A bachelor’s degree in Computational Mathematics with Data Analytics proposes offering a unique blend of traditional mathematical expertise and data analytical skills. The degree is designed to establish a comprehensive foundation in mathematical principles and techniques essential for quantitative analysis across various disciplines. This interdisciplinary program will be offered by the Department of Mathematics, in collaboration with the Faculty of Computing and Artificial Intelligence at AU. Computational Mathematics and Data Analytics offers a great variety of academic career paths, ranging from teaching at all levels to research in mathematics and its adjacent fields, as well as all careers where Data analytics is valuable. It qualifies students for graduate study not only in Mathematics, but also in neighboring disciplines such as Engineering, Physics, Data Science, Economics, Finance, MBA programs, and many others. Mathematical thinking combined with modeling and programming skills is the key to employment in a variety of high-level strategic positions in which analytic thinking, problem solving, and quantitative skills are paramount, ranging from consultancy, public administration, information technology, and data security, to high-level management.

HSSC with Mathematics from any BISE with at least 50 % marks OR

An examination equivalent to the Intermediate with mathematics and having an Equivalent Certificate issued by the Inter Board Chairman Committee, Islamabad

HSSC without Mathematics / Pre-Medical may be allowed admission with condition to take one additional course of 4 credit hours.

This program aims to equip students with a strong foundation in computational mathematics and data analytics, preparing them for graduate studies or direct entry into high-demand fields. With a focus on mathematical modeling and real-world applications, students will develop critical problem-solving and analytical skills essential for careers in science, engineering, finance, and industry.

Key Objectives:

  • * Build a solid base in computational mathematics
  • * Develop expertise in mathematical modeling and implementation
  • * Apply data analytics to complex, real-world problems

Learning Outcomes

Graduates of this program will be able to:

  1. 1. Develop a strong foundation in computational mathematics and data analytics to pursue careers in business, industry, government, or academia. Graduates will possess the necessary mathematical, statistical, and computational knowledge to tackle complex problems and adapt to emerging technological trends in data-driven fields.
  2. 2. Identify, analyze, and formulate complex mathematical and data-driven problems through critical evaluation and logical reasoning. Graduates will be able to derive valid conclusions by leveraging mathematical models, algorithms, and statistical techniques to ensure accuracy, effectiveness, and efficiency in real-world applications.
  3. 3. Apply appropriate mathematical techniques and modern computational tools, including machine learning, statistical software, and programming frameworks, for modeling and analyzing large-scale data. Graduates will have hands-on experience with industry-standard tools and an understanding of their limitations and practical implications.
  4. 4. Communicate complex mathematical and data-driven insights effectively to technical and non-technical audiences. Graduates will be proficient in preparing comprehensive reports, presenting findings visually and orally, and conveying actionable insights using appropriate data visualization techniques and storytelling methods.
  5. 5. Integrate mathematical and analytical knowledge with other disciplines such as artificial intelligence, finance, healthcare, and engineering to develop innovative solutions. Graduates will have the ability to address real-world challenges through interdisciplinary approaches and contribute to advancements in various domains.

Career Options

As an interdisciplinary degree in data analytics with a strong mathematical background, a degree in Computational Mathematics and Data Analytics promises to open the doors for a wide range of career options. These include:

  • • Financial Analysts in various organizations of quantitative finance, financial engineering, and insurance companies.
  • • Operations Researchers
  • • Mathematicians are frequently employed in Information Technology positions. Mathematical knowledge is essential for work in information security and cryptography.
  • • Statisticians are employed by large organizations and work in research and development divisions from academia to industry to analyze data from surveys and experiments.
  • • Education offers a wide field of employment ranging from secondary school teachers to university professors.
  • • Mathematicians pursue academic careers at research institutes or universities.
  • • Data Analysts, Data Engineers, Risk Analyst, Forecast Analyst in various sectors like finance, medicine, business, Machine Learning Engineer.