Full Stack Computer Vision Career Path- Beginner

Become a Computer Vision specialist in just 4 months through intensive hands-on training and learn how to build your own computer vision model from scratch.
20 Videos
No Coding Experience Required
45 Assignments
Self Paced

About This Course

Dive into the powerful world of data manipulation with Python libraries for data science like NumPy and Pandas. Explore how to efficiently work with multidimensional arrays, perform data wrangling operations, and analyze large datasets. These skills are crucial for anyone aspiring to become a data scientist, data analyst, or machine learning engineer.
What You'll Learn
Core Computer Vision Skills
  1. Grasp the core concepts and applications of computer vision in various industries.
  2. Master essential image processing skills such as resizing, cropping, rotating, blurring, sharpening, and edge detection.
  3. Gain hands-on experience with OpenCV for image reading, displaying, saving, and basic image manipulations.
  4. Learn techniques for detecting and describing features using methods like Harris corner detection, SIFT, and ORB.
  5. Understand object detection methods and algorithms like bounding boxes, Haar cascades, and HOG for identifying and locating objects.
  6. Utilize neural networks and Convolutional Neural Networks (CNNs) for image classification tasks, and leverage transfer learning to enhance performance with less data.
Tools and Technologies
  1. OpenCV: Powerful library for computer vision tasks, including image processing and manipulation.
  2. Python: Programming language used for implementing computer vision solution.
  3. TensorFlow: Framework for building and training deep learning models.
  4. Keras: High-level neural networks API for simplifying deep learning model development
  5. Scikit-Image: Library for image processing in Python.
communication and business skills for the field of computer vision:
  1. Stakeholder Engagement: Clearly communicate the benefits and limitations of computer vision solutions to stakeholders, ensuring their expectations are managed and aligned with project goals.
  2. Technical Documentation: Create detailed and accessible documentation of computer vision models, workflows, and results to facilitate understanding and collaboration among team members.
  3. Project Management: Efficiently plan, coordinate, and monitor computer vision projects, ensuring timely delivery and alignment with business objectives.
  4. Data Visualization: Present complex computer vision data and insights in a clear and compelling manner to non-technical stakeholders, aiding in decision-making processes.
  5. Cross-Disciplinary Collaboration: Work effectively with diverse teams, including data scientists, engineers, and business professionals, to integrate computer vision solutions seamlessly into business operations.
Business Problem Solving and Design Thinking
  1. Analyze and define business needs to align computer vision solutions with organizational goals.
  2. Design scalable computer vision architectures using tools like OpenCV and deep learning frameworks.
  3. Implement strategies to optimize cost-efficiency and performance using cloud-based computer vision services and performance monitoring tools.
  4. Develop secure and compliant computer vision solutions by leveraging encryption, access control, and compliance standards.
  5. Apply design thinking principles to create innovative and user-centric computer vision applications.
  6. Design and implement real-time computer vision systems that process and analyze video streams efficiently.
Curriculum Designed For Career Success
Module 1: Introduction to Computer Vision
2 Lectures

Gain a foundational understanding of computer vision and its applications in various industries. Learn the basic terminologies and concepts essential for working with images and videos.

  • 1.1 What is Computer Vision?:
    • Understand the core concepts and objectives of computer vision, including applications in healthcare (e.g., tumor detection), automotive (e.g., autonomous driving), and retail (e.g., automated checkout).
  • 1.2 Basic Terminologies:
    • Larn about pixels, images, channels, and how they form the basis of computer vision tasks, which are fundamental concepts applicable across all computer vision projects.
Module 2: Image Processing Basics
3 Lectures

Explore essential image processing techniques to manipulate and enhance images for analysis.

  • 1.1 Image Representation:
    • Understand the differences between grayscale and colour images and their use cases, such as medical imaging where grayscale images are used for X-rays and MRIs.
  • 1.2 Image Operations:
    • Master techniques for resizing, cropping, and rotating images, crucial for preprocessing images in facial recognition systems.
  • 1.3 Filtering:
    • Apply blurring, sharpening, and edge detection to improve image quality, which is vital for enhancing satellite images used in environmental monitoring.
Module 3: Introduction to OpenCV
3 Lectures

Get hands-on with OpenCV, a powerful library for computer vision tasks.

  • 1.1 Installation and Setup:
    • Learn how to set up OpenCV in your development environment, similar to how startups set up environments for rapid prototyping.
  • 1.2 Reading and Displaying Images:
    • Acquire skills to read, display, and save images using OpenCV, essential for developing applications that process and analyze image data in real-time.
  • 1.3 Basic Image Manipulation:
    • Perform basic image transformations and manipulations with OpenCV, foundational for creating photo editing tools and filters.
Module 4: Feature Detection and Description
3 Lectures

Learn techniques to detect and describe features in images for various computer vision applications.

  • 1.1 Corner Detection:
    • Understand Harris corner detection and its applications in detecting features for 3D reconstruction in robotics.
  • 1.2 Feature Descriptors:
    • Explore SIFT, ORB, and other descriptors for robust feature matching, important for matching keypoints in satellite images for geospatial analysis.
  • 1.3 Matching Keypoints:
    • Learn techniques for matching keypoints between images, useful for creating panoramic images from multiple photographs.
Module 5: Object Detection
3 Lectures

Delve into object detection methods to identify and locate objects within images.

  • 1.1 Understanding Bounding Boxes:
    • Understanding Python syntax and data types.
  • 1.2 Object-Oriented Programming (OOPs):
    • IGrasp the basics of bounding for object detection, which is crucial for implementing security systems that detect and track intruders.
  • 1.3 Control Structures and Functions:
    • Explore algorithms like Haar cascades and HOG for detecting objects, commonly used in face detection in cameras and mobile phones.
Module 6: Image Classification with Deep Learning
3 Lectures

Utilize deep learning to classify images into categories.

  • 1.1 Introduction to Neural Networks:
    • Understand the basics of neural networks and their applications in image classification, such as classifying medical images to detect diseases.
  • 1.2 Convolutional Neural Networks (CNNs):
    • Learn how CNNs work and why they are effective for image classification, essential for identifying defects in manufacturing processes through image analysis.
  • 1.3 Training a Simple CNN:
    • Hands-on training of a CNN for a basic image classification task, such as building a system to categorize images on social media platforms.
Module 7: Transfer Learning
2 Lectures

Leverage pre-trained models to enhance image classification tasks with less training data.

  • 1.1 Using Pre-trained Models:
    • Explore how to use pre-trained models for various tasks, accelerating the development of custom image classifiers in limited data scenarios.
  • 1.2 Fine-tuning Models:
    • Learn techniques for fine-tuning pre-trained models to suit specific needs, such as adapting general object detectors for specific industrial applications.
Module 8: Semantic Segmentation
2 Lectures

Learn to classify each pixel in an image into a meaningful category.

  • 1.1 Understanding Semantic Segmentation:
    • Explore the concepts and applications of semantic segmentation, such as segmentation medical images to identify different tissue types.
  • 1.2 Introduction to U-Net Architecture:
    • Understand the U-Net architecture used for image segmentation tasks, like using U-Net for automated tumor segmentation in radiology.
Case Studies

Industry Case Studies You Will Work On

Advanced Fraud Detection Techniques in Banking
Learn the skills and knowledge to detect fraudulent activities in credit card transactions, ensuring financial security for banking institutions and customers.
Skills learned:
Data Preprocessing
Feature Engineering
Model Evaluation
Anomaly Detection Techniques
Operational Efficiency Optimization in Banking
Develop the tools and techniques to forecast call volumes in banking call centers, improving resource allocation and enhancing customer service efficiency.
Skills learned:
Time Series Forecasting
Model Evaluation
Operational Optimization Techniques
Customer Segmentation Strategies for Banking Marketing
Learn how to segment bank customers based on their behavior and demographics to optimize marketing campaigns for targeted customer engagement and retention.
Skills learned:
Data Visualization
Clustering Algorithms
Customer Profiling techniques
Sales Prediction and Optimization in Banking
Learn how to predict sales performance and optimize sales strategies for banking products and services that drive revenue growth and customer acquisition.
Skills learned:
Predictive Modeling
Sales forecasting
Model Interpretation Techniques
Real-time ATM Fraud Detection in Banking
Equip yourself with the skills to detect fraudulent activities in ATM transactions, safeguarding banking institutions and customers from financial losses.
Skills learned:
Data Preprocessing
Model Evaluation
Anomaly Detection Techniques
Predictive Modeling for Loan Default Prediction in Banking
Predict loan default probabilities that enable banks to assess credit risk and make informed lending decisions.
Skills learned:
Feature engineering
Risk Assessment
Model Evaluation Techniques
Predictive Analytics for Customer Lifetime Value Estimation
Learn how to estimate the lifetime value of bank customers, facilitating targeted marketing strategies and personalized customer experiences.
Skills learned:
Customer Segmentation
Predictive modeling
Model Evaluation
Personalized Cross-Selling Recommendations in Banking
Gain the skills to build recommendation systems for cross-selling banking products and services based on customer behavior and preferences.
Skills learned:
Collaborative Filtering
Recommendation Algorithms
Customer Profiling Techniques
Machine Learning for Mortgage Risk Assessment in Banking
Learn the tools to assess mortgage loan risks, enabling banks to make informed lending decisions and manage credit risk effectively.
Skills learned:
Feature Selection
Risk Modeling
Credit Scoring Techniques
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Make A Life-Changing Career Choice

IN-DEMAND CAREER
45%
Growth in demand for Data Analysts in the next 5 years
MASSIVE JOB OPENINGS
1M +
Job openings and counting for Data Analysts worldwide.
BIGGEST GROWING INDUSTRY
$349.6 Billion
Amount industry is set to grow by 2030
HIGH ENTRY- LEVEL SALARY
₹8-14 LPA+
Current average CTC for entry-level Data Analysts in India.
Don't Just Learn. Specialize.
India's only course with industry specialization in the domain of your choice.
50+
Industry case studies
10+
Problem solving frameworks
Experience 360° deep specialized learning
50+
Assignments
10+
Industry Projects
100+
Hours of Learning
Learn with Ai
Our program incorporates modern Gen AI based workflows for data science so that you are equipped with the tools of the future.
Made for working professionals
Enjoy flexible learning options. Go at your own pace or learn through live classes with industry experts.
Placement support from dedicated counselors
Mock interviews with senior industry leaders
Craft the perfect resume
Access our network of partner companies

Land Your Dream Job With
Full Placement Support

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Craft a Winning Resume

Get expert help building a resume that showcases your data skills.
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Nail Your Interview

Practise mock interviews with our experienced mentors to ace the recruitment process. 
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Company Screening & Selection

Benefit from our extensive industry network and connections to unlock exciting career opportunities.
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The team was thrilled with the quality of instruction provided. We have requests from teams from other departments to undertake the training as well. 
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Avinash Purohit
DGM, Canara Bank
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Is This Bootcamp Right For You?
Are you looking for a career change?
Do you want to switch from your current job to a more lucrative career as a data analyst in finance ?
Do you want a promotion?
Are you a banking or finance professional looking to upgrade your career with the most sought after skill in today’s market - data analytics ?
Are you a beginner to data analytics?
Are you a recent graduate looking for a comprehensive program to teach you everything you need to know to launch your career as a data analyst in the financial sector ?
If you answered "Yes" to any of these questions, SkillCamper's Data Analyst Bootcamp is the perfect fit for you!

What makes us different

Youtube Tutorials& Courses
Live classes
No learner support
No access to any mentor
No live classes
No accountability
No time commitment
SkillCamper
16 weeks course
1:1 Mentorship
Access to industry experts
Live classes with experts
Dedicated academic counselors to ensure you complete course requirements
15-20 hours of time commitment per week - designed for working professionals
Other Bootcamps &Degree Programs
20-60 weeks course
1:1 support may or may not be available
Access to industry may or may not be available
Live classes only
Accountability through assignments and grading
Full-time commitment - not made for working professionals
Online CertificationProgram
3-4 weeks course
No learner support
No access to industry experts
No live classes
Limited accountability
8-10 hours per week of time commitment- suited to working professionals

“The mentors at SkillCamper teach very well, making all the concepts easy to understand. ”

Their teaching style is clear and effective, and I am grateful for their guidance. I hope they continue this excellent approach in the future.
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Ravi Prakash
Automation Test Analyst

“SkillCamper's Data Analytics Bootcamp is fantastic. ”

I had tried learning some data analytics tools through free platforms, but it wasn't enough to get a good opportunity. SkillCamper goes beyond just teaching tools; they focus on domain expertise, which is essential today. The course material is very practical, and I feel like I'm gaining valuable skills. Highly recommended!
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Sanjay Shah
Graduate in BSC-IT

“I'm doing the Data Analytics Bootcamp at SkillCamper, and it's great. ”

Even though I don't have a tech background, the mentors explain things in a simple way that I can understand. The projects and the friendly community make learning fun and helpful. I highly recommend SkillCamper for anyone new to data analytics!
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Ashish Lodhe
Graduate in BSC-IT

“The course is going well and the mentors are very supportive. ”

As a student from a non-tech background, I find their teaching style easy to follow. They explain everything in simple terms and help with any questions. I highly recommend SkillCamper for anyone starting from scratch! 
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Suman M-
Graduate in BSC-IT
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Testimonials

Alumni Success Stories

From career switchers to college grads, we have helped a diverse range of learners kickstart & progress rapidly in their data science careers. 
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Live Interaction

Self paced

Fee Structure

₹ 75,000

₹ 50,000

Curriculum & Course Materials

Live coding environment

AI-based learning platform

100+ hours of instruction

20+ assignments

10+ banking & finance case studies

Banking & finance domain focused curriculum

Capstone projects

Live Classes

Flexible study options

Cancel anytime in first 7 days, full refund

Mentors

15+ hours of sessions with industry veterans & experts

Personalized mentorship by course instructors

Unlimited 1:1 doubt solving sessions

Career Support

Personalized placement assistance

1:1 mock interviews with industry experts

Soft-skills training module

Essential digital tools for digital workplace module

Interview preparation module

Masterclass on resume building & LinkedIn

Access to curated companies & jobs

Live Interaction

Self paced

Fee Structure

$599

$299

Curriculum & Course Materials

Live coding environment

AI-based learning platform

100+ hours of instruction

20+ assignments

10+ banking & finance case studies

Banking & finance domain focused curriculum

Capstone projects

Live Classes

Flexible study options

Cancel anytime in first 7 days, full refund

Mentors

15+ hours of sessions with industry veterans & experts

Personalized mentorship by course instructors

Unlimited 1:1 doubt solving sessions

Career Support

Personalized placement assistance

1:1 mock interviews with industry experts

Soft-skills training module

Essential digital tools for digital workplace module

Interview preparation module

Masterclass on resume building & LinkedIn

Access to curated companies & jobs

Frequently Asked Questions

What technologies will I learn in the Computer Vision Bootcamp?
You’ll learn essential tools like OpenCV for image processing, TensorFlow and Keras for deep learning, and various techniques for object detection and image classification. These technologies are widely used in AI and computer vision applications, helping you build industry-ready skills.
Do I need any prior experience to join the Computer Vision Bootcamp?
No prior experience is required. This course is beginner-friendly, and we’ll guide you step-by-step from the basics of computer vision to advanced model-building techniques. Whether you’re new to programming or AI, this bootcamp is designed to get you up to speed.
How long does the Computer Vision Bootcamp last, and can I learn at my own pace?
The bootcamp spans 4 months, and you can learn flexibly at your own pace or join live classes with industry experts. With an expected time commitment of 15–20 hours per week, the bootcamp is ideal for working professionals looking to balance learning with their current schedules.
What will I learn during the Computer Vision Bootcamp?
You’ll explore image processing, feature detection, object detection, image classification, transfer learning, and semantic segmentation. You’ll gain practical skills by building computer vision models from scratch and solving real-world problems.
Will I have access to the course materials after completing the bootcamp?
Yes, you’ll retain lifetime access to all course materials, including video lessons, recorded sessions, and project files. This allows you to revisit content and continue practising even after the bootcamp ends.
What kind of career support will I receive during and after the bootcamp?
You’ll receive 1:1 mentorship, personalised resume-building workshops, and mock interviews with industry experts. Additionally, you’ll have access to our network of partner companies to help you find job opportunities in AI and computer vision.
What makes this Computer Vision Bootcamp different from others?
Our bootcamp offers real-world projects that give you hands-on experience with computer vision. You’ll also receive 1:1 mentorship, flexible learning options, and a 7-day money-back guarantee, so you can explore the course risk-free.
What is the cost of the bootcamp, and are there payment options?
The bootcamp costs ₹75,000, and we offer easy EMI payment plans to make the course more affordable. You can try the program with our 7-day no-questions-asked money-back guarantee to ensure it’s the right fit for you.
What types of projects will I work on during the bootcamp?
You’ll work on hands-on projects like object detection, image classification, and semantic segmentation. These projects are designed to help you apply what you’ve learned to real-world problems, building a portfolio that showcases your computer vision skills.
How will this bootcamp help me start a career in computer vision?
By the end of the bootcamp, you’ll have built a strong portfolio of computer vision projects and gained hands-on experience with industry-relevant tools. Our career support, including mock interviews and access to job opportunities, will help you confidently enter the job market in AI or computer vision.
I don’t have a tech background; can I still take this course?
Absolutely. This course is beginner-friendly and covers essential computer vision skills starting from scratch.
What type of job support do you provide after completing the course?
We offer comprehensive placement assistance, including resume building, mock interviews, and leveraging our network of industry partners.
How do you prepare students for the job market?
We equip students with industry-relevant skills, help craft winning resumes, and provide mock interview practice with experienced mentors.
Do you guarantee a job after completing the course?
While we do not guarantee a job, we provide extensive support to help you become highly competitive in the job market.
Can you help me find a job in any specific industry?
Our job assistance is generalized; we prepare you for a variety of roles in the data science field rather than focusing on specific industries.
What is the cost of the Data Science bootcamp?
The cost varies depending on the program. Our full bootcamp is priced between ₹50,000 and ₹75,000, depending on whether you choose self-paced or live instruction.
 Are scholarships available for the courses?
Yes, we offer scholarships that can cover up to 70% of the tuition fees, making our courses more accessible to a wider range of students.
What is included in the course fee?
The fee includes access to all course materials, live coding sessions, AI-based learning platform, case studies, capstone projects, and mentorship from industry experts.
What payment options are available for the course fees?
We offer flexible payment options, including easy EMIs, and you can cancel anytime in the first 7 days for a full refund.
Is financial aid or other support available aside from scholarships?
While our primary financial support is through scholarships, our enrollment advisors can also assist you with payment plans and financing options to help manage the cost of your education.

Ready to become a Data Scientist that industry loves to hire? Apply Now. 

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What technologies will I learn in the Data Science bootcamps?
You will learn Python, R, SQL, Power BI, Tableau, Excel, Pandas, Numpy, Matplotlib, Seaborn, and PySpark.