Level: Beginner
Create Image Recognition Systems Using Computer Vision & CNNs
Build computer vision systems using CNNs for image classification, object detection, and real-world AI applications.
4.9
2.3k+ learners
Duration
11 hr 25 min
Learners
2.3k+ Enrolled Students
Session Recording
Lifetime Access
Post Session
Mentor support
Session Schedule
11
Apr
Session 1 • Saturday • 2h 30m
8:00 pm to 10:30 pm
12
Apr
Session 2 • Sunday • 3h 15m
2:00 pm to 5:15 pm
18
Apr
Session 3 • Saturday • 3h 20m
5:00 pm to 8:20 pm
19
Apr
Session 4 • Sunday • 2h 20m
8:00 pm to 10:20 pm
Get Life Time Access
₹1,099
₹1,499
Discount 26% off
Course Fee
₹1,099
Worth of
₹1,499
Discount
26% Off
Includes
• Expert Designed Curriculum
• Doubt Clearing Session
• Forever Community Access
Outcomes Of This Sessions
What you will build during the live classes.
About the Project
Develop image recognition systems using convolutional neural networks. Work on classification and detection tasks using real datasets. Understand model architecture, training workflows, and deployment strategies used in production AI systems.
See LiveAfter this course, you can
Build a responsive website from scratch
Publish a project to your GitHub portfolio
Master HTML, CSS, and layout systems
Showcase a live project to recruiters
Course Curriculum
Expand or explore the full learning path.
Pre-Requisites Content
Complete this section before the live session to get the most out of the course. You'll unlock this content immediately after enrolling.
Python and virtual environment setup
20 min
Installing TensorFlow / PyTorch and OpenCV
25 min
Dataset download and folder structuring
15 min
Matrix operations and convolution intuition
25 min
Neural network fundamentals recap
20 min
Understanding image formats and channels
15 min
Image augmentation techniques
20 min
Live Session Content
This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.
Computer vision fundamentals
30 min
Image preprocessing and augmentation
30 min
Dataset preparation for CNN training
25 min
CNN layers and architecture breakdown
35 min
Building image classification models
30 min
Feature extraction using CNNs
25 min
Accuracy metrics and confusion matrix
30 min
Hyperparameter tuning strategies
30 min
Transfer learning techniques
25 min
Face recognition system implementation
30 min
Object detection workflows
30 min
Deploying image recognition demo app
30 min
Post Session Study Material
This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.
Medical image diagnosis case study
35 min
Object detection project walkthrough
35 min
Scaling computer vision models in production
30 min
Improving model robustness and accuracy
25 min
Train and evaluate a custom CNN model
50 min
Build an image classification demo interface
30 min
Requirements
What you should have before starting the course.
Laptop with minimum 8GB RAM (GPU preferred)
Intermediate Python programming knowledge
Basic understanding of deep learning
Familiarity with image datasets
Interest in building real-world computer vision systems
Tools you are going to use
OpenCV
TensorFlow
PyTorch
Keras
Python
NumPy
Learn From Expert Instructor
Meet the mentors leading the live sessions.
Aarav Sharma
Senior Frontend Engineer, StudioLabs
Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.
LinkedIn
Ananya Mehta
Design Technologist, CraftLabs
Ananya blends design and code to help learners ship portfolio-ready projects.
LinkedIn
Kabir Sayed
Frontend Mentor, PixelWorks
Kabir focuses on clean code, accessibility, and practical frontend delivery.
LinkedInYou should join this course if you
Students & Fresh Graduates
Build a strong portfolio
Learn from live mentors
Get feedback on your work
Working Professionals
Upgrade frontend skills
Ship real projects
Join a peer community
Career Switchers
Structured learning path
Hands-on practice
Guided sessions
Freelancers & Creators
Build client-ready sites
Improve delivery speed
Learn modern workflows
What you will get after completing this course
Receive an official course completion certificate
Earn skill-focused feedback from mentors
Showcase your project in the Shattak community
Access lifetime notes and references
Stay connected with instructors for guidance
Completion bonus
Certificate access, community showcase, and lifetime mentor guidance.
Hear From Learners Who've Taken This Course
Honest feedback from learners who completed the live sessions.
4.8
24
Clear structure, solid examples, and a fast pace that keeps you engaged.
Riya Jain
B.Tech, NIT Trichy
4.6
18
Practical sessions with feedback that helped improve my portfolio.
Kabir Singh
Frontend Intern, PixelWorks
4.9
12
Loved the structure and the live walkthroughs.
M
Meera Patel
Design Graduate
Join Our Community, Ask Questions
Frequently Asked Questions
Students, working professionals, and career switchers who want to build job-ready web projects.
Basic familiarity with HTML or CSS is helpful, but the course includes beginner-friendly guidance.
Yes, recordings are shared after each live session.
Mentors provide live feedback and follow-up notes during the sessions.
Yes, you can ask questions in the community group and during live office hours.
Starting From
11 Apr - 8:00 pm
Live Session
11Hr 25Min
Get Life Time Access
INR 1,099
INR 1,499
26% off
Get Life Time Access
INR 1,099
INR 1,499
26% off