PROJECT MANAGEMENT

Course Description

This course introduces the concept of managerial process in project management. It explores the process of lifecycle management of projects and the tools for decision making. The course will cover the important topics of project management process including cost and time estimation, project scheduling, managing risk, outsourcing, project closure and how to become an effective project manager. The technical and behavioral issues in project management with a broad range of industries to which project management principles can be applied will be also highlighted. By the end of this course the students will be able to understand how project management theories are practiced in business cases and will be able to apply theories in real life cases.

PROJECT MANAGEMENT

Evaluation Tools (Active Term)

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Reference Books & Course Materials

1. 01 Larson E. and Gray C. (2021). Project Management: The Managerial Process (8th ed.).

Learning Outcomes

1. L01 Developing knowledge on the fundamental principles of project management SOLO 5
2. L02 Explaining the phases in project life cycle SOLO 5
3. L03 Explaining the process of cost and time estimation SOLO 3
4. L04 Developing skills in risk management and project scheduling SOLO 3
5. L05 Planning project schedule SOLO 4

Program Outcomes

1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix