WEEK 0: Overview, Logistics & TFC : In Week 0 we will provide an overview of the basic rules and practices of managing large data sources. Additionally, we will introduce you to the Fresh Connection supply chain simulation game. This is a game that we will use throughout the course, starting on Week 1, to illustrate how different functions interact and how trade-offs can be made.
WEEK 1: DATA MANAGEMENT I: In this first week, we dive deeply into data modeling. You will learn 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 how to take real-world data and put it into fully normalized databases. We will finish up with a short review of client-server architecture. This week we will open The Fresh Connection Round 1, available for just one week!
WEEK 2: DATA MANAGEMENT II: In this week, you will become fully acquainted with how to use the Structured Query Language, or SQL. This is the language that allows humans (as well as other systems) to interact with relational databases. Through extensive examples, you will learn how to use SELECT, INSERT, JOIN, VIEW, and other statements. 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: In this week, we will introduce additional topics in data management. We will also provide a quick overview of the burgeoning field of Machine Learning. Building off of the data management skills mastered in weeks 1-2 and the first lesson of this week, you will learn how to set up and run both supervised and unsupervised learning techniques. We will be using the open source software package Orange (implemented in Python) for the machine learning lectures this week and next. Fresh Connection Round 2 is open this week.
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.
WEEK 5: Week off (preparation for Midterm Exam): In week 5 we give you time to play TFC game! You will have once week to play Round 3. No new graded assignments will be handed out during this week. We will also offer a Virtual Field Trip to New York City, where learners can see a an application of machine learning to logistical problems at a real company.
WEEK 6: MIDTERM EXAM: The Midterm exam covers all of the material from weeks 1, 2, 3, and 4. The objective is to ensure mastery of data management techniques and methods. It will be a timed exam, available during just one week and once you start the exam there is a limited time (4 hours) to complete it.
WEEK 7: Supply Chain Systems I: ERPs & SC Modules: So far, we have discussed how large sets of data are managed. In 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 off of this, we will provide an overview of the traditional supply chain operational and execution systems, such as, ERP, MRP, TMS, OMS, and WMS. In addition to our lectures, we will feature interviews and discussions with industry experts.
WEEK 8: Supply Chain Systems II: Supply Chain 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 will explore a case that will bring together many of the lessons you have learned in this course including how to work with big data, supply chain systems, platform interoperability, and track & trace in their interest of supply chain visibility. The graded assignment for this week will be proctored.
WEEK 9: Supply Chain Systems III: Software Selection, Implementation, and Challenges: In the first lesson, we will review how supply chain planning systems are used in practice. In the second lesson, we will review some of the challenges embedded in supply chain systems.
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, to include 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: Week Off (preparation for FINAL EXAM)
A free week to give you all a time to breathe! No assignment will be handed out.
WEEK 12: FINAL EXAM
The final exam covers all of the material in this course. The objective is to understand how supply chain systems and technologies work in practice; from data management to system integration. It will be a timed exam, available for just one week and once you start the exam there is a limited time (4 hours) to complete it.