Build a facial emotion recognition system using Python, OpenCV, and deep learning models. Detect emotions like happy, sad, angry, and surprise from facial expressions.
Beginner-friendly. Certificate included.
By the end of this course, you'll have the skills to land your first computer vision job or freelance clients.
Learn how AI analyzes facial expressions to detect human emotions in real time.
Use Python with OpenCV and pre-trained CNN models to classify emotions like happy, sad, angry, and more.
Build a real-time emotion recognition system using a webcam to analyze user expressions dynamically.
Store detected emotions with timestamps in a database for emotional behavior tracking and reports.
Design an engaging GUI that displays the video feed and detected emotions in real time..
Finish the course and receive a verified certificate of success.
Muhammad Yaqoob is the founder of Tentosoft Pvt Ltd and a seasoned Computer Vision expert. With 10+ years of experience and over 5,000+ students taught globally, he brings deep industry knowledge and a passion for practical, hands-on learning.
8 weeks of comprehensive training with 50+ lessons and 10+ hours of content
Facial Emotion Detection is a computer vision technology that identifies human emotions from facial expressions using AI. It plays a vital role in fields like healthcare, marketing, and human-computer interaction.
Course Introduction and Features
Detect emotions from faces
Real-time emotion tracking
Setting up the Python environment involves installing Python, essential libraries like OpenCV and TensorFlow, and a code editor. This foundation allows smooth development and testing of AI-based computer vision applications.
Installing Python
VS Code Setup for Python Development
This project involves detecting human emotions using facial expressions through machine learning and deep learning models. It combines datasets, model training, and inference to classify emotions like happy, sad, angry, or neutral.
Facial Emotion Detection Project Overview
Detect emotions via face
Open Colab in browser
Google Colab is a free cloud-based Jupyter notebook environment. Setting it up allows running Python code with GPU support, enabling faster development and testing of AI and deep learning models.
Set up Google Colab
Open Colab in browser
Fast model development
The dataset consists of facial images labeled with emotions. Downloading and preprocessing this dataset is the first step in training a model to classify facial expressions accurately using deep learning techniques.
Facial Emotion Detection Dataset Download
Download facial image data
Essential for emotion tasks
Dataset Visualization focuses on representing the distribution and characteristics of the facial emotion dataset using visual tools. Techniques like emotion count bar charts, sample image grids, and class balance plots help in understanding data quality, class imbalance, and sample diversity before training the model.
Dataset Visualization
Plot emotion class counts
Prep for better training
Pre-trained weights for YOLOv9 help in initializing the model with learned features, significantly improving training speed and accuracy. These weights are downloaded before beginning the fine-tuning or inference process.
Pre-trained yolov9 model weight file download
Use pretrained model
Needed for inference tasks
YOLOv9 (You Only Look Once version 9) is a cutting-edge real-time object detection model. It’s known for high speed and accuracy, making it suitable for detecting faces and emotions in live video feeds.
yolov9 model info
Latest YOLO version
Ideal for emotion tracking
Efficient and powerful
The YOLOv9 model code is structured to include input preprocessing, model architecture definition, training loops, and loss functions. Each component works together to accurately detect and classify facial features and emotions.
yolov9 model code explanation
Preprocess input images
Detect facial features
Supports real-time tasks
Model training involves feeding the dataset into YOLOv9, adjusting weights using backpropagation, and optimizing for accuracy. This phase is essential for teaching the model to recognize various facial emotions effectively.
yolov9 model training
Feed data to YOLOv9
Monitor loss and metrics
Core learning phase
Inference is the process of using a trained model to predict emotions from new facial images. It involves image preprocessing, model loading, and generating output labels representing different emotional states.
Model Inference Code Explanation
Load trained model
Preprocess input image
Is This Course Right for You?
Kickstart your AI journey with structured, hands-on learning.
Build a portfolio that recuriters can't ignore.
Add powerful AI/CV features to your apps and software.
Upskill for higher-paying, future-ready tech roles.
Build Smarter, more intelligent applications.
Transition into AI even with zero background.
One-time payment for lifetime access to all course materials and updates
Rorem ipsum dolor sit amet, consectetur adipiscing elit. Etiam eu turpis molestie, dictum est a, mattis tellus. Sed dignissim, metus nec fringilla accumsan, risus sem sollicitudin lacus, sed risus a, mattis tellus. Sed dignissim, metus nec fringilla accumsan, risus sem sollicitudin lacus, sed risus .
Highly recommended for small teams who seek to upgrade their time & perform.
₹ 6720 inclusive of GST ₹ 13999
52% OFF🎁 Coupon Code:
Secure Payment Gateway
You can add this certificate in your Resume! Share it with your LinkedIn network 🚀
This Certificate Is Proudly Presented To
This certificate is given to Jacqueline Thompson for her achievement in the field of education and proves that she is competent in her field.
Signature
CERTIFICATE
Date of Event
Get full project code for 20+ real-world applications – build, customize, and learn hands-on with working solutions.
Join weekly live Q&As to resolve queries and deepen your understanding with real-time support
Enhance your confidence with communication tips, resume builder templates, and personal branding guides tailored for tech careers.
Get feedback, share wins, and grow with other learners in a safe and supportive environment.
Enroll today to claim all bonuses before the offer expires!
Get Instant Access