Data Analytics for Cost Engineering and Project Controls Professionals

Instructor: H. Lance Stephenson, CCP FAACE Hon. Life

Lance Stephenson is a senior leader with over 35 years of experience in the operational, capital portfolio, and project delivery environment, where he has worked for the owner, engineer, and constructor. Based on Lance’s years of experience and education in the operational and capital project delivery environment, Lance has provided direction in the areas of organizational design, process improvements, auditing, maturity assessments, and the development and implementation of best practices for improved capital portfolio and project effectiveness. Lance is a contributing member of the Technical Board for AACE International and is a Certified Cost Professional, a Project Management Professional, and a certified member of the Royal Institute of Chartered Surveyors. Lance’s past roles include director, senior manager, supervisor, PM/CM, specialist, analyst, foreman, tradesman, and life-long learner and practitioner. Lance is currently the Director of Operations for AECOM.

Description
The Data Analytics for Cost Engineering and Project Controls Professionals is a course designed for individuals looking to enhance their skills in data analytics and total cost management. This course covers a wide range of topics, from introduction to data analytics to advanced analytics techniques and data visualization. It also allows practitioners the opportunity to explore the use of analytical methods in cost engineering and project controls problem-solving, highlighting organizational and contextual issues. The practitioners would also understand and construct simple analytical models of a problem that can be manipulated or solved to identify decisions that can yield the best outcomes according to one or more carefully defined criteria. This will be explored through mini-cases and illustrations. 

Course Outcomes
The goal of this course is to give students a basic understanding of how to apply analytics methods in the project delivery environment. 

Key Learning Objectives
Understand the concepts of data analytics;
Recognize the process of problem-framing;
Identify ways analytic models have been applied;
Distinguish characteristics of analytic targets;
Frame the business problem statement into an analytics problem;
Identify steps for creating a simple analytical model;
Describe considerations for communicating analytics results and cultivating buy-in.

Course Overview
This comprehensive data analytics course is designed to provide participants with the knowledge and skills needed to excel in the field of data analytics. The course covers a wide range of topics including data collection, data cleaning, data analysis, data visualization, and more. Participants will have the opportunity to work on real-world projects and case studies to apply their learning in a practical setting.

Course Structure

1. Introduction to Data Analytics
   • What is data analytics?
   • Importance of data analytics in decision-making
   • Overview of tools and technologies used in data analytics
2. Data Collection and Cleaning
   • Types of data sources
   • Data collection methods
   • Data cleaning techniques
3. Data Analysis
   • Exploratory data analysis
   • Statistical analysis techniques
   • Machine learning algorithms for data analysis
4. Data Visualization
   • Importance of data visualization
   • Tools for data visualization
   • Best practices for creating effective visualizations
5. Real-World Projects
   • Participants will work on real-world data analytics projects to apply their learning and gain practical experience
6. Case Studies
   • Analysis of real-world case studies to understand how data analytics is applied in various industries
7. Ethical Considerations in Data Analytics

• Privacy concerns

• Bias and fairness in data analysis
• Compliance with regulations and laws