Online courses directory (1728)

This course is about modeling and how computer models can support managerial decision making. A model is a simplified representation of a real situation and modeling is the process of developing, analyzing and interpreting a model in order to help make better decisions. Models can be invaluable tools in managing and understanding the complexity and risk inherent in many business problems. As a result, models have become an increasingly important part of business at all levels from daily operations to strategic decision making.

This course will help learners become intelligent users and consumers of these models. To this end, we will cover the basic elements of modeling – how to formulate a model and how to use and interpret the information a model produces. The course emphasizes “learning by doing” so that students will be expected to formulate, solve, and interpret a number of different optimization and simulation models using Excel spreadsheets. An important theme in the course is to understand the appropriate use of models in business and the potential pitfalls from using models incorrectly or inappropriately.

The course has two distinct parts:

• The first half of the course we will cover supervised learning techniques for regression and classification. In this framework, we possess an output or response that we wish to predict based on a set of inputs. We will discuss several fundamental methods for performing this task and algorithms for their optimization. Our approach will be more practically motivated, meaning we will fully develop a mathematical understanding of the respective algorithms, but we will only briefly touch on abstract learning theory.
• In the second half, we shift to unsupervised learning techniques. In these problems the end goal less clear-cut than predicting an output based on a corresponding input. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data. Some applications of these models include object recommendation and topic modeling.

Marketers want to understand and forecast how customers purchase products and services and how they respond to marketing initiatives.

Learn how analytics help businesses drive marketing to maximize its effectiveness and optimize return on investment (ROI).

In this course, part of the Business Analytics MicroMasters program, discover how to develop quantitative models that leverage business data, statistical computation, and machine learning to forecast sales and marketing impact for:

• customer relationship management;
• market segmentation;
• value creation;
• communication;
• monetization.

You will learn how to use probabilistic models and optimization tools to model customer demand forecasts, pricing sensitivity, Lifetime Value and how to leverage such data to make optimal decisions on designing new products, marketing segmentation and strategy.

Firms such as Apple, Alibaba, Facebook, SalesForce, Uber and Yelp operate as platform ecosystems that match buyers and sellers, gain value and market share from network effects, and harness their users to innovate.

This course teaches you how to convert products to platforms and how to generate platform innovation. You will learn how to negotiate platform startup, convert existing businesses, and make vital decisions on issues of openness, cannibalization, and competition.

You will discover how to apply concepts from two sided networks, information asymmetry, pricing, intellectual property, and game theory to real problems.

This course is taught by the instructor who literally wrote the book on this topic, “Platform Revolution: How Networked Markets Are Transforming the Economy—and How to Make Them Work for You.”

This course is part of both the Digital Leadership and Product Management MicroMasters programs.

The job of a data scientist is to glean knowledge from complex and noisy datasets.

Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks.

Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL. 

How do robots climb stairs, traverse shifting sand and navigate through hilly and rocky terrain?

This course, part of the Robotics MicroMasters program, will teach you how to think about complex mobility challenges that arise when robots are deployed in unstructured human and natural environments.

You will learn  how to design and program the sequence of energetic interactions that must occur between sensors and mechanical actuators in order to ensure stable mobility. We will expose you to underlying and still actively developing concepts, while providing you with practical examples and projects. 

As Cloud Computing shapes businesses of all sizes, it is vital to understand the technologies behind cloud infrastructure, both public and private.

In this course, part of the Cloud Computing MicroMasters program, you will learn to evaluate and compare cloud systems, technologies and providers. In doing so, you will build an understanding of the concepts of elasticity and availability through cloud orchestration.

Some industry leading cloud platforms will be covered in this class, including: Amazon Web Services, VMware vSphere, Microsoft Azure, Google Cloud, and OpenStack. You will use the built-in tools and management consoles within those platforms to configure and manage the infrastructure.

Want to gain software quality skills used in mission critical systems?

Modeling checking, symbolic execution and formal methods are techniques that are used for mission critical systems where human life depends upon the system working correctly.

In this course, part of the Software Testing and Verification MicroMasters program, you will learn how to perform these techniques manually and by using automation tools.

No previous programming knowledge needed. The concepts from this course can be applied to any programming language and testing software. This course will use Java, Java Path Finder and Java Modeling Language, however, for examples and assignments.

Instructional designers today have a tremendous number of tools and resources available to them to create highly engaging courses. Social media, digital video, and freely available online instructional resources and applications connect and engage people in new, and exciting ways. When creating online learning experiences, instructional designers integrate and infuse these digital tools and digital content in ways that engage and connect learners to course content. 

In this education and teacher training course, part of the Instructional Design and Technology MicroMasters Program, you will explore the design, development, and integration of digital media to enhance the learning experience and investigate how media, emerging and mobile tools, and online applications impact technology-mediated learning environments.

Choosing instructional materials for a course may seem like a simple step, but in fact, there are many important aspects of online learning experience development that are important to consider, such as content creation, copyright and creative commons, accessibility testing, and visual and web design techniques.

Course topics include media and visual literacy, design for online and mobile environments, use and design of open educational resources, emerging technologies, and trends in technology such as mobile learning environments.

Improvements in modern biology have led to a rapid increase in sensitivity and measurability in experiments and have reached the point where it is often impossible for a scientist alone to sort through the large volume of data that is collected from just one experiment. 

For example, individual data points collected from one gene expression study can easily number in the hundreds of thousands. These types of data sets are often referred to as ‘biological big data’ and require bioinformaticians to use statistical tools to gain meaningful information from them.

In this course, part of the Bioinformatics MicroMasters program, you will learn about the R language and environment and how to use it to perform statistical analyses on biological big datasets.  

This course, part of the Software Development MicroMasters program, will dig deep into the principles of object oriented design, and introduce new abstraction techniques and design patterns. You will use these techniques to build an application that makes use of popular online services and APIs – the most complex software design project so far.

By the end of the course, you will have a solid foundation in Java and Object-Oriented Design, as well as many software development concepts that can be applied to any language.

Learners who enroll in the Verified track will receive staff grading for the course project and increased interaction with the instructors and staff.

Social media technologies are continuously transforming the ways consumers interact with each other and firms. These changes constitute a fundamental shift in the marketplace--consumers have greater opportunities to voice their opinions and connect with their peers as well as increased influence over marketers and brands.

In this course, part of the Digital Product Management MicroMasters program, we examine how organizations capitalize on social media and consumer-to-consumer interactions to support their marketing efforts. We view these issues from a strategic and a practical perspective, rather than a technical or platform perspective. We will give you the knowledge you need to create engaging content for platforms such as Facebook, Instagram, Twitter, and Snapchat, as well as how to identify influencers, deliver content to a targeted audience, and measure the success of your efforts.

This course will equip learners with the skills they need to promote their company’s products or services, or their own personal brand using social media. Additionally, learners will gain an understanding of how they can use social media to achieve specific organizational objectives and measure the effectiveness of those efforts.

In this course you will learn how to turn solar cells into full modules; and how to apply full modules to full photovoltaic systems.

The course will cover design of photovoltaic systems, such as utility scale solar farms or residential scale systems (on/off the grid). You will learn about the function and operation of various components including inverters, batteries, DC-DC converters and the grid. After learning about the components, you will gain an understanding of the main design decisions to be taken when planning a real PV installation with excellent performance and reliability.

Finally, you will practice modelling the performance of a PV system for different solar energy applications, and estimating the energy production of a client's potential system.

This course is part of the Solar Energy Engineering MicroMasters Program designed to cover all physics and engineering aspects of photovoltaics: photovoltaic energy conversion, technologies and systems.

How do you protect the critical data that is increasingly being stored in the cloud? Learn how to build a security strategy that keeps data safe and mitigates risk.

In this course, part of the Cloud Computing MicroMasters program, you will be introduced to industry best practices for cloud security and learn how to architect and configure security-related features in a cloud platform. Case studies and government standard documents will be reviewed to help ensure appropriate levels of security are implemented.

You’ll develop the necessary skills to identify possible security issues in the cloud environment. You will also gain experience with tools and techniques that monitor the environment and help prevent security breaches such as monitoring logs and implementing appropriate security policies.

Data driven decision-making systems allow instructional designers to engage in continuous improvement of course design to optimize student learning.

In this education and teacher training course, part of the Instructional Design and Technology MicroMasters program we will delve into data driven decision-making and you will learn data mining techniques to collect actionable data. You will learn how to analyze learner statistics to improve the impact of design and technology on learning. 

It’s important for instructional designers to have systematic plans for gathering data and learner analysis to guide ongoing course adjustments to improve teaching and learning. Data is critical to the continuous improvement process.

Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?

In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.

Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.

Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.

All programming examples and assignments will be in Python, using Jupyter notebooks.

Please note that the verified certificate option is not currently open for this course. Please enroll in the audit track and you will be emailed when the verified certificate option is open for enrollment.

Businesses, consumers, and societies leave behind massive amounts of data as a by-product of their activities. Leading-edge companies in every industry are using analytics to replace intuition and guesswork in their decision-making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insights and running controlled experiments to test hypotheses.

This course, part of the Analytics: Essential Tools and Methods MicroMasters program, prepares you to understand data and business analytics and become a leader in these areas in business organizations.

It covers the methodologies, algorithms, issues, and challenges related to analyzing business data. It will illustrate the processes of analytics by allowing you to apply business analytics algorithms and methodologies to real-world business datasets from finance, marketing, and operations. The use of real-world examples and cases places business analytics techniques in context and teaches you how to avoid the common pitfalls, emphasizing theimportance of applying proper business analytics techniques.

In addition to cases, this course features hands-on experiences with data collection, analysis, and visualization using Python programs and analytics software such as SAS.

This course includes a significant analytics project.

This course, part of the Software Development MicroMasters Program, introduces how teams design, build, and test multi-version software systems.

You will learn software engineering principles that are applicable to the breadth of large-scale software systems. The course explores topics such as agile development, REST and Async programming, software specification, design, refactoring, information security, and more.

By the end of this course, learners will work in teams, applying an agile software development process to specify, design, and test multiple versions of complex software systems.

Learners who enroll in the Verified track will receive staff grading and increased interaction with the instructor and staff.

Learn how to create a culture of experimentation, where data is swiftly gathered to assess business value and drive innovation.

In this course, you will learn how to use Object and Service Oriented design principles and your development team to increase system flexibility so you can efficiently run experiments at the technical level and also refine business processes and models.

Good design enables a capability for experimentation that would otherwise be infeasible as it speeds up learning and decreases the development time needed to realize the necessary technical changes to drive the next experiment. This capability produces an increase in optionality and paths for innovation; and so overall increases business value.

The course, part of both the Digital Product Management and Digital Leadership MicroMasters programs, addresses both the digital (technical) and social (people) infrastructures and the essential interfaces between them. Managing these interfaces requires designing varying capacities to transfer, translate or transform the knowledge being used to develop experiments. This course focuses on two aspects of the social infrastructure:

1. the capacity of the technical infrastructure to engage user and identify their needs;
2. the ability to manage the interfaces between the development team and the technical infrastructure over time.

We will focus on how modular design is essential to project, process, and business model experimentation. Most importantly, you will learn how the synthesis of design, management and experimentation can create real business value.

In this course, part of the Marketing in a Digital World MicroMasters program, you will learn how to apply the concepts of advertising and marketing to branding. We will examine topics and various strategies related to building, measuring, and managing a brand, including direct and indirect measures of brand equity, structures of desired brand knowledge, choice of brand elements, development of supporting marketing programs, and management of brands over time.

You will learn how to:

• Develop a framework to identify and establish brand positioning and values to build customer based brand equity
• Plan and implement brand marketing programs through integrated marketing communications and brand associations to build brand equity
• Evaluate how a brand equity management system can capture customer mindset and enhance market performance through sources and outcomes of brand equity
• Design specific strategies that focus around extending, revitalising and reinforcing existing brands to retain brand resonance (i.e. loyalty, attachment, community and engagement).

The branding landscape is fast-paced and continually changing, yet is a stimulating and exciting environment in which to work. This course is relevant to anyone working in marketing, communications, public relations, social media and advertising.

This course is part of the CurtinX MicroMasters Credential in Marketing in a Digital World that is specifically designed to teach the critical skills needed to be successful in this exciting field. In order to qualify for the MicroMasters Credential you will need to earn a Verified Certificate in each of the five courses.

Use the knowledge of Photovoltaic technology, systems and microgrids to design your own engineering project.

This project-based course finalizes the Solar Energy Engineering MicroMasters program and focuses on applying the knowledge you gained to a solar energy project. You will work on either your own project or on a project provided by the course team. These projects can be focused on design, analysis, monitoring or integration of any photovoltaic application.

First, you will write a short project plan describing the project and the orientation of your work. After approval, you will execute your project.

Your final product is a written paper on the results of your project. This paper will be peer reviewed and assessed by a professor. You will also defend your project in an oral presentation. You will be assessed on your ability to justify design choices, to critically analyze the performance of systems, to find creative solutions and to show the potential of your solution.

Finding a sponsor for your project within a company, institute or university is encouraged.

This is the last course of the Solar Energy Engineering MicroMasters Program designed to cover all physics and engineering aspects of photovoltaics: photovoltaic energy conversion, technologies and systems.

You can start the capstone project after completing PV1x, PV2x and PV3x. However, you will need the knowledge and skills gained in PV4x to complete the final module of this course, the oral presentation.

Note: The capstone project is only accessible for ID verified MicroMasters learners.