Software Engineering for Data Science LCP

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Course overview
  • Level: Intermediate
  • Study period: 16 weeks
  • Author: AIAT
  • Evaluation:
    Self-Assessment/Projects
  • Rich learning experiences:
    300-400 h    ours
This subject equips students to thrive in next-gen data science teams, driving the application of cutting-edge techniques to craft innovative solutions. Emphasizing a software engineering approach, the course imparts essential knowledge of software engineering concepts and techniques, empowering students to contribute effectively to team projects and refine their own workflows. 

Students will navigate the intersection of data science and software engineering, advocating for a harmonious blend of both disciplines. They will engage in team-based projects, utilizing a structured process for analyzing, designing, and developing software that integrates data science technologies. The curriculum covers requirement analysis using a modified agile approach, system architecture assessment, and the implementation of security and reliability measures in data science applications. Reflective exercises will help students identify areas for future learning and career growth, ensuring they are well-prepared for the evolving landscape of data science and software engineering.

Unlock your career's potential with an industry-recognized professional qualification certificate

Our Facilitator

Dr. Murli Viswanathan

DIRECTOR, IT PROGRAMS

Prof. Murli has a PhD in Computer Science from Monash University and a BS in Computer Science & Information Systems from Deakin University. Prof. Murli worked with Carnegie Mellon University for 16 years before Joining AIAT where he is the Director of IT programs. He lectures students in AI, Machine Learning, Analytics, Big Data, Software Engineering, and other areas. He has managed/coordinated over two dozen student projects with the South Australian Government departments and industry partners. Prof. Murli is a senior member of the Australian Computer Society Accenture Subject Matter Expert in Analytics. He has substantial experience with research projects, course and curriculum design and has delivered a variety of courses at all levels in information systems and computer science since 1996.
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