Overview

The Bachelor of Data Science and Machine Learning is an innovative and interdisciplinary program designed to prepare students for the rapidly evolving fields of data science, artificial intelligence, and machine learning. This program combines rigorous training in mathematics, statistics, computer science, and specialized machine learning algorithms to provide students with a comprehensive understanding of the principles and practices underlying the analysis, interpretation, and management of large data sets. Throughout the program, students engage with real-world data sets and projects, developing skills in data preprocessing, visualization, statistical inference, predictive modeling, and algorithmic design. The curriculum is structured to not only impart technical proficiency in programming languages such as Python and R and tools like Tensor Flow and PyTorch but also to foster critical thinking, problem-solving, and ethical considerations in data science practices. Graduates of this program are well-equipped to tackle complex data-driven challenges and contribute to innovations across a wide range of industries, including technology, finance, healthcare, and beyond, positioning them at the forefront of the digital economy.

Vision

The Data Science and Machine Learning Program is based on the vision that harnessing the power of data is essential for driving innovation and addressing complex global challenges. The program emphasizes the importance of producing graduates who are not only skilled in analyzing and interpreting data but also committed to advancing the field of machine learning to transform industries, improve decision-making, and contribute to the betterment of society.

Mission

To graduate data scientists and machine learning experts who are dedicated to leveraging data for innovation and informed decision-making. These graduates will be proficient in applying advanced analytical techniques, developing intelligent systems, and utilizing cutting-edge machine learning tools across various domains. The program is grounded in the mission of empowering students with the knowledge and practical skills necessary to address complex challenges, drive technological advancements, and uphold the highest standards of ethical data use and problem-solving.

Goals

  • Foundational Knowledge: Providing students with a solid foundation in mathematics, statistics, and computer science, which are crucially important for understanding and applying data science and machine learning techniques.

  • Data management skills: Teaching students how to collect, organize, manage, and store large data sets effectively to ensure data quality and accessibility for analysis.

  • Providing students with analytical skills: Developing students’ ability to analyze and interpret data, using statistical methods and data visualization techniques to extract ideas and guide the decision-making process.

  • Master the concept and use of machine learning: Providing students with a comprehensive understanding of various machine learning algorithms and models including supervised, unsupervised and enhanced learning, along with the skills needed to implement these models to solve real-world problems.

  • Providing students with programming experience: Ensuring that students are proficient in the programming languages commonly used in data science and machine learning, such as Python and R, in addition to getting students familiar with relevant libraries and frameworks.

  • Ethical and Legal Awareness: Instilling an understanding of the ethical considerations and legal implications related to data privacy, data security and the use of artificial intelligence and prepare students to deal with these challenges in their professional work.

  • Problem Solving Skills: Developing students’ ability to apply data science and machine learning techniques to solve complex problems across various domains such as healthcare, finance and technology.

  • Communication Skills: Enhancing students' ability to communicate complex data findings to specialized and non-specialized audiences effectively through clear visualizations and convincing narratives.

  • Research ability: Enhancing research skills that enable students to undertake independent projects and contribute to field knowledge as well as keep up with emerging trends and technologies. 

Careers of Graduates

After completing this degree, you will be well-positioned for a career in the local and global labor market, having the following potential opportunities:

  • Government institutions that serve a huge part of citizens (education, health, and communications) in the field of data analysis.

  • The banking sector in the field of data analysis and machine learning.

  • Information technology sector in private companies.

  • The industrial sector in the field of employing machine learning to increase production.

Program Learning Outcomes

Upon completion of this program, students should be equipped with comprehensive knowledge, skills, and abilities to excel in their endeavors.

  • Technical and programming skills: Students will be able to use programming skills.

  • Students will be able to carry out statistical analysis using professional software. This includes applying statistical models, data management, and inferential statistics.

  • Students will have a deep understanding of the principles of machine learning and artificial intelligence. They will also be able to apply these techniques to real-world problems and data sets.

  • Students will have in-depth knowledge of how to deal with different data models and use visualization tools to interpret and display data effectively.

  • Students will be able to apply data science concepts and methods to solve real-world problems and communicate these solutions effectively.

  • Students will be able to deal with social and professional issues related to data science and artificial intelligence in addition to how to deal ethically with data.

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