WEEK 0: Overview & Logistics: In Week 0, we will provide an overview of the course and the software you will need.
WEEK 1: Data Management I: In this first week, we ask 'why look to data for answers and introduce data modeling. We dive into data modeling and the basics of relational models, including entities, attributes, keys, tables, and of course, databases. You will become familiar with Entity-Relationship Diagrams that describe the business rules through a combination of relationships and cardinality between entities. We will show examples of taking real-world data and putting it into fully normalized databases. We will finish up with a short review of client-server architecture.
WEEK 2: Data Management II: In this week, you will become thoroughly acquainted with using the Structured Query Language, or SQL, the language that allows humans (as well as other systems) to interact with relational databases. You will learn how to use SELECT, INSERT, JOIN, VIEW, and other statements through extensive examples. We will be using MySQL for these assignments, but you can use any database implementation that you are comfortable with.
WEEK 3: Data Management III: This week, we will introduce additional topics in data management. Building on the data management skills mastered in weeks 1-2 and the first lesson of this week, you will learn about supervised and unsupervised learning techniques and model quality. We will also provide a quick overview of the burgeoning field of Machine Learning.
WEEK 4: Machine Learning: In Week 4, we will dive more deeply into the field of Machine Learning. We will present examples of commonly used machine learning algorithms and some applications. Next, we will discuss methods to train and validate classifiers and the trade-offs between classifier performance and overfitting. We will be using the open-source software package Orange (implemented in Python) for machine learning.
WEEK 5: Prep Week: This is a prep week in which no new graded assignments will be released. It provides you time to complete previous assignments and prepare for the Midterm next week. We will also offer a Virtual Field Trip to New York City, where learners can apply machine learning to logistical problems at a real company.
WEEK 6: Midterm Exam: The Midterm Exam covers all material from weeks 1, 2, 3, and 4. The objective is to ensure mastery of data management techniques and methods. The exam will only be available for 72 hours, and once you start it, there is a limited time (4 hours) to complete it.
WEEK 7: Supply Chain Systems I: ERPs, SC Modules, and Software Selection and Implementation: So far, we have discussed how to manage large sets of data. This week, we take a specific look at supply chain systems starting with typical data structures and communication methods (such as EDI, XML, etc.). Building on this, we will provide an overview of the traditional supply chain operational and execution systems, such as ERP, MRP, TMS, OMS, and WMS. Finally, we will review how supply chain planning systems are used in practice and some of the challenges embedded in supply chain systems.
WEEK 8: Supply Chain Systems II: Warehouse Week: This week focuses on warehouses. We will cover both the fundamentals of warehouses and then take you on two field trips to see what you learned applied in actual practice.
WEEK 9: Supply Chain Systems III: Visibility and Track & Trace: In this week, you will learn about track and trace systems and the importance of visibility in supply chains. Dr. Chris Caplice will introduce this topic and its application across industries. In the second lesson, Dr. Bateman explores a case that brings together the concepts of working with big data, supply chain systems, platform interoperability, and track & trace in their interest of supply chain visibility.
WEEK 10: Supply Chain & Technology Trends: In this week, Dr. Caplice and Dr. Ponce will introduce current technologies and trends and discuss how they may impact supply chains, including autonomous trucks and vehicles, delivery drones, mobile computing, additive manufacturing (3D printers), crowdsourcing delivery, robotics, and blockchain. We will conclude the week with a wrap-up of the course and the MicroMasters program series. There will be no graded assignment for this week.
WEEK 11: Prep Week: Again, this is a prep week with no new graded assignments so that you can get prepared for the Final Exam!
WEEK 12: Final Exam: The Final Exam covers all material in this course. The objective is to understand how supply chain systems and technologies work in practice, from data management to system integration. The exam will only be available for 72 hours, and once you start it, there is a limited time (4 hours) to complete it.