Executive Certificate in Project Management, AI & Data Analytics

project management

To be announced

This course explores the integration of project management principles with data analytics techniques. Students will learn how to leverage data analytics methodologies to enhance project decision-making, improve outcomes, and drive project success. The course provides a foundational understanding of project management and introduces the essential data analytics concepts, tools and techniques that applicable to project environments.

About the Course

Course Time: 18:30 - 21:30 with 2 breaks

Enrolment: 17 Feb - 31 Mar 2024

Commencement: 2 Apr 2024

Course Schedule

Class Schedule: 2 evening classes per week with 3 hours per class

Total Duration: 8 lectures (3 hours each) with a total of 24 hours

Assessment Methods

Part A: Individual or group case study to assess understanding of PM and Data Analytic techniques (50%).

Part B: Assessment of Multiple choice on Project management (50%).

Completion Requirements: Final score is no less than 50 based on the calculation: (Part A+ Part B) /2 (Out of 100 for each part); And class participation and attendance no less than 70%

Course Language

English, Cantonese

Mode of Study

Face to face

Venue

Lingnan Union Park Centre, 771-775 Nathan Road, Prince Edward, Kowloon

Course Structure

course 2 structure

Course Syllabus

Part (A): PMI Project Management Perspective (18 hrs)

Lecture-1: Project management fundamentals and core concepts (Part 1 & 2)

Project life cycles and processes
Project management planning
Project roles and responsibilities
Follow and execute planned strategies or frameworks (e.g., communication, risks, etc.)
Problem-solving tools and techniques in project environment

Lecture-2: Project planning, scheduling, resource allocation and estimation

Core concepts of project planning
Project scheduling techniques
Project Resources allocation tools and techniques
Project estimation techniques

Lecture-3: Predictive, plan-based methodology

Conditions to use a predictive, plan-based approach
Create project management plan schedule
Document project controls of predictive, plan- based projects

Lecture-4: Agile Frameworks and Methodology (Part 1)

Conditions to use an adaptive approach
Plan project iterations

Lecture-5: Agile Frameworks and Methodology (Part 2)

Document project controls for an adaptive project
Explain the components of an adaptive plan
Prepare and execute task management steps

Lecture-6: Business Requirement Analysis Framework

Business analysis (BA) roles and responsibilities
Conduct stakeholder communication
Gather requirements
Demonstrate an understanding of product roadmaps
Determine how project methodologies influence business analysis processes
Validate requirements through product delivery

Part (B):

Lecuture-7,8: Data Analytics Perspective (6 hrs)

Data Analytics

Fundamentals of data analytics and its relevance to project management
Basics of data collection, cleaning, and pre-processing
Data-Driven project management ICT systems skills, techniques and tools: Data warehousing, storage, data-lake, Hadoop,
Data-Drive project management software analytics skills, techniques and tools: Data mining and machine learning techniques: decision tree, classification & regression, random-forest, dimension reduction & SVM
Implementing data analytics for project quality management
Understanding data visualization for project reporting
Introduction to project risk management
Applying data-driven improvements for decision making and future projects

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