

Build a QA RAG system with Langchain

1 Hour1 Lesson1

Improving Real World RAG Systems :Key Challenges

4.8

34 Hours1 Lesson1

Building Your First Computer Vision Model

4.8

1 Hour 10 Minutes 1 Lesson1

MidJourney: From Inspiration to Implementation

4.6

1 Hour 10 Minutes 2 Lessons 2

Building Text Classification Models in NLP

4.8

38 Minutes 1 Lesson1

Nano Course Cutting Edge LLM Tricks

4.6

19 Minutes 1 Lesson1

Introduction to Data Visualization

4.9

1 Hour5 Lessons 5

Introduction to Business Analytics

4.5

31 Minutes 4 Lessons 4

Introduction to PyTorch for Deep Learning

30 Minutes 4 Lessons 4

Time Series Forecasting using Python

4.7

2 Hours3 Lessons 3

Build Your 2025 Winning Data Science Resume with AI

4.5

2 Hours2 Lessons 2

Essential : SQL Skills for Data Beginners

2 Hours3 Lessons 3

A comprehensive Learning path to become a Data Analyst

4.6

1 Hour1 Lesson1

Mastering Multilingual GenAI Open-Weight for Indic Language

4.6

2 Hours5 Lessons 5

A Comprehensive Learning Path to Become a Data Scientist in 2025

4.8

1 Hour1 Lesson1

Introduction to Cloud

4.7

30 Minutes 5 Lessons 5

Dimensionality Reduction for Machine Learning

4.9

30 Minutes 1 Lesson1

Getting Started with Decision Trees

4.6

30 Minutes 1 Lesson1