Project management is an essential skill for data scientists, as it equips them with the tools to effectively plan, organize, and deliver projects—whether academic, industrial, or research-based. From defining objectives to managing stakeholders, successful data science projects require clear communication, realistic timelines, and agile coordination.
This course provides an in-depth understanding of project management fundamentals. It covers the historical evolution of project management, life cycles, frameworks, and the impact of culture and stakeholder involvement on project success. Students will learn how to initiate, plan, and guide projects in multidisciplinary teams.
A historical look at the evolution of project management and its importance in today’s dynamic, global environment. Introduces major milestones and methodologies.
Covers basic concepts, terminologies, roles, and the relevance of project management across industries and disciplines.
Explains the various stages of a project's life—from initiation and planning to execution and closure—with real-world examples.
Introduces structured methodologies and frameworks (like PMBOK), offering a standardized approach to project planning and execution.
Focuses on identifying stakeholders, analyzing their influence, and managing their expectations throughout the project.
Explores the influence of organizational and national cultures on project success and team dynamics, especially in international and interdisciplinary settings.
Discusses how to define a project, write a charter, and align initial goals with stakeholder expectations and business needs.
Understanding project management will make your technical work more impactful. Try to apply these principles to your academic and personal projects. Practicing project planning, stakeholder mapping, and project life cycle management will be highly valuable in your internships and future jobs.