Courses

Site Survey With Ekahau Training How To Perform Site Surveys What you'll learn: You will learn how to perform Site Surveys.You will understand how to analyse of Site Survey outputsYou will be very familiar with a great Site Survey Product which is Ekahau. Welcome to The Course Site Survey With Ekahau Training ( Perform Site Surveys )With the help of this course, you will be able to get all necessary information to learn how to perform Pre deployment Site Surveys You will learn theory behind each topic and then see how they are implemented.You will learn:Predictive Site SurveyPassive and Active Site SurveysHow ToCreate Design DocumentationHow To Prepare Customer QuestionnaireStatement of Work DocumentSite Survey DeliverablesImpact of Material AttenuationApplication Need For VoiceRequirements For Voice TrafficApplications For VideoCoverage For LocationHow To Start The Site SurveyEkahau Site Survey OverviewCoverage RequirementsStarting a New Project on EkahauAuto-PlannerUsing Scale Creating Walls and Alignment Feature on EkahauPre-Site Survey ChecklistPre-Deployment Site SurveySite-Survey For CoverageSite-Survey For Different EnvironmentsSite-Survey For RoamingSite Survey DevicesEkahau Survey ModeSurvey Methods - Stop and GoSurvey Methods -Continuous Survey - CopyPost-Deployment Site Survey OverviewPerforming Post-Deployment Site Survey

Note: This course will be closed on May 5th 2025 for updates. Please ensure all content has been completed by then. We aim to relaunch this course with new updates in July 2025.This free course, Becoming an ethical researcher, explores the ethics of planning, carrying out and reporting research which involves human participants. It will sensitise you to issues that a researcher should consider to support ethical and well-justified decision-making.A wide variety of research scenarios are used to stimulate individual reflection and discussion on the course forum, participation in which, together with successful completion of quizzes, will contribute to gaining a digital badge. Transcript6565Enrolling on the course will give you the opportunity to earn an Open University digital badge. Badges are not accredited by The Open University but they're a great way to demonstrate your interest in the subject and commitment to your career, and to provide evidence of continuing professional development.Once you are signed in, you can manage your digital badges online from My OpenLearn. In addition, you can download and print your OpenLearn statement of participation – which also displays your Open University badge.The Open University would reallyappreciate a few minutes of your time to tell us about yourself and your expectations for the course before you begin, in our start-of-course survey 6666.Once you complete the course we would also value your feedback and suggestions for future improvement, in our end-of-course survey 6767. Participationwill be completely confidential and we will not pass on your details to others.

The online course of Engineering Surveying is a unique course that delves into the principles, techniques, and practices of engineering surveying. In this rapidly developing era, engineering surveying not only plays a crucial role in traditional fields such as architecture, roads, and bridges, but also plays an increasingly important role in emerging fields such as geographic information systems, satellite navigation, and unmanned driving. Therefore, by studying this course, you will lay a solid foundation for career development in the field of engineering or related fields.In this course, you will comprehensively master the basic principles and methods of engineering surveying. Covering topics such as leveling, angle measurement, traverse measurement, terrain measurement, construction measurement, etc., students will learn to use various measuring instruments, including leveling instruments, total stations, GNSS receivers, etc., and gain a deeper understanding of how to process measurement data and generate accurate measurement results.Through the study of this course, you will acquire practical vocational skills, including the operation and maintenance of measuring instruments, processing and analysis of measurement data, and writing measurement reports. These skills will provide strong support for you to find your ideal job in the engineering field.

Society has a growing range of big problems that need solutions which are novel and affordable. By developing the mindset and learning the skills associated with innovation and entrepreneurship, you can apply these to create real world impact in any future career - whether it is in academia, in industry or government or as a founder of a business. This course was developed by the p2i consortium, a group of prominent research institutions and global businesess, led by University of Cambridge. This course demystifies the entrepreneurial process to start a business and highlights similarities between researchers, innovators and entrepreneurs. The course is designed to support researchers gain the mindset and skills to spot opportunities and have the capacity to act on these with confidence, whether that’s in relation to pursuing an academic career, a policy intervention , a commercial opportunity or other means of bringing their research out into the wider world to have an impact. The course is equally suitable for individuals who want to learn about innovation and entrepreneurship and are very short of time and cannot easily gain this knowledge through attending numerous workshops and seminars. **** The course provides a powerful combination of content, examples, relatable role models all in one place and in a structured way. **** The course features insights from successful researchers turned academics, founders, and industry leaders. The course includes exercises to reinforce learning. The outputs of the exercises help articulate the value and impact of research or business ideas, and will increase learners’ confidence and credibility to turn their ideas into reality.

This course is for early career researchers and mentors who believe that modern scientific careers require management skills and want to be research leaders. This curriculum gives you skills to effectively implement funded projects, thereby enhancing your career success. Research leaders take on a number of new roles, rights, and responsibilities--as scientific leaders, financial administrators, managers, and mentors. In this course, we explain how to optimize the people, teams, projects, and finances for which you are responsible. Despite your research training, you are probably facing an urgent training gap in leadership and management skills. Scientific careers falter for non-science reasons when researchers fail to execute a scope of work: struggle to track expenses and returns substantial unspent grant funds; or run out of funds by spending on the wrong people or mismanaging the right people. Consequently, projects close with inadequate progress on aims, thus compromising successful competition for future funding. This course will help avoid these traps. Leadership and management are essential skills for researchers. Several early career researchers, senior scientists, and administrative leaders are eager to share their expertise and experiences with you.

Explore strategies for becoming a more effective policy researcher in this informative webinar hosted by the University-Based Child and Family Policy Consortium. Gain insights from two experts, Dr. Elizabeth Gershoff and Dr. Rachel Chazan Cohen, as they share their experiences bridging research and policy. Learn about taking advantage of opportunities, conducting research in government settings, interdisciplinary work, funding, and engaging with policymakers. Discover various research methods, types of research questions, and activities involved in policy research. Receive valuable advice on flexibility, centralized governance, and participating in technical expert panels. Understand how to effectively communicate with Congress and navigate the complexities of policy-oriented research in child and family studies.

Learn Research Methods & Machine Learning What you'll learn: Introduction to ResearchFinding a research problemFinalzing your objectivesResearch MethodologyIntroduction to Machine Learning:- What is Machine Learning ?,Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google CollabsArtificial Neural networks [Theory and practical sessions - hands-on sessions]Support Vector Machines Indicative Module ContentIntroduction to Research - This session will help you to start the wonderful journey of research. Research is useful for finding new opportunities , new discoveries and higher studiesFinding a research problem - Finding a research problem is the most important aspect of any research project . (Undergraduate, Postgraduate etc..)Finalizing your objectives- Research MethodologyPositivismInterpretivismIntroduction to Machine Learning:- What is Machine Learning ?,-> in this session we will get an overview of machine learning Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google Collabs - (All the instructions will be provided to setup the environment successfully.)Artificial Neural networks [Theory and practical sessions - hands-on sessions] - This practical hands-on session will guide you to create a comprehensive ANN projectMachine Learning Techniques : Support Vector Machines - Lecture &Hands - On with Google Collabs , Trees and Random Forest - Lecture &Hands-On with Google Collabs,

Explore the importance of open access in academic research and learn how developers can contribute to making scientific papers freely available to the public. Discover Dissemin, a Django-based website promoting global Open Access policies, which enables researchers to legally deposit their papers in repositories like Zenodo. Gain insights into the workings of the research world and the challenges involved in assisting researchers to make their work accessible to all. Understand the paradox of publicly funded research being locked behind paywalls and the potential solutions offered by Python-powered tools.

Research can be a time-consuming process, with vast amounts of information to sift through, analyze, and synthesize. Leveraging the power of generative AI can simplify these tasks, making it easier to find relevant studies, summarize key insights, develop research plans, and uncover new connections between findings. In this course, Generative AI for Researchers, you’ll learn to streamline your research process by utilizing AI-powered tools to enhance efficiency and depth. First, you’ll explore how to use AI to summarize the main themes or parts of complex documents, allowing you to grasp the essential points of a paper quickly. Next, you’ll discover techniques for brainstorming precise and relevant search terms, helping you retrieve more targeted results on research engines. Finally, you’ll learn how to develop research plans and identify relationships between findings by prompting generative AI to produce related research questions and hypotheses. When you’re finished with this course, you’ll have the skills and knowledge of leveraging generative AI in research needed to conduct more effective literature reviews, accelerate planning, and uncover new insights, all while saving valuable time and enhancing the quality of your academic work.

Learn to intelligently detect and take down cyber threats What you'll learn: a high level overview of the 7 threat intelligence phasesHunting - The goal of hunting is to establish techniques to collect samples from different sources that help to start profiling malicious threat actors.Features Extraction - goal of Features Extraction is to identify unique Static features in the binaries that help to classify them into a specific malicious group.Behavior Extraction - The goal of Behavior Extraction is to identify unique Dynamic features in the binaries that help to classify them into a specific malicious group.Clustering and Correlation - The goal of Clustering and Correlation is to classify malware based on Features and Behavior extracted and correlate the information to understand the attack flow.Threat Actor Attribution - The goal of Threat Actors is to locate the threat actors behind the malicious clusters identified.Tracking - The goal of tracking is to anticipate new attacks and identify new variants proactively.Taking Down - The goal of Taking down is to Dismantled Organized Crime Operations. Welcome to this FREE course preview of the Cyber Security Threat Intelligence Researcher Certification. The Cyber Security Threat Intelligence Researcher Certification will help you acquire the skills needed to find out who is behind an attack, what the specific threat group is, the nation from which the attack is being launched, as well as techniques being used to launch this attack. You will know how to take a small piece of malware, find out who is responsible for launching it, the threat actor location and also how to take down that threat actor, with the support of your local law enforcement. In today’s cyber security landscape, it isn't possible to prevent every attacks. Today’s attackers have significant funding, are patient, sophisticated, and target vulnerabilities in people and processes as well as technologies. With organizations increasingly relying on digitized information and sharing vast amounts of data across the globe, they have become easier targets for many different forms of attack. As a result, every company’s day-to-day operations, data and intellectual property are seriously at risk. In a corporate context, a cyber attack can not only damage your brand and reputation, it can also result in loss of competitive advantage, create legal/regulatory noncompliance and cause steep financial damage. Today’s secure environment will have vulnerabilities in it tomorrow, so an organization cannot allow itself to become complacent. There is only so much an organization can do by defending itself against threats that have already occurred. If an organization only reacts to new threats as they come up, are likely acting too late. It is important to understand and prioritize cyber threat intelligence processes, and how they can be integrated into an organization’s security operations in a way that adds value. Cyber threat intelligence (CTI) is an advanced process enabling organizations to gather valuable insights based on analysis of contextual and situational risks. These processes can be tailored to the organization’s specific threat landscape, industry and market. This intelligence can make a significant difference to organizations' abilities to anticipate breaches before they occur. Giving organizations the ability to respond quickly, decisively and effectively to confirmed breaches allows them to proactively maneuver defense mechanisms into place, prior to and during the attack. In this course, we’ll introduce you to the 8 phases of threat intelligence: Hunting - The goal of hunting is to establish techniques to collect samples from different sources that help to start profiling malicious threat actors. Features Extraction - The goal of Features Extraction is to identify unique Static features in the binaries that help to classify them into a specific malicious group. Behavior Extraction - The goal of Behavior Extraction is to identify unique Dynamic features in the binaries that help to classify them into a specific malicious group. Clustering and Correlation - The goal of Clustering and Correlation is to classify malware based on Features and Behavior extracted and correlate the information to understand the attack flow. Threat Actor Attribution - The goal of Threat Actors is to locate the threat actors behind the malicious clusters identified. Tracking - The goal of tracking is to anticipate new attacks and identify new variants proactively. Taking Down - The goal of Taking down is to Dismantled Organized Crime Operations.

This course presents research conducted to increase our understanding of how data collection decisions affect survey errors. This is not a “how–to-do-it” course on data collection, but instead reviews the literature on survey design decisions and data quality in order to sensitize learners to how alternative survey designs might impact the data obtained from those surveys. The course reviews a range of survey data collection methods that are both interview-based (face-to-face and telephone) and self-administered (paper questionnaires that are mailed and those that are implemented online, i.e. as web surveys). Mixed mode designs are also covered as well as several hybrid modes for collecting sensitive information e.g., self-administering the sensitive questions in what is otherwise a face-to-face interview. The course also covers newer methods such as mobile web and SMS (text message) interviews, and examines alternative data sources such as social media. It concentrates on the impact these techniques have on the quality of survey data, including error from measurement, nonresponse, and coverage, and assesses the tradeoffs between these error sources when researchers choose a mode or survey design.

The course gives an introduction to survey research methodology, to provide Master students with the fundamental knowledge about this method for collecting and analyzing data for their thesis.

Explore the latest developments and challenges in Cosmic Microwave Background (CMB) surveys through this comprehensive lecture that delves into emerging opportunities in cosmological research. Learn about cutting-edge survey techniques, data analysis methods, and the potential scientific breakthroughs that upcoming CMB observations promise to deliver. Gain insights into how these advanced surveys are pushing the boundaries of our understanding of the early universe and the technical challenges that researchers must overcome to extract meaningful cosmological information.

This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. Faculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs.

This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. Faculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs.

Explore the latest findings in weak lensing cosmology from the Hyper Suprime-Cam (HSC) Year 3 survey in this informative 32-minute conference talk. Delve into the cutting-edge research presented by Hironao Miyatake at the International Centre for Theoretical Sciences as part of the "Largest Cosmological Surveys and Big Data Science" program. Gain insights into how the HSC survey is pushing the boundaries of large-scale structure mapping at higher redshifts, complementing other ongoing surveys like DES and KiDS. Learn about the implications of these results for precision cosmology and how they contribute to our understanding of the Universe's structure and evolution. This talk is an excellent opportunity for cosmology enthusiasts and researchers to stay updated on the latest advancements in weak lensing studies and their impact on our cosmological models.

This specialization is intended for early career and novice researchers who are preparing to write their first major biomedical or health research grant proposals. Through three courses, you will cover how to plan and prepare proposals and resubmissions; develop study designs and data analysis plans that align with budgets, timelines, and milestones; and apply writing techniques that increase reader comprehension and engagement. These courses will prepare you to use best practices and avoid common pitfalls in your health research grant proposals.

This course teaches the fundamentals of Python 3 in the context of academic research. Our tutor team support researchers across the whole of Imperial College London, including in science, engineering, mathematics, computing, medicine, and business. We have created this course to help our learners and researchers elsewhere prepare for modern research, which often includes a substantial amount of programming. You'll gain the basic skills needed to produce substantial programming projects which are accurate, professional, scalable, and which perform effectively. This will set you up well for the type of programming you'll need to do as a researcher. In this course, you'll learn: • the basics of Python including variables, types, if-blocks, loops, functions and exceptions. • how to write code using Visual Studio Code, which is a modern, professional tool used by programmers across all disciplines and professions. • best practices and the reasoning behind them, with a focus on developing skills and knowledge to help you become a confident and independent programmer. Projects throughout the course will allow you to practise designing and structuring progressively larger pieces of code - so, by the end, you'll be ready to produce the sort of code expected of a researcher. Throughout the course, you can draw on support from the learning community, sharing with your peers, answering questions, and giving feedback on solutions to exercises. This course is designed to be appropriate for complete novices to programming or learners who may already know another programming language. We hope you enjoy learning Python with us!

Explore the frontiers of cosmological research in this lecture from the "Largest Cosmological Surveys and Big Data Science" program. Delve into the latest advancements in cosmic microwave background observations, large-scale structure mapping, and multi-messenger cosmology. Learn about ongoing and future wide-area surveys such as DES, DESI, Euclid, and LSST, as well as upcoming X-ray and 21 cm surveys. Gain insights into the challenges and opportunities presented by big data in cosmology, and discover how these surveys are pushing our understanding of the Universe to new heights. Benefit from expert knowledge and hands-on experience in analyzing large survey data, essential for early career researchers in the field of cosmology.

Explore mindfulness techniques and their applications in scientific research through this insightful 48-minute conference talk delivered by Christian Frezza at the EACR Early Career Researchers Conference 2023. Gain valuable insights into incorporating mindfulness practices into your academic and professional life, enhancing focus, reducing stress, and improving overall well-being. Discover how mindfulness can positively impact scientific productivity and creativity, and learn practical strategies to implement these techniques in your daily routine as an early career researcher.