Artificial Intelligence and Data Engineering

Admission

Home aide Article

Admission Requirements:

Students having minimum 2.5 GPA or second division both in SSC and HSC from science background may apply for admission into AIDE as per the guideline of University Grants Commission (UGC) of Bangladesh. Students completing five O-level subjects and at least two A-level subjects and obtaining at least GPA 2.0 may apply for admission.

 

Program completion:

In order to obtain B.Sc. in Artificial Intelligence and Data Engineering, students will have to complete 153 credits with at least CGPA 2.00. If any student fails in any course, she/he will get opportunity to improve the grade by retaking the same in the subsequent semesters. Students willing to obtain a Bachelor of Science in Artificial Intelligence and Data Engineering will have to follow the general guidelines of degree requirements of the university.

 

Program Focus Areas (Major Areas Covered):

  • Artificial Intelligence (AI) and Intelligent Systems
  • Machine Learning and Deep Learning
  • Data Engineering and Big Data Technologies
  • Data Analytics and Visualization
  • Cloud Computing and Distributed AI Systems
  • Data Pipelines, ETL, and Real-Time Data Processing
  • Database Systems and Data Management
  • Generative AI and AI-driven Applications
  • AI Product Development and Research
  • Industry-Oriented Projects and Internship-Based Learning

These focus areas are designed to develop skills in building AI-powered solutions, managing large-scale data systems, and applying AI and data-driven technologies to solve real-world problems.

Career Prospects of Graduates (Specific Job Roles):

Graduates of the B.Sc. in Artificial Intelligence and Data Engineering (AIDE) program can pursue careers in the following roles (but not limited to):

  • AI Engineer – Develop intelligent systems, AI applications, and automation solutions.
  • Machine Learning Engineer – Build, train, optimize, and deploy machine learning models.
  • Deep Learning Engineer – Design neural network-based solutions for vision, language, and prediction tasks.
  • Data Engineer – Design and manage large-scale data pipelines, data platforms, and processing systems.
  • Big Data Engineer – Work with big data technologies for large-scale data storage and analytics.
  • Data Scientist – Analyze complex datasets and develop predictive models for business and research applications.
  • Data Analyst – Extract insights from data using analytics, visualization, and statistical techniques.
  • Cloud AI Engineer – Develop and deploy AI and data solutions using cloud platforms.
  • MLOps Engineer – Manage machine learning model deployment, monitoring, and lifecycle operations.
  • Generative AI Application Developer – Build AI-powered applications using modern generative AI technologies.
  • Database Engineer – Design, optimize, and manage advanced database systems.
  • AI Research Assistant/Researcher – Conduct research in AI, machine learning, and data-driven technologies.
  • Business Intelligence (BI) Analyst – Develop data-driven strategies through analytics and visualization.
  • AI Product Developer – Create innovative AI-based products and technology solutions.
  • Data Engineering Consultant – Provide professional solutions for data infrastructure and AI implementation.
  • Entrepreneur/AI Startup Founder – Develop AI and data-centric products and services