20489 Other courses

I offer private and group sessions of Shinrin Yoku (Forest Bathing) as a certified Guide. We’ll merge with the beauty of nature in Edinburgh area embracing Japanese rituals of the Yamabushi Shamans and practicing Forest Bathing. If you have ever been among trees in a woodland, listening to the birds, walking, or simply searching for some silence, you have already experienced the Japanese practice of shrin-yoku or forest bathing. In Japanese, “shinrin” means forest and “yoku” means bath, or immersing oneself in the forest and soaking in the atmosphere through the senses. Breathing deeply and finding peace in nature has a massive positive role on your body and mind. Plants release substances from their leaves that are effective in positively stimulating the immune system, as many studies have proved. Forgetting your mobiles and usual busy schedule, in the magic atmosphere of nature , you will take this time off for yourself only to re-build and re-create the cycle that naturally links human beings with nature as a part of the whole. It will be your slowing down time to re-connect literally with your roots.  Some time of digital detoxing will help you to pay attention to your breath, to use all of your senses, to meditate while walking, to dance freely, to stay silent. When did you last touch a tree trunk, or notice the symphony of animals and leaves dancing around you? We will create our sacred space in this time of reconnection with a shamanic ceremony . In this ceremony, you will receive guidance, healing and inspiration, you will learn how to create an altar, smudging with burning sacred herbs, calling the seven directions and then receiving your talking stick to share your heart with your close beautiful circle of souls for this circle. A ceremony is spontaneous, a ceremony is unique, a ceremony is a direct connection with the spirits of the land.  Think about what you need to re-create in your life. Think about what you want to re-connect with along your path. Ask for guidance and the fairies will answer, they always do. Sessions normally last at least 120min plus the walking time to enter the woodland and the current price is for 1-1. Private groups will receive a bespoke quote. If you wish to have a longer session a bespoke price will be provided.  In Edinburgh there are three options: A) in Saughton Park: 2 hours experience daytime during the week as less busy B) In Hermitage of Braid: 3 hours experience+ 1hour inbetween walking in/out C) in Dalmeny Estate: 4 hours experience+ 1.5 hour inbetween walking in/out Giada's Journey Creative explorer of the human well-being with twenty years’ experience running events, workshops and retreats. Co-author of a non-profit book with other 33 Italian women about their stories in different countries. She has been learning to heal herself supportinga Holistic connection between mind, body and spirit. She has been studying and practicing Buddhist teachings, meditation and the Five Tibetan Rites Yoga in Nepal, India and Italy. Approached the imaginal world and dreams with the psychologist Elio Occhipinti and a regressive hypnosis journey with the vision of the psychiatrist Brian Weiss. Her studies and practice have helped her become: Shamanic Practitioner with the two years formal training at Anam Cara Shamanic and Integral Yoga Teacher, Ikigai Coach,Forest Therapy Guide qualified with Selene Calloni Williams at the Imaginal Academy and part of the Italian-Swiss Association for Counselling and Coaching, Aiscon.  Professional Esoteric Numerologist graduated at The Connaissance School of Numerology Corporate Mental Health Coach achieved with WeFocus Founder of Drink In Art exhibitions of local artists in private flats Founder of Invisible Caims creative and spiritual workshops, classes and therapies Founder of the Art and Spirituality Centre centre for creativity and well-being in Edinburgh By attending to our classes, workshops, 1 to 1 sessions and retreats you agree to our TERMS AND CONDITIONS Payment  Bookings are non-refundable.  Disclaimer  By booking a class or workshop or retreat or 1-1 session -online or any other venues – with us, you release Giada Gaslini, Invisible Caims, School of Shamanism and any business partners working with Invisible Caims from any liability arising out of any personal injuries, emotional or physical release, death, expectations of results, theft in the venue or damages that may happen to people and objects while attending. We recommend that you consult your GP regarding the suitability of undertaking an exercise programme, if the class you are booking includes it like with yoga or similar, and following all the safety instructions required before beginning to exercise. When participating in an exercise, there is the possibility of sustaining a physical injury. If you engage in this exercise programme, you agree that you do so at your own risk, are voluntarily participating in these activities and assume all risk of injury to yourself. You acknowledge that coaching, shamanic healing and counselling are not to be used as a substitute for psychotherapy, psychoanalysis, mental health care, or other professional advice by legal, medical or other professionals. Our sessions are aimed at inner research, problem solving and personal growth, they do not replace the work of doctors and psychotherapists because they do not consider, treat or aim to solve pathologies and symptoms that are strictly medical. All contracts subject to and governed by the law according to my current insurance.   Added element of the disclaimer If the class happens in any venue and you are causing any damage to the property, you are taking responsibility of your actions. It is down to the individual to take personal responsibility when participating in physical activity and when entering a space that is used and shared by other parties. Invisible Caims does not take any responsibility about possible risks that may arise but can only advise and enforce guidelines and legal requirements as defined by the Scottish Government and local authorities.   

The objective of the OTHM Level 4 Diploma in Health and Social Care Management qualification is to equip learners with the underpinning knowledge, understanding and skills required for a career in the health and social care sector at a managerial level. This fast track Level 4 Diploma in Health and Social Care Management programme enables learners to demonstrate their skills by producing evidence from their work or training activities. Learners will acquire care management skills in the Health and Social Care sector. Key Highlights of fast track Level 4 Diploma in Health and Social Care Management are: Program Duration: 6 Months (Regular 9 months duration also available) Program Credits: 120 Designed for working Professionals Format: Online No Written Exam. The Assessment is done via Submission of Assignment Tutor Assist available Dedicated Student Success Manager Timely Doubt Resolution Regular Networking Events with Industry Professionals Direct entry into Year 1 of a three-year UK Bachelor's degree LSBR Alumni Status No Cost EMI Option Who is this course for? Working Professionals, A-Level holders, learners who are looking for Career Progression and a formal undergraduate qualification leading to award of degrees in future. Requirements For entry onto the OTHM Level 4 Diploma in Health and Social Care Management qualification, learners must possess: Relevant NQF/QCF/RQF Level 3 Award/Diploma or at the level of GCE/GCSE or equivalent qualification Learner must be 18 years or older at the beginning of the course Mature learners (over 21) with management experience (learners must check with Admission Counsellors at LSBR regarding this experience prior to registering for the programme) Career path Progress to: Year 2 of a Three-year UK Bachelor's degree Completion of your qualification will meet the University standard academic entry requirements. However, each applicant will be subject to individual assessment and other entry requirements which may affect university entry. Certificates Certificate of Achievement Digital certificate - Included Once you complete the course, you would be receiving a digital copy of your Diploma along with its Transcript which can be downloaded from the awarding body website without any additional charge. You can also order Hard copy certificate by paying a nominal cost directly to the awarding body.

Accounting and finance are at the very heart of business operations. From banking to manufacturing, from huge service industries to micro businesses, the ability to manage, plan and account for money is still the ultimate measure of business success and the key driver of growth. The objective of the Level 4 Diploma in Accounting and Business qualification is to provide learners with an understanding of accounting and business in the broader business context, and to provide them with the practical, industry-focused skills to manage business finances, budgets and cash flow effectively, and to play a key role in business growth. Key Highlights of Diploma in Accounting and Business - Level 4 qualification are: Program Duration: 9 Months (Can be Fast tracked) Program Credits: 120 Designed for working Professionals Format: Online No Written Exam. The Assessment is done via Submission of Assignment Tutor Assist available Dedicated Student Success Manager Timely Doubt Resolution Regular Networking Events with Industry Professionals Direct entry into Year 1 of a three-year UK Bachelor's degree LSBR Alumni Status No Cost EMI Option Who is this course for? Working Professionals, A-Level holders, professionals working in range of industries looking for a career in finance and accountancy Requirements For entry onto the OTHM Level 4 Diploma in Accounting and Business qualification, learners must possess: Relevant NQF/QCF/RQF Level 3 Award/Diploma or at the level of GCE/GCSE or equivalent qualification Learner must be 18 years or older at the beginning of the course Mature learners (over 21) with management experience (learners must check with Admission Counsellors at LSBR regarding this experience prior to registering for the programme) Career path Progress to: Year 2 of a Three-year UK Bachelor's degree Completion of your qualification will meet the University standard academic entry requirements. However, each applicant will be subject to individual assessment and other entry requirements which may affect university entry. Certificates Certificate of Achievement Digital certificate - Included Once you complete the course, you would be receiving a Physical hard copy of your Diploma along with its Transcript which we would Courier to your address via DHL or Royal Mail without any additional charge

This one-day course introduces the field of user experience and provides an excellent entry point to our other specialised training courses. UX processes and practices have become a central component of product design, service design and web design.

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Duration 2 Days 12 CPD hours Overview What is JIRA Software? Managing agile projects using JIRA Software Managing project backlog Managing iterations / sprints Managing releases / versions Managing project components Managing security Managing fields and screens Managing custom issue types Viewing various burn-down/burn-up reports This course introduces students to JIRA Software which is one of the most popular agile project management tool. Agile methods help in accelerating the delivery of initial business value. Continuous planning and feedback ensures that value is maximized throughout the development process. JIRA Software lets you manage project backlog, plan and execute sprints, and manage releases. It also lets you view useful reports, such as, velocity, various burndown / burn-up charts. Navigating JIRA Connecting to JIRA Software JIRA Account System Dashboard Sidebars Global Sidebar Search Help Dashboards Projects Boards Issues Project Sidebar Summary Managing Projects What is a Project? What is a Project (Contd.)? Backlog Sprints Versions / Releases Issues What is Component? Project Name and Key Project Key Format Editing Project Key Caveats Editing Project Key Deleting Project Summary Managing Versions What is Version What is Version (Contd.)? Merging Versions Other Version Options Version Fields What is Version? Summary Managing Issues Issues What are Epics? Epics ? Types Creating a new Epic What is a Story? Creating a Story Story Estimation Tasks Sub-tasks Summary Managing Sprints Sprints What is typically done in Sprint Planning? Velocity Agile Board Sprint Naming Convention Sprint Execution Summary Search & Using JQL Search Search Types JQL JQL Examples Sharing search result Save Search and Reuse in a Board Summary Working with JIRA Dashboards and Reports What is a JIRA Dashboard? Creating a JIRA Dashboard Choosing a Dashboard Layout What is a Gadget? Gadgets Available Out-of-the-box Adding a Gadget to a Dashboard Adding a Gadget to a Dashboard (Example Calendar Gadget) Moving a Gadget Removing a Gadget from a Dashboard Viewing Dashboard as a Wallboard Deleting a Dashboard JIRA Reports Generating a JIRA Report Generating a JIRA Report (Example ? Burndown Chart) Viewing the Burndown Chart Report Categories Available Out-of-the-box Agile Reports Issue Analysis Reports Forecast & Management Reports For further details ? Summary Jira Agile Common Jira Software boards Scrum Agility Kanban Scrum vs. Kanban Scrumban History of Kanban Kanban for software teams Kanban boards Kanban boards (Contd.) Kanban cards The benefits of Kanban Planning flexibility Shortened time cycles Fewer bottlenecks Visual metrics Continuous Delivery Kanban ? Kanban backlog Summary Miscellaneous Issue Features Voting Watching an Issue Adding/Removing Labels Linking Issues Linking Issue (Contd.) Commenting on Issue Attaching a File to an Issue Attaching a File to an Issue (Contd.) Cloning (Copying) an Issue Cloning (Copying) an Issue (Contd.) Cloning (copying) an Issue (Contd.) Viewing an Issue?s Change History Viewing an Issue's Change History (Contd. Summary Managing Fields & Screens (OPTIONAL: TIME PERMITTING) Fields OOB Fields Custom Fields Field Type Screens Summary

Effective Personal Productivity will help you in four crucial areas: Become highly organised and effective in your own area of day-to-day responsibility. Set and track personal and team goals, manage priorities and hit project deadlines. Improve delegation and communication skills, ensuring the right work is done the right way by the right people. Identify areas for continual improvement in and outside of work and implement strategies to maintain a healthy, well-balanced life.

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#cpc #cpcexam #driver_training #drivertraining #grantham #hgv #lincolnshire #training_course #transport #transportmanager

Vectorworks Evening Course face to face One to one