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In recent years, the field of digital image processing has undergone significant development due to a wide range of digital products that have been developed and are being extensively used by numerous companies and organizations.
Our Image Processing Course Online is experiencing rapid development and growth due to the significance and wide variety of products in the field. Join the professional and comprehensive Image Processing program at Real Time College!
In response to the demand and need, tech companies are investing significant resources to enhance their capabilities in the field of image processing. The demand for skilled and professional image processing developers is at its peak and is expected to further increase in the coming years.
What Is Image Processing?
Image processing is a way to convert an image into a numerical form and apply specific functions to it in order to obtain an enhanced image and extract useful information for the desired purpose.
In image processing, various operations can be performed. All these operations can assist us in analyzing the information and, accordingly, calculating positions, conducting quality tests for digital products (and other products), and essentially embedding automation and artificial intelligence in almost any selected element.
There are different stages involved in image processing, including importing the image through an optical scanner or a digital camera, analyzing and treating the image, and drawing conclusions accordingly. Moreover, during the course of this program, we will work with common tools such as the NumPy, Pandas, Matplotlib, and OpenCV libraries.
What does the role of an Image Processing professional include?
Image Processing professionals develop methods for identifying elements in images and deriving desired insights sought after by technology and IT companies.
Image Processing professionals can perform a wide range of actions on any image file they wish to modify. Through image processing, they can remove noise, objects, and any details that interfere with the desired image.
An Image Processing professional significantly enhances and sharpens the quality of an image file, pastes and adds parts from other images, and can also automatically extract entities from the image.
To perform image analysis, image enhancement, noise reduction, geometric shape changes, image registration, and three-dimensional image processing, image processing toolbox applications allow you to automate common image processing workflows.
Why Study Image Processing Course at Real Time College
In the Image Processing course, we will learn about practices, methods, innovative approaches, and algorithms for image processing, image restoration, and image analysis. The curriculum of the Image Processing Course Online at Real Time incorporates comprehensive theoretical knowledge and practical exercises.
The lessons in the course focus on the practical knowledge and skills required for the field, and they have been developed in collaboration with technology companies in the industry. The content is continuously updated based on ongoing projects in our development division.
Alex Shoihat
Head of Machine Learning
Alex holds a bachelor's degree in Information Systems (B.Sc.) and a master's degree in Electrical and Electronics Engineering.
Alex is a Machine Learning Engineer at RT. He specializes in the AI field, with over 13 years of experience in project development, management, and transitioning from development to production in various domains such as Linux Embedded.
Alex has experience working with the integration of Machine Learning and Deep Learning in the Computer Vision and Data Analysis field.
Image Processing Curriculum
The Image Processing Certification program is made up of a number of courses (modules).
We know that each of us arrives with a different background and level of knowledge. In order to tailor the content to best fit your needs, you can choose the track that is most suitable for you:
Image Processing Certification studies at the college are currently conducted online.
Comprehensive Track
This track includes all the courses in the program and is designed to make you an expert in the field.
- Designed for students with little to no experience.
- Requires 9 to 12 months to complete.
- 550 academic hours.
Standard Track
This track includes only the courses and content specifically designed for the Image Processing Certification program.
- Designed for students with prior knowledge in the high-tech industry.
- Requires 6 to 7 months to complete.
- 230 academic hours.
Self-Designed Track
This track allows you to select only the specific courses and content that you are interested in and wish to complete.
- Designed for students with experience in the field.
- Requires 1 to 3 months to complete, depending on the courses chosen by the student.
| Image Processing / CV Courses | |||||
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| Machine Learning Fundamentals | 25 academic hours |  Comprehensive Track |
 Standard Track |
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This course presents the theory and fundamentals of Machine Learning, as well as recommended working methods for ML. | |||||
| Scientific Python | 30 academic hours | Comprehensive Track |
Standard Track |
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The "Scientific Python" course at RTG College is part of an advanced learning program that equips students with the necessary skills for advanced analysis of scientific data. Throughout the course, students develop proficiency in the Python programming language and practice using libraries like NumPy, Pandas, and Matplotlib for data processing and analysis. The knowledge is conveyed through hands-on projects, allowing students to apply the knowledge and develop solution-focused abilities in a practical environment. At the end of the course, students conduct in-depth analysis and present their findings in a final project. The course provides you with the tools for breakthroughs in the complex world of data analysis. | |||||
| Machine Learning With Python | 50 academic hours | Comprehensive Track |
Standard Track |
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Python offers a wide range of libraries that can be used for Machine Learning (such as NumPy, SciPy, Matplotlib). In this course, you will learn how to implement the tools from these libraries. Using these tools, we will also implement models that were taught in previous courses. | |||||
| Deep Learning with Tensorflow | 50 academic hours | Comprehensive Track |
Standard Track |
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Deep Neural Networks draw inspiration from the way the human brain functions and represent the most advanced subset of Artificial Intelligence. In this course, you will learn how to develop and test Deep Learning models using the TensorFlow / Keras platforms for Machine Learning and Neural Networks projects. | |||||
| OpenCV | 40 academic hours | Comprehensive Track |
Standard Track |
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In this course you will learn to use Open CV. OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It provides a wide range of tools, functions, and algorithms for tasks related to computer vision and image processing. OpenCV is widely used by researchers, developers, and engineers to develop applications that involve image and video analysis, object detection and tracking, facial recognition, augmented reality, robotics, and more. Its flexibility, efficiency, and extensive community support make it a popular choice for projects that require computer vision capabilities. | |||||
| CUDA | 35 academic hours | Comprehensive Track |
Standard Track |
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The CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) developed by NVIDIA. It allows developers to harness the power of NVIDIA GPUs (Graphics Processing Units) for general-purpose computing tasks beyond just graphics rendering. CUDA enables accelerated parallel processing by utilizing the many cores in modern GPUs to perform calculations simultaneously. This technology is especially beneficial for computationally intensive tasks such as scientific simulations, data analytics, machine learning, and deep learning, as it can significantly speed up the execution of complex computations. | |||||
| Software Programming | |||||
| Linux Admin | 50 academic hours | Comprehensive Track |
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In this course, you will learn how to seamlessly operate a Linux system and techniques to maximize your utilization of Linux's capabilities. The curriculum is divided into two sections.
The first part of the course will cover installation, file management, and permissions. By the end of this part, you will be proficient in managing the system seamlessly. In the second part of the course, you will delve into system configurations, users management, network cards, Linux kernel management, and more. Linux is an open-source, free operating system known for its relatively high security. It provides software testers and developers with efficiency and freedom of action. The vast majority of software applications, such as servers, applications, databases, or internet services, are deployed on Linux operating systems. Therefore, it is critical for software testers to possess knowledge and experience in Linux. This course equips you precisely with such expertise. | |||||
| Python | 90 academic hours | Comprehensive Track |
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The focus is on Python 3, aiming to provide the knowledge and experience required for programming real-world applications in an object-oriented industry. You will learn how to develop software using Python. You will be taught techniques and appropriate tools to professionally develop high-level Python programs suitable for high-tech companies. This is a very practical course in which we will also be using circuit boards. Python is currently considered one of the most popular and sought-after programming languages in the IT industry. Its popularity and widespread use in various industry projects make Python one of the most demanded programming courses. The high demand and diverse employment opportunities make Python highly beneficial to specialize in for a rewarding professional career with multiple growth opportunities. | |||||
| C++ | 90 academic hours | Comprehensive Track |
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This course will cover Object-Oriented Programming using the C++ language, emphasizing polymorphism, multiple inheritance, exceptions, and multithreading. | |||||
| SQL | 30 academic hours | Comprehensive Track |
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In this course, you will learn and practice SQL (Structured Query Language) and gain thorough familiarity with MySQL. The goal of the course is to learn how to communicate and perform various operations with the database. Most software operates with large amounts of data in the background. Nowadays, this data can be stored in different types of databases, like MySQL or Oracle in the backend. During software testing, some of this data needs to be verified, for example, to check if the relevant data is stored correctly in the databases. Therefore, knowledge of database basics and SQL queries is essential. In the course, we will cover topics such as SQL Formal Definitions, The Relational Model, SQL Key Notes, SQL Properties, SQL User Objective, Data Definition Language, and more. | |||||
| AWS | 35 academic hours | Comprehensive Track |
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The course is designed to help you gain a deep understanding of the architectural principles and services of Amazon Web Services (AWS). You will learn how to design and deploy AWS cloud applications using recommended best practices endorsed by Amazon. | |||||
| GIT (Version Control) | 25 academic hours | Comprehensive Track |
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Git is an open-source version control system that serves as a tool for managing code versions and the software development process. Its primary purpose is to help developers efficiently manage code and track changes in software files. In this course, you will learn the core features of Git, workflow techniques, and methods to undo changes or maintain multiple project versions. Additionally, you'll discover how to collaborate effectively with other teams and developers. Designed for programmers seeking the best and most suitable way to manage code development versions, the course covers essential workflow principles, core features, version control, collaboration, and more. | |||||
Admission Requirements
- Basic computer skills (Windows OS).
- Basic knowledge in mathematics.
- No previous programming experience is required.
Who is the Image Processing course suitable for?
- System programmers or engineers studying ML.
- Students interested in specializing in data analysis, business intelligence, or data science.
- Students interested in specializing in computer vision.
Certifications and Credentials
Requirements for eligibility for the certificate:
- Participation in at least 80% of the course hours
- Submission of a final project / final exam with a score of 70 and above
- Obligation to submit course assignments, including exercises, homework, and projects
Upon successful completion of the Image Processing program, you will be awarded a Image Processing Certificate by RTG. This certificate will attest to your high level of knowledge and professionalism.
Why Study Image Processing at RTG
Paying Tuition for Image Processing
Some students turn to personal loans to fund their coding education.
A diverse range of personal lending choices is at your disposal for careful consideration and assessment. Should you opt for a personal loan, be sure to select the one that aligns most effectively with your individual circumstances and financial goals.
Your eligibility for various government aid and scholarship programs may vary depending on your location.
As such, it is recommended that you explore the options and inquire about any scholarships or financial aid opportunities available.
Top Companies Where Our Graduates Work
FAQ
1. University/college graduates with degrees in science who are interested in specializing in the field or as part of the Artificial Intelligence program.
2. Knowledge and experience in operating systems such as Windows and Linux — an advantage.
3. Background and/or experience in programming languages — an advantage.
* Candidate acceptance will be subject to a professional knowledge interview + an exam.
Some potential roles in image processing include:
1. Image Processing Engineer/Scientist: Working on developing and implementing image processing algorithms for various applications such as medical imaging, computer vision, remote sensing, and more.
2. Computer Vision Engineer: Focusing on developing algorithms and technologies that allow computers to understand and interpret visual information from the world, used in applications like facial recognition, object detection, autonomous vehicles, and augmented reality.
3. Data Scientist/Analyst with Image Analysis: Utilizing image processing techniques to extract insights from visual data, contributing to projects involving image-based data analysis and interpretation.
4. Machine Learning Engineer: Combining image processing skills with machine learning techniques to build models that can learn patterns and features from images for predictive analysis and decision-making.
These are just a few examples, as the application of image processing techniques extends to a wide range of fields and industries, reflecting the increasing demand for professionals in this area.
We are aware that the path to a successful career in the field involves practice, building a portfolio, and gaining relevant industry experience. Real Time College uniquely provides extensive experience and real project development from the high-tech market, ensuring that our students graduate with comprehensive and relevant knowledge, coupled with practical experience rather than just theoretical understanding.
Based on our experience in recruitment and project development activities, we know precisely what tech companies require and expect from new employees in their ranks. Accordingly, the curriculum is designed to include the practical aspect of the program.
Currently, all classes in the Image Processing program take place online.
Salary Info Image Processing
The estimated total pay for an Entry Level Image Processing Engineer is $91,981 per year in the United States area, with an average salary of $83,048 per year.
Source: glassdoor.com