9 Weeks Archives

About This Course:

This is the 4th course in the intermediate, undergraduate-level offering that makes up the larger Programming and Data Structures MicroBachelors program. We recommend taking them in order, unless you have a background in these areas already and feel comfortable skipping ahead.

These topics build upon the learnings that are taught in the introductory-level Computer Science Fundamentals MicroBachelors program, offered by the same instructor.

This is a self-paced course that continues in the development of C++ programming skills. Among the topics covered is the development of more advanced command-line programs that utilize file processing, linked lists, stacks, queues, trees, binary search trees, and tree balancing algorithms to solve problems. Several implements are presented in the development of each data structure, including hash maps, AVL, and red and black trees. Students learn how to utilize and program these data structures through the lectures and the labs. C++ programming material is presented over eight weeks of interactive lectures with quizzes to assess your understanding of the material. Students will experience hands-on practice writing C++ programs through twenty-two lab challenges.

This course focuses on the efficiency of different data structures to solve various computational problems. A data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data. The data structures and algorithms learned in this class are the foundation of modern programming.

What You’ll Learn:

Design and develop programs that utilize linked lists to store data internally.
Design and develop programs that utilize stacks and queues to manage collections of data
Utilize binary search trees and balanced trees to implement fast retrieval of data from a collection of data stored in memory.

MicroBachelors® Program in Programming & Data Structures

Drive your career forward

Introduction to Programming in C++

Advanced Programming in C++

Introduction to Data Structures

Advanced Data Structures

4 Courses 9 Months 6 - 8 Hours per week

Complete Program $1,195.20

Program Details

Meet Your Instructor:

Aspen Olmsted

Adjunct Professor at New York University Tandon School of Engineering Aspen Olmsted is an adjunct faculty member in the New York University Tandon School of Engineering in the Computer Science and Engineering department. Aspen's fulltime job is as an assistant professor and Graduate program director at the College of Charleston. He obtained a Ph.D. in Computer Science and Engineering from The University of South Carolina. Before his academic career, he was CEO of Alliance Software Corporation. Alliance Software developed N-Tier enterprise applications for the performing arts and humanities market. Dr Olmsted’s research focus is on the development of algorithms and architectures for distributed enterprise solutions that can guarantee security and correctness while maintaining high-availability. In his Secure Data Engineering Lab, Aspen mentors over a dozen graduate and undergraduate students each year

About this course

Master the fundamental components of advanced literature searching in the health sciences.

Informationist Mark MacEachern and a team of fellow health sciences informationists at the University of Michigan designed this course for anyone responsible for constructing literature searches as part of their research. This course will specifically help professionals and researchers in the health sciences improve the overall quality and reporting of their literature searches.

After completing the course, you will better understand the importance of literature searches in health sciences work, the components of effective searches, and best practices to sufficiently report the search process. All learners who rely heavily on past research in their project work – regardless of their experience or current competence – will benefit from this practical learning experience.

What you’ll learn

The components of advanced searches
How to identify the types of projects dependent on advanced searching
How to construct advanced searches
Ways to uncover search-related biases that impact projects
Procedures for citation management
Best practices for reporting search strategies

Meet your instructors

Mark MacEachern

Health Sciences Informationist at Taubman Health Sciences Library, The University of Michigan

Mark MacEachern is a health sciences informationist at the University of Michigan Taubman Health Sciences Library. As an informationist, Mark teaches health sciences students about evidence-based practice and advanced search methodologies, and frequently collaborates with health professionals on review projects. In 2013, he co-developed the flipped, continuing education course Systematic Reviews: Opportunities for Librarians, which empowers information experts to engage in such projects, and lead the course through 2017. He has also been invited to join the faculty of the Medical Library Association's Research Training Institute, which will see its first cohort in 2018. Mark received his Master of Library and Information Science degree from the University of Western Ontario in 2007.

Jean Song

Health Sciences Informationist at Taubman Health Sciences Library, The University of Michigan

Jean Song is the Assistant Director for Academic and Clinical Engagement (ACE) for the University of Michigan’s (UM) Taubman Health Sciences Library (THL). She began her career as the Reference Coordinator at the Public Health Library & Informatics at UM and then moved to Pfizer Global Research and Development where she worked as a systems administrator and project manager for their document management and adverse event reporting systems. She returned to UM as the Bioinformationist for THL and a liaison to the National Center for Integrative Biomedical Informatics (NCBI). She then headed and built the Research and Informatics unit at THL and moved into her current role as the lead of ACE. The ACE unit at THL has responsibility for curricular integration and teaching and learning in departments across the schools of health sciences, expert searching and systematic reviews, and clinical information management services. Jean has her B.S. in biological sciences from Stanford University and her MSI from the UM’s School of Information.

Tyler Nix

Health Sciences Informationist at Taubman Health Sciences Library, The University of Michigan

Tyler Nix is an informationist at the University of Michigan Taubman Health Sciences Library, where he partners with health sciences students and faculty on education and research projects related to advanced literature searches, research impact metrics and tools, and data visualization resources. Prior to the University of Michigan, he was an Associate Fellow at the National Library of Medicine. Tyler received his Master of Science in Library Science degree from the University of Kentucky in 2015.

Judith Smith

Health Sciences Informationist at Taubman Health Sciences Library, The University of Michigan

Judy Smith is a Health Sciences Informationist at the Taubman Health Sciences Library (THL), at the University of Michigan, Ann Arbor. Judy partners with faculty, students, and staff in the Department of Health Policy and Management in the School of Public Health. In that role, she works to integrate information skills and resources into the curriculum, providing numerous instruction sessions and consultations on advanced literature review techniques. Additionally, Judy engages with public health research initiatives, especially as they relate to health policy. She also serves as a point person for information needs at an interdisciplinary research complex, the North Campus Research Complex (NCRC), which houses the Institute for Health Care Policy and Innovation. Judy is also working with a team of informationists at THL on a mixed methods study to measure the library’s impact patient and population care. Judy holds a Master of Science, Library and Information Science from the University of Illinois, Champaign Urbana, and a Bachelor of Arts in English from the University of Michigan.

About This Course:

As part of the Principles of Manufacturing MicroMasters program, this course focuses on decision making for system design, as it arises in manufacturing systems and supply chains.

You will learn about frameworks and models for structuring key system design issues and trade-offs that arise in today’s supply chains and manufacturing systems.

The course will also cover various models, methods and software tools for decision support for:

Logistics network design
Capacity planning and flexibility
Make-buy
Supply chain contracting
Supply chain risk mitigation

You will learn through industry applications and cases to illustrate concepts and challenges.This course should be taken in sequence following Supply Chains and Manufacturing Systems: Planning.

Develop the engineering and management skills needed for competence and competitiveness in today’s manufacturing industry with the Principles of Manufacturing MicroMasters Credential, designed and delivered by MIT’s #1-ranked Mechanical Engineering department in the world. Learners who pass the 8 courses in the program will earn the MicroMasters Credential and qualify to apply to gain credit towards MIT’s Master of Engineering in Advanced Manufacturing & Design program.

What You’ll Learn:

Frameworks and models forsystem design
Decision supportmodels
Methods and software tools for supply chain contracting and risk mitigation

MicroMasters® Program in Principles of Manufacturing

Learn from the world’s #1 ranked Mechanical Engineering department

Manufacturing Process Control I

Manufacturing Systems I

Management in Engineering: Accounting and Planning

Supply Chains for Manufacturing: Inventory Analytics

Manufacturing Process Control II

Supply Chains for Manufacturing: Capacity Analytics

Manufacturing Systems II

Management in Engineering: Strategy and Leadership

8 1 year 5 months in total 10 - 12 hours per week

Complete Program $1,260.00

Program Details

Prerequisites:

Supply Chains and Manufacturing Systems: Planning is required unless there is a strong prior knowledge of Logistics Systemsand Operations Management

Frequently Asked Questions:

For more information, please see the POM FAQ Page.

Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Meet Your Instructors:

Stephen Graves

Abraham J. Siegel Professor of Management at Massachusetts Institute of Technology Stephen Graves is the Abraham J. Siegel Professor of Management and a Professor of Operations Management at the MIT Sloan School of Management. He has a joint appoitnemnt with the MIT Department of Mechanical Engineering. Graves develops and applies operations research models and methods to solve problems in manufacturing and distribution systems and in service operations. Graves holds an AB in mathematics and social sciences and an MBA from Dartmouth College, and an MS and a PhD from the University of Rochester.

Sean Willems

Haslam Chair in Supply Chain Analytics at University of Tennessee Sean Willems is the Haslam Chair in Supply Chain Analytics at the University of Tennessee's Haslam College of Business. In 2000, he co-founded Optiant, a provider of multi-echelon inventory optimization tools, which was later acquired by Logility, Inc. He has been a visiting professor of operations management at the MIT Sloan School of Management since 2016. His work with companies such as Hewlett Packard, Proctor & Gamble, and Intel has led to finalist selections for the 2003, 2010, and 2017 Franz Edelman Award for Achievement in Operations Research and the Management Sciences.