Upcoming Paid Online Courses (287)
The capstone project includes the evaluation of the competencies and performance tasks, which define an Associate Android Developer (Fundamental Application Components, Application User Interface (UI) and User Experience (UX), Persistent Data Storage, Enhanced System Integration and Testing and Debugging).
You will demonstrate your understanding of the fundamental application components of programming for Android, how to build clean and compelling user interfaces, using view styles and theme attributes to apply a consistent look and feel across an entire application. Your app will connect with the internet sharing preferences and files, SQLite databases, content providers, libraries as ORM or Realm. You will design, plan, build and publish in the Google Play store your own Android Application.
This capstone project is part of the GalileoX Android Developer MicroMasters Program 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 four courses as well as this final capstone project.
Please note that the verified certificate option for this course is limited to 300 learners. The verified certificate option will close when this limit is reached.
Analytical models are key to understanding data, generating predictions, and making business decisions. Without models it’s nearly impossible to gain insights from data. In modeling, it’s essential to understand how to choose the right data sets, algorithms, techniques and formats to solve a particular business problem.
In this course, part of the Analytics: Essential Tools and Methods MicroMasters program, you’ll gain an intuitive understanding of fundamental models and methods of analytics and practice how to implement them using common industry tools like R.
You’ll learn about analytics modeling and how to choose the right approach from among the wide range of options in your toolbox.
You will learn how to use statistical models and machine learning as well as models for:
- change detection;
- data smoothing;
- decision making.
There is much more to software testing than just finding defects. Successful software and quality assurance engineers need to also manage the testing of software.
In this course, part of the Software Testing and Verification MicroMasters program, you will learn about the management aspects of software testing. You will learn how to successfully plan, schedule, estimate and document a software testing plan.
You will learn how to analyze metrics to improve software quality and software tests.
We will also discuss software quality initiatives developed by industry experts.
No previous programming knowledge needed.
The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data.
The goal of this course, part of the Analytics: Essential Tools and Methods MicroMasters program, is for you to learn how to build these components and connect them using modern tools and techniques.
In the course, you’ll see how computing and mathematics come together. For instance, “under the hood” of modern data analysis lies numerical linear algebra, numerical optimization, and elementary data processing algorithms and data structures. Together, they form the foundations of numerical and data-intensive computing.
The hands-on component of this course will develop your proficiency with modern analytical tools. You will learn how to mash up Python, R, and SQL through Jupyter notebooks, among other tools. Furthermore, you will apply these tools to a variety of real-world datasets, thereby strengthening your ability to translate principles into practice.
This course presents an example of how to apply a database application development methodology to a major real-world project.
All the database concepts, techniques and tools that are needed to develop a database application from scratch will be introduced along the way as you apply them to your own major class team project.
In addition to the development methodology, techniques and tools learned in this course will include the Extended Entity Relationship Model, the Relational Model, Relational algebra, calculus and SQL, database normalization, efficiency and indexing. Finally, techniques and tools for metadata management and archival will be presented.
Explore this five-unit course and discover a unified framework for understanding the essential physics that govern materials at atomic scales. You’ll then be able to relate these processes to the macroscopic world.
The course starts with an introduction to quantum mechanics and its application to understand the electronic structure of atoms and the nature of the chemical bond. After a brief description of the electronic and atomic structures of molecules and crystals, the course discusses atomic motion in terms of normal modes and phonons, as well as using molecular dynamics simulations.
Finally, principles of statistical mechanics are introduced and used to relate the atomic world to macroscopic properties.
Throughout the course, students will use online simulations in nanoHUB to apply the concepts learned to interesting materials and properties; these simulations will involve density functional theory and molecular dynamics.
Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. This area is also concerned with issues both theoretical and practical.
In this course, we will present algorithms and approaches in such a way that grounds them in larger systems as you learn about a variety of topics, including:
- statistical supervised and unsupervised learning methods
- randomized search algorithms
- Bayesian learning methods
- reinforcement learning
The course also covers theoretical concepts such as inductive bias, the PAC and Mistake‐bound learning frameworks, minimum description length principle, and Ockham's Razor. In order to ground these methods the course includes some programming and involvement in a number of projects.
By the end of this course, you should have a strong understanding of machine learning so that you can pursue any further and more advanced learning.
This is a three-credit course.
Regression Analysis is the most common statistical modeling approach used in data analysis and it is the basis for more advanced statistical and machine learning modeling.
In this course, you will be given fundamental grounding in the use of widely used tools in regression analysis. You will learn the basics of regression analysis such as linear regression, logistic regression, Poisson regression, generalized linear regression and model selection.
Throughout this course, you will be exposed to not only fundamental concepts of regression analysis but also many data examples using the R statistical software. Thus by the end of this course, you will also be familiar with the implementation of regression models using the R statistical software along with interpretation for the results derived from such implementations.
This course is more about the opportunity for individual discovery than it is about mastering a fixed set of techniques.
This course provides students and professionals in the analytics field with an accelerated introduction to the basics of management and the language of business.
The objective is to enhance an analytics-focused learner's effectiveness in the business world. Designed for students who possess little background in business, the course provides an introduction to the types business issues and problems that challenge management teams today.
The course is taught as a series of business disciplinary modules. The professors who teach the modules represent a diversity of functional areas, including accounting, finance, marketing, international marketing, industry analysis, and business strategy.
Topics covered include:
- basic accounting principles and theory
- financial statement formats, usage and analysis
- cost accounting, variance analysis, and the use of accounting data for decision making
- capital structure and financial analysis techniques
- methods of valuating entrepreneurial ventures, sources of entrepreneurial capital
- the marketing mix (product, price, promotion, and place) and strategic considerations in market planning
- fundamentals of industry analysis, business strategy formulation, and the use of innovation as a competitive weapon.
Imaging technologies form a significant component of the health budgets of all developed economies, and most people need advanced imaging such as MRIs, X-Rays and CT Scans (or CAT Scans) during their life. Many of us are aware of the misinformation sometimes offered in TV dramas, which either exaggerates the benefits or overemphasizes the risks.
This medical imaging course provides an introduction to biomedical imaging and modern imaging modalities. The course also covers the basic scientific principals behind each modality, and introduces some of the key applications, from neurological diseases to cancers. This course includes modules specially designed for the general public, whilst also providing some advanced modules which could contribute to professional development in health, engineering and IT industries.
During each week of this course, chefs reveal the secrets behind some of their most famous culinary creations — often right in their own restaurants. Inspired by such cooking mastery, the Harvard team will then explain the science behind the recipe.
Topics will include:
- How molecules influence flavor
- The role of heat in cooking
- Diffusion, revealed by the phenomenon of spherification, the culinary technique pioneered by Ferran Adrià.
You will also have the opportunity to become an experimental scientist in your very own laboratory — your kitchen. By following along with the engaging recipe of the week, taking precise measurements, and making skillful observations, you will learn to think like both a cook and a scientist. The lab is certainly one of the most unique components of this course — after all, in what other science course can you eat your experiments?
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As a professional web software developer, you will not only need to know how to program in this simple yet powerful language, but you will need to understand the fundamentals of how data is exchanged on the World Wide Web (WWW) and what tools and frameworks are available to you for creating robust, interactive web applications.
We will also introduce you to modern web frameworks and component-based libraries such as React for efficiently developing modular web page components, which improve scalability and maintainability. We will also cover modern software methodologies such as model-driven development, and architectures such as model-view-controller (MVC) and model-view-presenter (MVP). We will explore how they are used by teams of professional software developers to create high quality applications.
Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.
TU Delft’s approach to observation theory is world leading and based on decades of experience in research and teaching in geodesy and the wider geosciences. The theory, however, can be applied to all the engineering sciences where measurements are used to estimate unknown parameters.
The course introduces a standardized approach for parameter estimation, using a functional model (relating the observations to the unknown parameters) and a stochastic model (describing the quality of the observations). Using the concepts of least squares and best linear unbiased estimation (BLUE), parameters are estimated and analyzed in terms of precision and significance.
The course ends with the concept of overall model test, to check the validity of the parameter estimation results using hypothesis testing. Emphasis is given to develop a standardized way to deal with estimation problems. Most of the course effort will be on examples and exercises from different engineering disciplines, especially in the domain of Earth Sciences.
This course is aimed towards Engineering and Earth Sciences students at Bachelor’s, Master’s and postgraduate level.
The course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.
In this anatomy course, part of the Anatomy XSeries, you will explore the interactive relationships of the cardiovascular, respiratory and urinary systems, and the roles they play in your body.
This course is a primer for the cardiovascular, respiratory, and urinary systems in which students learn the pertinent details of the structures and functions through a combination of lectures, videos, labeling activities and quizzes.
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