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Professional Diploma in Artificial Intelligence

 

Department of Information Technology — Artificial Intelligence and Its Applications

 

1. Program Overview:

An intensive professional and applied program extending over 3 months (80 hours of approved study load), aimed at providing participants with up-to-date knowledge and programming and practical skills in the fields of artificial intelligence and its contemporary applications. The program covers Python for artificial intelligence, machine learning algorithms, neural networks and deep learning, Natural Language Processing (NLP), and Generative AI.

2. Key Objectives:

  • Mastering programming and data preparation: using Python to build artificial intelligence solutions and to prepare, process, and ready datasets for training.
  • Mastering Machine Learning algorithms: applying supervised and unsupervised learning algorithms, and evaluating and tuning model performance.
  • Understanding deep learning and neural networks: understanding the architecture of Artificial Neural Networks (ANNs) and Deep Learning applications.
  • Mastering generative AI and language processing: studying Natural Language Processing (NLP) models, generative artificial intelligence techniques, and developing integrated intelligent projects.

3. Target Audience:

  • Developers and programmers wishing to transition into or specialize in artificial intelligence engineering and applications.
  • Data engineers, data analysts, and researchers in intelligent technologies.
  • Students and graduates of Computer Science, Information Systems, and Software Engineering programs.
  • Interested individuals and professionals seeking to employ generative artificial intelligence technologies and tools in their work and projects.

4. Study Plan Modules (12 Interactive and Applied Modules):

1. Introduction to Artificial Intelligence and Its Fundamental Concepts.

2. Python Fundamentals for Artificial Intelligence.

3. Data and Its Preparation for Artificial Intelligence Applications.

4. Machine Learning Basics.

5. Supervised Learning.

6. Unsupervised Learning.

7. Evaluation of Artificial Intelligence Models and Performance Improvement.

8. Neural Networks and Deep Learning.

9. Natural Language Processing (NLP).

10. Generative AI.

11. Contemporary Artificial Intelligence Applications and Tools.

12. Final Artificial Intelligence Project.

5. Program Data and Organizational Assessment

  • Field and specialization: Information Technology / Artificial Intelligence and Its Applications.
  • Duration and sessions: 3 months (evening period) | from 20 to 25 lectures (two lectures per week, two hours per lecture).
  • Distribution of credit hours (80 total hours):

50 hours: interactive live lectures (remote / online).

20 hours: required readings and open resources.

7 hours: chapter questions and self-assessment.

3 hours: final review and completion examination.

  • Attendance and assessment requirements: an attendance rate of no less than 75% of the live sessions, in addition to assignments and periodic practical applications.
  • Final project: an online assessment test (25 multiple-choice questions + 5 practical case questions), in addition to implementing and submitting an integrated applied artificial intelligence project.

 

 

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