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Bachelor’s in Data Engineering and Intelligent Systems

 

Three-Year Academic Plan (Bachelor Program)

Total Credits: 150

 

1 – Foundations

 

Semester 1

Code

Course Title

Credits

MATH101

Calculus I

3

PHYS101

General Physics I

3

ITAI101

Introduction to IT & AI

3

CS101

Programming I (Python)

3

UNI101

Academic English I

2

 

 Semester 2

Code

Course Title

Credits

MATH102

Calculus II

3

PHYS102

General Physics II

3

CS102

Programming II (OOP – Java)

3

ITAI102

Digital Logic & Computer Organization

3

UNI102

Academic English II

3

 

 

2 – Core Engineering & Data Foundations

 

Semester 3

Code

Course Title

Credits

MATH201

Linear Algebra

3

STAT201

Probability & Statistics

3

CS201

Data Structures & Algorithms

3

ITAI201

Database Systems

3

ITAI202

Web Technologies

3

 

Semester 4

Code

Course Title

Credits

CS202

Operating Systems

3

ITAI203

Advanced Databases & SQL Optimization

3

ITAI204

Computer Networks

3

ITAI205

Discrete Structures

3

ITAI206

Software Engineering

3

 

 

3 – Specialized Data Engineering + AI

 

Semester 5

Code

Course Title

Credits

DEIS301

Data Engineering Fundamentals

3

DEIS302

Machine Learning

3

DEIS303

Cloud Computing & Distributed Systems

3

DEIS304

Big Data Analytics (Hadoop & Spark)

3

DEIS305

Data Warehousing & ETL

3

 

Semester 6

Code

Course Title

Credits

DEIS306

Deep Learning

3

DEIS307

Intelligent Systems Design

3

DEIS308

Data Governance, Ethics, & Security

3

DEIS309

NoSQL Databases

3

DEIS310

DevOps for Data Engineers

3

 

 

4 – Specialization, Research, and Industry Preparation

 

Semester 7

Code

Course Title

Credits

DEIS401

Advanced Topics in Data Engineering

3

DEIS402

AI-Based Decision Support Systems

3

DEIS403

Real-Time Data Processing & Stream Computing

3

DEIS-405

Natural Language Processing

3

DEIS-GP1

Graduation Project I

3

 

Semester 8

 

Code

Course Title

Credits

DEIS 498

Capstone Project II

3

DEIS 422

Professional Ethics & Technology Law

3

DEIS 424

Entrepreneurship & Innovation in AI

3

DEIS 499

Industry Internship II (Long-Term)

3

Learning outcomes

 


  Program-Level Learning Outcomes (Graduate Profile)

Graduates of the Data Engineering and Intelligent Systems program will be able to:

 

1- Engineering & Analytical Skills

  • Apply mathematical, statistical, and computational methods to solve complex data engineering and AI problems.
  • Analyze large-scale datasets using structured and unstructured approaches.

2- Data Engineering Competence

  • Design, implement, and manage data pipelines, data warehouses, and distributed systems.
  • Utilize cloud platforms, big data frameworks, and ETL processes for scalable data solutions.

3- Artificial Intelligence & Intelligent Systems

  • Develop, train, evaluate, and deploy machine learning and deep learning models.
  • Design AI-based decision support systems for real-world applications.

4- Programming & Software Engineering

  • Demonstrate proficiency in modern programming languages (Python, Java, C#) and software engineering methodologies.
  • Apply object-oriented, functional, and data-driven programming principles.

5- Research & Problem-Solving

  • Conduct independent research, literature review, and experimental design.
  • Formulate innovative solutions to contemporary problems in data engineering and intelligent systems.

6- Professionalism & Ethics

  • Demonstrate understanding of ethical, legal, and social responsibilities related to AI, data privacy, and cybersecurity.
  • Communicate effectively with technical and non-technical stakeholders.

7- Teamwork & Leadership

  • Work effectively in multidisciplinary teams.
  • Lead projects, including graduation projects and industry collaborations.

8- Lifelong Learning

  • Adapt to emerging technologies, frameworks, and methodologies in data engineering and AI.
  • Engage in continuous professional development and research activities.

Career Opportunities & Industry Alignment 

 

The Data Engineering & Intelligent Systems program prepares graduates for a rapidly expanding technology sector driven by big data, artificial intelligence, cloud computing, and intelligent automation. Graduates are equipped with the technical expertise, practical skills, and professional competencies to compete in both local and international job markets.

 

Career Opportunities for Graduates

 

Graduates of this program can pursue a wide range of high-demand careers, including:

 

     Data Engineering & Analytics Careers

  •          Data Engineer
  •          Big Data Engineer
  •          ETL Developer / Data Pipeline Developer
  •          Data Warehouse Engineer
  •          Business Intelligence (BI) Engineer
  •          Data Systems Architect
  •          Cloud Data Engineer
  •          Data Governance Specialist

 

    Artificial Intelligence & Machine Learning Careers

  •          Machine Learning Engineer
  •          AI Engineer / AI Systems Developer
  •          Deep Learning Specialist
  •          Computer Vision Engineer
  •          NLP Engineer
  •          Reinforcement Learning Engineer
  •          Model Deployment Specialist (MLOps)

 

      Cloud, DevOps, and System Automation Careers

  •          Cloud Engineer (AWS, Azure, Google Cloud)
  •          Cloud Solutions Architect
  •          DevOps Engineer
  •          Site Reliability Engineer (SRE)
  •          Automation Engineer
  •          RPA Specialist

 

 

      Intelligent Systems & Smart Technologies Careers

  •          Intelligent Systems Engineer
  •          IoT Engineer / Edge AI Specialist
  •          Smart Infrastructure Systems Developer
  •          Decision Support Systems Engineer

 

      Software & Computing Careers

  •          Full-Stack Developer with AI integration
  •          Backend Engineer (high-performance systems)
  •          Software Engineer in data-driven applications

 

     Research, Academia, and Scientific Careers

  •          AI Research Assistant / Data Science Researcher
  •          University Teaching Assistant / Lecturer
  •          R&D specialist in research centers and technology hubs

 Industry Alignment: Why This Program Meets Market Needs

This department is specifically designed to match current and future industry demands, not just local but global.

 

Alignment with Global Industry Trends

The program aligns with major trends including:

  • Cloud-native data platforms
  • AI-driven automation
  • Data privacy and governance
  • Real-time analytics
  • Smart city applications
  • Industry 4.0 transformations

 

Strong Fit for the Iraqi & Middle Eastern Job Market

Iraq and neighboring countries (Türkiye, UAE, Saudi Arabia, Qatar) are rapidly investing in:

  • E-government transformation
  • Smart city projects
  • AI and digital economy strategies
  • Modern data centers and cloud adoption
  • Health, energy, and security analytics

This ensures high employability and regional relevance.

 

 Industry-Integrated Curriculum]

The curriculum includes:

  • Cloud platforms (AWS/Azure/GCP)
  • Big data tools (Hadoop, Spark, Kafka)
  • AI & ML frameworks (TensorFlow, PyTorch)
  • MLOps/DevOps
  • Real-time streaming
  • Data security & privacy

Making graduates ready from day one.

 

Internship & Industry Partnership Strategy

The department will collaborate with:

  • Tech companies (local and international)
  • Banks and financial institutions
  • Hospitals and healthcare centers
  • Telecommunication companies
  • Government digital transformation offices
  • AI and automation startups

Internships in 4th year ensure real-world experience.

 

Entrepreneurial & Startup Opportunities

Graduates are equipped to start their own businesses in:

  • AI consulting
  • Data analytics services
  • Automation solutions
  • IoT and intelligent systems products
  • Smart applications for industry

 Graduate Competitive Advantages

Graduates from this department gain a competitive distinction through:

  • Cross-disciplinary training (data + AI + cloud)
  • Hands-on labs and real-world projects
  • Early exposure to industry certifications (AWS, Google, Microsoft)
  • Strong emphasis on ethical and responsible AI
  • Research-oriented graduation projects
  • Market-oriented electives and specializations

Tuition Fees:

  • USD 6,000 for the full program (8 semesters + graduation project)

  • Flexible installment payment options available throughout the study period

  • Registration fee: USD 100 (one-time payment)

Contact Information:

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