Courses tagged with "Free" (291)
Are you working in the development sector and looking to take the next step in your career and take on a leadership role?
This business and management course is an introduction to key leadership theories and concepts that you will need to be an effective leader and manager. You will learn how leadership is different from management.
You will learn practical skills needed to build a shared vision, and lead across boundaries. You will learn to recognise your own leadership style, and the leadership styles of others. You will learn the different types of power, and tools for gaining legitimacy in your development work.
Upon course completion, you will be prepared to take on leadership roles in development and work effectively across geographical, cultural, organizational and disciplinary boundaries.
You will also develop a personalized leadership plan throughout the course, which will help you continue your leadership journey after you complete the MOOC.
This is the first course in the Leadership in Global Development MicroMasters Program. In order to get the most out of this course, we recommend that you complete this course prior to completing the other courses in the MicroMasters Program. We also recommend that you have experience working in the development sector or a strong interest in this area.
This course introduces the origin and key concepts of sustainability and how to apply those to sustainable development practice.
Sustainable development will be explored through theories and case studies from a range of Disciplines. You also will learn about planetary boundaries, urbanisation and growing inequality, to show how integral sustainable development is to our everyday existence.
This course will attempt to provide key content knowledge to bridge the science and the practice of the application and enhancement of sustainable development. The course draws on contemporary examples from both The University of Queensland (UQ) and the Sustainable Development Solutions Network (SDSN) to address the world’s most urgent challenges, with emphasis on the linkages between science and policy.
Being a leader in development means working in complex and challenging contexts. Projects rarely run as planned, and managers need to be flexible and adaptive in their approach.
This course will teach you the skills to tackle complex problems in developing - and developed - countries. You will learn how problems in development contexts are always complex - no matter how simple they may appear at first. You will learn strategies for how to dig deeper into the problem and come up with solutions that address the real issues. You will learn techniques and practical tools for understanding local context, and ways to lead effectively.
This course will also expose you to the disconnect between policy and practice.
Uncertainty is a way of life in development, and leaders need the skills to adapt and excel in this space. Join us to learn effective strategies for being an adaptive leader in development.
This course is part of the Leadership in Global Development MicroMasters Program. In order to get the most out of this course, we recommend that you have experience working in the development sector or a strong interest in this area. We also recommend that you complete the following courses prior to commencing or in parallel with these courses: Leaders in Global Development and The Science and Practice of Sustainable Development.
There are many approaches and perspectives about what is most important within the development sector. Some practitioners argue that basic water and sanitation is essential to good development, others push for women’s economic empowerment. Others still believe that good governance and institutions are the driving factor to sustainable development.
In this development studies course, you will engage with contemporary debates and gain new perspectives on what it means to be a leader in development. By gaining a good understanding of the different challenges facing development workers across the globe, you will be able to lead more effectively across sectors and organizations.
The course focuses each module around key readings that argue a particular perspective or idea. Interviews with the author, alongside other academics and practitioners, complement these readings and encourage new ways of thinking about the challenges facing workers in this space. Learners are encouraged to reflect on their own ideas and practice, and share their perspectives with other learners and the course team.
This course is part of the Leadership in Global Development MicroMasters Program. In order to get the most out of this course, we recommend that you have experience working in the development sector or a strong interest in this area. We also recommend you have completed the following courses prior to commencing or in parallel with these courses:
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.
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.
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.
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.
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.
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.
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