INS 4112 units400 LevelFirst Semester

Project Management

B.Sc. Data Science, University of Uyo

Planning, executing and controlling projects: scope, schedule, cost, risk and stakeholders, across both traditional and agile approaches. Directly applicable to running your final-year project on time.

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  • 2 recommended textbooks
  • an AI tutor that has read this course’s outline and notes
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Course outline

  1. 01Project characteristics, the project lifecycle and the role of the project manager
  2. 02Project initiation: charter, stakeholders and scope definition
  3. 03Work breakdown structure and activity definition
  4. 04Scheduling: Gantt charts, network diagrams, CPM and PERT; critical path and float
  5. 05Resource allocation, levelling and cost estimation; budgeting
  6. 06Risk management: identification, qualitative and quantitative analysis, response planning
  7. 07Quality management and change control
  8. 08Agile approaches: Scrum roles, sprints, backlogs and ceremonies; Kanban
  9. 09Monitoring and control: earned value analysis; project closure and lessons learned

Recommended textbooks

  • A Guide to the Project Management Body of Knowledge (PMBOK Guide) — Project Management Institute

    7th ed. — the reference framework the exam follows

  • Project Management: A Systems Approach — Harold Kerzner

    13th ed. — thorough on planning and control techniques

How to pass INS 411

  • CPM/PERT network problems are guaranteed and are pure method marks — practise drawing the network, computing earliest/latest times and identifying the critical path until it is mechanical
  • Know the difference between agile and waterfall well enough to argue which suits a data science project (usually agile — requirements shift as you learn what the data supports)
  • Actually build a Gantt chart for your DTS 417 project; students who plan their project finish it
  • Learn the earned value formulas (CV, SV, CPI, SPI) — they are compact, examinable and frequently forgotten

Other 400 Level courses

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