Interesting Courses - Computer Science

ICS435

Disruptive Technology

Innovation-driving technologies, Artificial Intelligence, Robotics, Digital Platforms, Internet of Things, Social media. Strategies for sustainable business growth, transforming traditional products, services, Modern technology for organizational change, adapting to market shifts, evolving consumer behavior, changing technology landscapes.

ICS434

Artificial Intelligence Quality Assurance and Model Auditing

Evaluating the quality, Reliability of artificial intelligence systems, Model auditing, Risk assessment. Testing model performance, Designing governance frameworks. Practical skills in auditing artificial intelligence models, Document findings, Presenting recommendations, Deployment in real-world applications.

ICS430

Cloud-based Artificial Intelligence and Data Analytics

Exploring the use of cloud platforms for large-scale data processing, artificial intelligence model development, analytical system architecture. Development of skills in cloud-based tools, deep data analytics, designing scalable and solutions.

ICS429

Artificial Intelligence for Robotics and Autonomous Systems

Development on Artificial Intelligence techniques for robotics and autonomous systems, perception, navigation, autonomous decision-making. The build of intelligent robotic prototypes, evaluation of performance in real-world scenarios.

ICS428

Generative Artificial Intelligence and Large Language Models

The concepts, technologies, applications of Generative Artificial intelligence and Large Language Models. Developing skills in building generative prototypes, analyzing model behavior, evaluating performance and risks.

ICS427

Ethical and Responsible Artificial Intelligence

Exploring ethical principles, Risk management, Governance in Artificial Intelligence development, deployment. Learning impacts assessment, designing systems, applying Artificial Intelligence to systems.

ICS422

Internet of Things and Applications

Principles and concepts of the Internet of Things, Ideologies, Architectures. Case studies, Platforms in system development, Hardware, Software components. Communication protocols. Embedded programming, Applications of the Internet of Things.

ICS340

Intelligent Systems Design and Applications

Designing, Developing, Evaluating intelligent systems for autonomous decision-making across applications. Learning problem analysis, Intelligent system to architecture design, prototype development.

ICS328

Natural Language Processing

Processing, Understanding language data, Usage of Natural Language Processing techniques. Building, Analyzing, Evaluating Natural Language Processing models for practical applications, gaining the ability for designing systems, Interpreting, Generating human language.

ICS327

Deep Learning

The principles and architectures of deep learning, Model development, Training, Evaluation for real-world applications. Developing skills in building neural network models, performing Deep Data analysis, Applying deep learning solutions.

ICS326

Machine Learning and Implementation

The foundational principles of machine learning, Data preparation, Model development, Evaluation techniques, Practical deployment. Technical problem-solving, Deep data analysis, the ability to design and implement machine-learning prototypes.

ICS316

Introduction to Data Science

Concepts and principles of data science, Data preparation, Data cleaning, Exploratory data analysis, Predictive analysis, Prescriptive analysis, Conditional analysis formats. Challenges in data science, Basic data science tool usage, applying statistics to data science, Using machine learning for data analysis.

ICS401

Ethical Hacking and Pentesting

Ethical hacking, Penetration testing, Planning, Reconnaissance, Scanning, Post-exploitation hacking, Reporting results. Vulnerability, Solutions mitigate the risk of attack, Intrusion detection, exploiting any vulnerability in the target network environment, avoiding hacking, preventing hacking, understanding protection approaches computer network attacking.

ICS311

Cybersecurity

Fundamental concepts and scope of cybersecurity, cybersecurity objectives and threat landscape, cyber risks, vulnerabilities, and attack vectors, principles of information security and risk management, network and cloud security fundamentals, web and application security basics, data protection and privacy, identity and access management, security monitoring and incident response, cybersecurity governance, policies, and compliance, ethical, legal, and professional issues in cybersecurity, cybersecurity best practices for individuals and organizations; case studies and analysis of cybersecurity incidents.

ICS310

Blockchain and Cryptography Technology

Foundations of blockchain technology from multiple perspectives, Key concepts, Developments around cryptocurrencies, Distributed ledger systems, Basic components of a blockchain, Operations underlying algorithms. Hashing, Cryptography foundations, post-quantum cryptography.

ICS305

Deep Learning and Advanced Artificial Intelligence

Introduction to machine learning, statistical pattern recognition, learning theories, Supervised learning, generative learning, discriminative learning, parametric learning, non-parametric learning, artificial neural networks, supporting vector machines. Unsupervised learning, Clustering, Dimensionality reduction, kernel methods, Discussion of the applications of machine learning, Robotic control, Data mining, Autonomous navigation, Bioinformatics, Speech recognition, Text processing, Web data processing.

ICS206

Cloud Computing

Concepts and principles of cloud computing architecture, cloud creation and components, Services on cloud computing platforms, Software as a service (SaaS), Platform as a service (PaaS), Infrastructure as a service (IaaS), Data storage services, Leveraging cloud computing, Basic cloud security, Basic tools and technologies for cloud design.

ICS207

Artificial Intelligence and Machine Learning

Machine learning models, Machine learning applications, Supervised and unsupervised machine learning, Integrating generative Artificial Intelligence, Types, Applications, Case studies, Problems, Impact and Prompt engineering.