About This Course:

This is the 2nd course in the intermediate undergraduate-level offering in 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.

1. Introduction to Programming in C++
2. Advanced Programming in C++
3. Introduction to Data Structures
4. Advanced Data Structures

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 functions, arrays, and strings to solve problems. Students learn to program in C++ through the lectures and the labs. C++ programming material is presented over eight weeks of interactive lectures with bi-weekly quizzes to assess your understanding of the material Students will experience hands-on practice writing C++ programs through twelve lab challenges.

Students will not only learn to use these more advanced procedural programming functionalities. They will also learn to analyze the computational complexity of their code. Computational complexity theory focuses on classifying computational problems according to their inherent difficulty and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by the mechanical application of mathematical steps, such as an algorithm.

A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition by introducing mathematical models of computation to study these problems and quantifying their computational complexity, i.e., the number of resources needed to solve them, such as time and storage.

About This Course:

Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.

In this course, part of our Professional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.

You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.

What You’ll Learn:

• The basics of machine learning
• How to perform cross-validation to avoid overtraining
• Several popular machine learning algorithms
• How to build a recommendation system
• What is regularization and why it is useful?

Frequently Asked Questions:

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By registering as an online learner in our open online courses, you are also participating in research intended to enhance HarvardX’s instructional offerings as well as the quality of learning and related sciences worldwide. In the interest of research, you may be exposed to some variations in the course materials. HarvardX does not use learner data for any purpose beyond the University’s stated missions of education and research. For purposes of research, we may share information we collect from online learning activities, including Personally Identifiable Information, with researchers beyond Harvard. However, your Personally Identifiable Information will only be shared as permitted by applicable law, will be limited to what is necessary to perform the research, and will be subject to an agreement to protect the data. We may also share with the public or third parties aggregated information that does not personally identify you. Similarly, any research findings will be reported at the aggregate level and will not expose your personal identity.

Please read the edX Privacy Policy for more information regarding the processing, transmission, and use of data collected through the edX platform.

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Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

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.

About MIT Horizon:

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

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.

About MIT horizon

MIT Horizon is an expansive content library built to help you explore emerging technologies. Through easy-to-understand lessons, you’ll be guided through the complexities of the latest technologies and simplified expert-level concepts. Designed for both technical and non-technical learners, you can examine bite-size content that can lead to maximum career outcomes.

For a limited time, gain access to the complete MIT Horizon library.

Register today for exclusive entry.

Course Overview:

What You’ll Learn

• Key analytic technologies and techniques, e.g. predictive modeling and machine learning, and how these can play a role in managerial decision making
• How to effectively manage the analytical processes and use the results of these processes as the basis for making informed, evidence-based decisions
• How companies can use analytics as the basis for creating value

Prerequisites

Elementary college course in statistics.

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.

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.

Frequently asked questions

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.

About this course

The exciting field of Cloud Computing is rapidly changing how businesses operate today. Cloud computing provides rapid access to shared pools of resources, such as: compute, storage, networks, applications, services, or libraries using an on-demand, utility-based model. The characteristics of a cloud computing model include: self-service, network access, resource pools, rapid elasticity, and metered resource usage. As with any large-scale shift, new skills and processes must be learned and implemented to overcome management challenges. Existing business processes, workflows, and policies must be adapted to account for this new technology.

This course, part of the Cloud Computing MicroMasters program, focuses on commonly encountered management issues with the adoption and implementation of cloud computing. Examples include: Cloud migration, Cloud Requests for Proposals, Cloud Service Level Agreements, and other business process compliance issues.

You will examine these issues in depth, then review industry best practices and other case studies to develop the techniques that address and mitigate them. Business processes such as procurement, vendor management, and end-user management are also covered.

Students get up to $600 AWS credits for the entire program.

Verified students receive $100 AWS educate starter account credit, when they sign up. Students who complete and use up their $100 will receive additional credits after completing the course. See Frequently Asked Questions below for further information.

This course is part of the Cloud Computing MicroMaster’s program from UMGC. Upon completion of the program and receipt of the verified MicroMaster’s certificate, learners may then transition into the full UMGC Master’s Program in Cloud Computing Architecture. See the MicroMasters program page for more.

Frequently asked questions

How long does a student have to apply to and complete the full UMGC degree?

To ensure that your program remains relevant and up-to-date, UMGC sets time limits for completing a program. Students have five (5) consecutive years from the start of the graduate degree to complete their degree. For students who start with a MicroMasters, their “time clock” begins on the date that they complete their last course in the MicroMasters program and receive their Verified Certificate. This means that students should apply to UMGC promptly to begin the degree and have as much time as possible to complete it.

Verified students receive $100 AWS educate starter account credit, when they sign up. Students who complete and use up their $100 will receive additional credits after completing the course.

Is this offer just for students who purchase a Verified Certificate?

AWS discontinued promotional credits for students and now use $100 AWS educate starter. If you purchase a Verified Certificate you will receive a sign-up credit of $100 and an additional $100 AWS Educate credit upon successfully passing the course.

How do I receive my AWS educate starter credit?

To take advantage of this benefit, you must first create an AWS Educate starter account by clicking on the link located in lesson 3 before the exams. Once registered, you will be provided with a $100 starter credit.

What is the AWS exercise?

This optional activity, which does not count towards the course’s final grade, will introduce you to the world of cloud computing through the creation of a W

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.

About This Course:

Learn how to statistically analyze data with the Six Sigma methodology using inferential statistical techniques to determine confidence intervals and to test hypotheses based on sample data. You will also review cause and effect techniques for root cause analysis.

You will learn how to perform correlation and regression analyses in order to confirm the root cause and understand how to improve your process and plan designed experiments.

You will learn how to implement statistical process control using control charts and quality management tools, including the 8 Disciplines and the 5 Whys to reduce risk and manage process deviations.

To complement the lectures, learners are provided with interactive exercises, which allow learners to see the statistics “in action.” Learners then master statistical concepts by completing practice problems. These are then reinforced using interactive case studies, which illustrate the application of the statistics in quality improvement situations.

Upon successful completion of this program, learners will earn the TUM Lean and Six Sigma Yellow Belt certification, confirming mastery of Lean Six Sigma fundamentals to a Green Belt level. The material is based on the American Society for Quality (www.asq.org) Body of Knowledge up to a Green Belt Level. The Professional Certificate is designed as preparation for a Lean Six Sigma Green Belt exam.
 

What You’ll Learn:

• To identify process problems and perform a root cause analysis using cause and effect diagrams and regression analysis.
• To analyze data using inferential statistical techniques, including confidence intervals and hypothesis testing.
• To test and quantitatively assess the impact of different improvement options using the design of an experiment.
• To test for the significance of effects using an Analysis of Variance.
• To implement control mechanisms for long-term monitoring using control charts for both quantitative and qualitative measurements.
• To apply the Six Sigma methodology for the Analyze, Improve and Control phases in your work or research.

Frequently Asked Questions: