Artificial Intelligence Engineering Program
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Simulation of Human Intelligence
Artificial Intelligence Engineering Program
What is AI?
In simple terms, artificial intelligence is a behavior exhibited by machines and systems, similar to that of human beings. In the case of a computer system, its artificially intelligent ability to mimic human behavior stems from its collection and analysis of past activities and data. With each new piece of information, the machine can make corrections to itself so that previous errors won’t resurface and make any necessary adjustments to handle new inputs. This approach enables AI systems to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between different languages.
The artificial intelligence engineer can extract data efficiently from various sources, design smart algorithms, build and test machine learning models, then deploy those models to create AI-powered applications capable of performing complex tasks smartly.
Therefore, Artificial Intelligence is the ability of machines to perform tasks that normally require human intelligence—for example, recognizing patterns, learning from experience, drawing conclusions, making predictions, or taking action—whether digitally or as the smart software behind autonomous physical systems.
Artificial Intelligence Program at GU adopts the general knowledge and skills issued by the National authority for quality assurance and accreditation of education (NARS) for computer science graduate. The curriculum offered has been studied and referenced in the following universities: Stanford University, Carneige Mellon University and Ain Shams University. Learners will be capable of developing a smart software that uses machine learning and deep learning and will apply smart software to engineering applications.
In order to receive your degree, you need to study the following credit hours:
University requirement: 20 Credit Hours.
Mathematic & Basic Science: 39 Credit Hours.
Computer Science & Engineering: 36 Credit Hours.
AI Science & Engineering: 39 Credit Hours.
Advanced specially requirement: 18 Credit Hours.
Biomedical informatics: 0 Credit Hours.
Project & Training: 8 Credit Hours.
Total: 160 Credit Hours.
The program considers developing smart software that depends on machine learning, deep learning, Logic-based AI, Natural Language Processing, and Robotics.
The graduate of the Artificial Intelligence Engineering program has all the capabilities of computer Engineering program graduates. Also, the graduates of the Artificial Intelligence Engineering program have the following characteristics:
- The ability to develop smart software that uses machine learning and deep learning.
- The ability to apply smart software to engineering applications.
- Build AI models from scratch and help the organization's different stakeholders, such as product managers and employees, understand what results they gain from the model.
The Program will open up career opportunities in the international companies specialized in AI & ICT. Graduates may work in several Career Fields such as: Self-driving car manufacturers, Factories and companies operating in smart systems, Robot’s manufacturers, Smart home components manufacturers, Ministries and government agencies related to smart applications, Manufacturers of smart personal health devices, etc.
Since several industries around the world in different domains such as healthcare and education use Artificial Intelligence, there has been exponential growth in career opportunities within the field of AI. Some of these job roles are:
- Owns a Startup
Artificial Intelligence Engineers have a great opportunity to start their own AI startups.
- AI Developer
An AI developer works closely with electrical engineers and develops software to create artificially intelligent robots.
- Machine Learning Engineer
Machine learning engineers build predictive models using vast volumes of data. They have in-depth knowledge of machine learning algorithms, deep learning algorithms, and deep learning frameworks.
- Data Scientists
Data scientists collect, clean, analyze, and interpret large and complex datasets by leveraging both machine learning and predictive analytics.
- Business Intelligence Developer
They're responsible for designing, modeling, and analyzing complex data to identify the business and market trends.
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