This course gives you an introduction to modeling methods and simulation tools for a wide range of natural phenomena. The different methodologies that will be presented here can be applied to very wide range of topics such as fluid motion, stellar dynamics, population evolution, ... This course does not intend to go deeply into any numerical method or process and does not provide any recipe for the resolution of a particular problem. It is rather a basic guideline towards different methodologies that can be applied to solve any kind of problem and help you pick the one best suited for you. The assignments of this course will be made as practical as possible in order to allow you to actually create from scratch short programs that will solve simple problems. Although programming will be used extensively in this course we do not require any advanced programming experience in order to complete it.

There is a vast variety of contemporary surface analysis methods that you can use for your research. If you are not sure which one is right for you, or if you want to obtain the right information about different surface analysis techniques, then this course is for you! This course describes the most widely used analysis methods in contemporary surface science. It presents the strengths and weaknesses of each method so that you can choose the one that provides you with the information you need. It also reviews what each method cannot give to you, as well as how to interpret the results obtained from each method. This course is filled with examples to help you become familiar with the graphs and figures obtained from common surface analysis methods. Each method is described in a similar way: basic principle, apparatus scheme, example results, special features, and actual device examples.

Interested in learning how to solve partial differential equations with numerical methods and how to turn them into python codes? This course provides you with a basic introduction how to apply methods like the finite-difference method, the pseudospectral method, the linear and spectral element method to the 1D (or 2D) scalar wave equation. The mathematical derivation of the computational algorithm is accompanied by python codes embedded in Jupyter notebooks. In a unique setup you can see how the mathematical equations are transformed to a computer code and the results visualized. The emphasis is on illustrating the fundamental mathematical ingredients of the various numerical methods (e.g., Taylor series, Fourier series, differentiation, function interpolation, numerical integration) and how they compare. You will be provided with strategies how to ensure your solutions are correct, for example benchmarking with analytical solutions or convergence tests. The mathematical aspects are complemented by a basic introduction to wave physics, discretization, meshes, parallel programming, computing models. The course targets anyone who aims at developing or using numerical methods applied to partial differential equations and is seeking a practical introduction at a basic level. The methodologies discussed are widely used in natural sciences, engineering, as well as economics and other fields.

Discover the principles of solid scientific methods in the behavioral and social sciences. Join us and learn to separate sloppy science from solid research! This course will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity. We will use examples from sociology, political sciences, educational sciences, communication sciences and psychology.

This course teaches you the basics of conducting qualitative research. You will learn how to: (a) design research questions, (b) write interview questions, and (c) conduct observations. You will also be introduced to basic data analysis techniques and think about where you would like to publish and present your research. This course is perfect for anyone interested in conducting qualitative research but isn't sure how to get started. At the end of this course, you will have gained knowledge about the primary tools used in qualitative research and how to use them. You will be ready to go forth and conduct your own research.

The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner. These data sets in turn allow us to generate hypotheses at the click of a mouse or tap of a finger. In Plant Bioinformatics on Coursera.org, we covered 33 plant-specific online tools from genome browsers to transcriptomic data mining to promoter/network analyses and others, and in this Plant Bioinformatics Capstone we'll use these tools to hypothesize a biological role for a gene of unknown function, summarized in a written lab report. This course is part of a Plant Bioinformatics Specialization on Coursera, which introduces core bioinformatic competencies and resources, such as NCBI's Genbank, Blast, multiple sequence alignments, phylogenetics in Bioinformatic Methods I, followed by protein-protein interactions, structural bioinformatics and RNA-seq analysis in Bioinformatic Methods II, in addition to the plant-specific concepts and tools introduced in Plant Bioinformatics and the Plant Bioinformatics Capstone. This course/capstone was developed with funding from the University of Toronto's Faculty of Arts and Science Open Course Initiative Fund (OCIF) and was implemented by Eddi Esteban, Will Heikoop and Nicholas Provart. Asher Pasha programmed a gene ID randomizer.

There is an increasing attention to ethics in engineering practice. Engineers are supposed not only to carry out their work competently and skilfully, but also to be aware of the broader ethical and social implications of engineering and to be able to reflect on these. According to the Engineering Criteria 2000 of the Accreditation Board for Engineering and Technology (ABET) in the US, engineers must have “an understanding of professional and ethical responsibility” and should "understand the impact of engineering solutions in a global and societal context.” This course provides an introduction to ethics in engineering and technology. It helps engineers and students in engineering to acquire the competences mentioned in the ABET criteria or comparable criteria formulated in other countries. More specifically, this course helps engineers to acquire the following moral competencies: - Moral sensibility: the ability to recognize social and ethical issues in engineering; - Moral analysis skills: the ability to analyse moral problems in terms of facts, values, stakeholders and their interests; - Moral creativity: the ability to think out different options for action in the light of (conflicting) moral values and the relevant facts; - Moral judgement skills: the ability to give a moral judgement on the basis of different ethical theories or frameworks including professional ethics and common sense morality; - Moral decision-making skills: the ability to reflect on different ethical theories and frameworks and to make a decision based on that reflection. With respect to these competencies, our focus is on the concrete moral problems that engineers encounter in their professional practice. With the help of concrete cases is shown how the decision to develop a technology, as well as the process of design and production, is inherently moral. The attention of the learners is drawn towards the specific moral choices that engineers face. In relation to these concrete choices learners will encounter different reasons for and against certain actions, and they will discover that these reasons can be discussed. In this way, learners become aware of the moral dimensions of technology and acquire the argumentative capacities that are needed in moral debates with stakeholders (e.g. governments, users, and commercial business departments).

Matthew Lesko is America's #1 Free Money Researcher.  He's written over 100 books on the subject including 2 New York Time s Bestsellers. Two of this books won "Best Reference Book of the Year" awards and he was a financial  columnist for the New York Times,  Chicago Tribune and Good Housekeeping magazine. Matthew has sold over 4 million reference books on free money and had a string of very successful infomercials.  He has been a regular guest on TV talk shows like The Today Show, Good Morning America, The Tonight Show, Letterman, Oprah, Larry King, CNN, ABC News and Fox News. He still spends every day of his life researching grants and other alternative sources of free money and help for clients who need to solve their financial problems or fund their projects. This Course Will Cut Your Internet Research Time By 80% Lesko has taken his 40 years of research experience and developed a simple set of skills and tricks to keep you out of the Google Search Run-A-Round. Your new skills will not only save you tons of internet research time and frustration...but more importantly, you will finally discover the money sources that were never showing up in Google. You'll Learn The 5 Biggest Problems When Using Google and How To Solve Them. 1...Quantity not Quality 2...Advertising Dollars 3...Accuracy 4...Asking The Wrong Question 5...You Can't Call Google You will also learn how to use 6 alternative websites that specialize in showing you only free sources of money and help--never trying to sell you anything. Your Google Searching Will Never Be The Same Again! But, You'll Now Have A Bigger Problem.... What Are You Going To Do with All The Extra Time You've Saved by No Longer Going Around in Google Circles? Matthew Lesko New York Times Best Selling Author and Entrepreneur

On Being a Scientist will provide you with an overview of scientific conduct & ethics, what it means to be a scientist and allows you to become acquainted with academic practice, thus meeting a demand for increased awareness in scientific integrity. This course is designed to inform you on topics as scientific integrity and social responsibilities of scientists. Broad questions, which are inseparably linked to these topics are discussed: namely regarding the nature of science and the societal role it fulfills. Course objectives: After this course you will: 1) Understand the basic principles of science, and know what is "not done". 2) Have a realistic image of science and scientists. 3) Recognize integrity dilemmas, know how to respond in clear cases, and have the skills to respond prudently in unclear cases. 4) Know and understand the differences and similarities of various disciplines. 5) Have a basic understanding of the role of science in society, realise your own societal responsibilities, and are able to take a position in societal issues where science plays a role. The course consists of a feature film, supported by short lectures, set to serve as a starting point for the discussions and assignments.

This MOOC is about demystifying research and research methods. It will outline the fundamentals of doing research, aimed primarily, but not exclusively, at the postgraduate level. It places the student experience at the centre of our endeavours by engaging learners in a range of robust and challenging discussions and exercises befitting SOAS, University of London's status as a research-intensive university and its rich research heritage. The course will appeal to those of you who require an understanding of research approaches and skills, and importantly an ability to deploy them in your studies or in your professional lives. In particular, this course will aid those of you who have to conduct research as part of your postgraduate studies but do not perhaps have access to research methods courses, or for those of you who feel you would like additional support for self-improvement. No prior knowledge or experience in research is required to take this course and as such, the course is for everyone. This MOOC draws on a wealth of existing course material developed to support research training across SOAS, University of London and particularly drawing from the Centre for International Studies and Diplomacy (CISD). In 2015, the course was nominated for the prestigious Guardian University Award for its innovative approach to online learning. Participation in or completion of this online course will not confer academic credit for University of London programmes