Modern ICT Project Management

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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 simulated internship course immerses students in ICT project management, blending Agile and traditional methodologies. They apply principles, use software tools, and explore adaptive and predictive styles. The curriculum covers industry standards, ethics, social, cultural, and legal issues, emphasizing teamwork, planning, scheduling, and resource management. 

Master project management principles and methodologies in the ICT sector, blending Agile and traditional approaches. 

Apply project management software tools for planning, scheduling, budgeting, and resource management. 

Analyze ethical, social, cultural, and legal impacts of projects on diverse stakeholders. 

Evaluate project status and recommend corrective actions to meet specific objectives within agreed parameters. 

Develop collaborative teamwork and individual skills to manage industry-standard projects effectively. 

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

Our Facilitator

Dr. Manish Gupta

Australian Institute of Advanced Technologies Lecturer

Dr. Manish Gupta, lecturer of AIAT, has extensive experience as a researcher and lecturer at the University of Adelaide, University of Technology Sydney, and Torrens University, Australia. He specializes in Artificial Intelligence, Machine Learning, Deep Learning, Data Science, and Software Engineering. Dr. Gupta earned his Ph.D. from Jawaharlal Nehru University, India, and conducted postdoctoral research at the Gwangju Institute of Science and Technology, South Korea, and the University of Pennsylvania (UPENN), USA, focusing on biosensors and AI-driven medical diagnostics. He currently serves as Head of Innovation and R&D at the digital healthcare start-up ArogyaPandit in India. Dr. Gupta holds two patents, has published over 80 papers in prestigious journals and conferences, and co-authored the book Particle Machine Learning with Spark.
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