Health Data Science (September 2022) About the course Data science is revolutionising how medicine is understood and this course, offered by the Usher Institute, will equip healthcare professionals with the key foundations and data skills that are needed to address the widely-recognised opportunities that data can bring to biomedicine and healthcare. It is acknowledged there is a shortage of data skills in the healthcare sector and this is the perfect course for someone looking to gain these knowledge. The course provides an introduction to key concepts, principles and methods of data science in health, enabling exploration of the potential for data to transform healthcare. Learn how to use current data science tools to process healthcare data for effective analysis and reporting and gain practical experience in working with data. Gain critical understandings of ethical and legal implications of working with healthcare data. Further information can be found in the University's course catalogue: Health Data Science Who is the course for? This course is for anyone working in health or social care or computational roles who is interested in starting a career in data science OR graduates who are seeking to develop data science skills that can be applied in health, social and care services. This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection. Accreditation This course is accredited by the Federation for Informatics Professionals in Health and Social Care (FEDIP). FEDIP accreditation highlights educational providers who are furthering the development of the health and care informatics profession. The Federation is comprised of the leading professional bodies in health and care informatics and accredits this course as part of our recommended learning for health and care informatics professionals in this field. Entry requirements As this course is designed mainly for health and care professionals, we expect our students to have qualifications or work experience in such environments (e.g. NHS National Services, Acute/Community/Public health), Third sector organisations, Social Services, Nursing homes, pharmaceutical companies, diagnostic laboratories, etc.). An understanding of the fundamentals of maths and statistics (at Higher level) would be advantageous but is not a prerequisite for joining the course. You should be educated to a degree level as this course is catering for those seeking postgraduate academic credit. However, professionals who are involved with managing services and caseloads and have 5 years of work experience may also apply even if they do not hold a degree qualification. Check whether your international qualifications meet our general entry requirements: Entry requirements by country You must be comfortable studying and learning in English if it is not your first language. Learning Outcomes Explain and critically discuss key concepts, principles and methods of data science in health. Apply a range of specialised data science techniques to different medical and healthcare scenarios. Analyse health data with the use of the R programming language, including summarisation, visualisation and interpretation. Critically examine the ethical, societal and regulatory principles and implications of data science in health. How will the course be delivered? This is a 10-week online course (plus 2 weeks for assessment), comprising a total of 100 hours of study. It is based around short recorded videos, which are complemented with readings and discussions in the forums. Hands-on programming tasks in R will equip students with key data skills, and online tutorials will allow students to ask questions and discuss topics of interest. Health Data Science is designed for busy health professionals and all live lectures will be recorded so students can view them at a convenient time. There are two assignments which need to be completed and some live tutorials, usually scheduled at 10am and 6pm. These will also be recorded, but it is recommended you try to attend at least one of the time slots. The course will require engagement throughout. Usually, live tutorials are scheduled for Wednesdays, 6pm but there are weeks (week 2, 6, and 8) in which we also offer a 10am session. The course organiser also offers regular online drop-in sessions: Thursdays at 6pm. All tutorials and drop-in sessions are recorded and available afterwards. There are no exams for this course - assessment is 100% coursework. Your final mark will be based on the following: Weekly Quizzes with a short number of questions on the topics covered each week (20% i.e. 10 weeks x 2%) Programming Assignment where you use R to process, analyse and visualise data, as well as report on your analysis (50%) Essay-Style Assignment where you discuss the societal and ethical implications of data science in health (30%) 1,000 words Course fees and funding Course fees for 22/23 are £1010 but funded places are available for people employed or unemployed in Scotland (residency requirements apply). Funding Through the Scottish Funding Council (SFC) Upskilling Fund, a limited number of fully-funded places are available on Data Upskilling Short Courses at The University of Edinburgh. Eligibility Funded places are available to those who meet SFC fee waiver criteria: “Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.” If you are from outside Scotland, you need to have settled status in the UK and meet other residency criteria: be ordinarily resident in the United Kingdom, the Channel Islands or the Isle of Man for the three years immediately before course start date, and have ‘settled status’ in the UK (as set out in the Immigration Act 1971) at the course start date, and be ordinarily resident in Scotland at the course start date. You can find out more about residency criteria on the SAAS website or in this summary. Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. You can check your likely fee status here: https://www.ed.ac.uk/tuition-fees/fee-status/work-out Please email us at upskilling@ed.ac.uk if you would like to discuss your funding eligibility before applying. Please note that full-time students (including full-time PhD students) are not eligible for funding. What will I receive upon completion? You will receive a certificate of completion after the final assessment date if you have submitted your coursework. How to apply Applications for September 2022 are now closed. Health Data Science will run again in this academic year (January and April 2023). To be kept up to date on when this, and other courses within the Data Upskilling Short Courses portfolio, are running please join our Mailing List Related courses Big Data and Analytics in Health and Social Care Data Ethics in Health and Social Care Entrepreneurship and Data-Driven Innovation in Health and Social Care Implementation Science in Health and Social Care Practical Image Analysis 1 Practical Introduction to Data Science Systems Thinking in Health and Social Care User-Driven Service Design in Health and Social Care Further Study with UoE This course is offered as part of Data Science for Health and Social Care, an innovative online programme looking to equip students with the data science skills, capabilities and competencies to realise the value of data in a healthcare setting. You can use credits achieved on this course towards postgraduate study on this programme (MSc, PG Diploma or PG Certificate), subject to approval by the Programme Director. You may also be able to use credits achieved on this course towards other University of Edinburgh postgraduate programmes, subject to the approval of the relevant Programme Director. Degree Finder Contact Us Image Sep 19 2022 00.00 - Nov 25 2022 23.59 Health Data Science (September 2022) Learn the key foundations and data skills that are needed for data-driven innovation with this online course for health and social care professionals. Subscribe to our Mailing List
Health Data Science (September 2022) About the course Data science is revolutionising how medicine is understood and this course, offered by the Usher Institute, will equip healthcare professionals with the key foundations and data skills that are needed to address the widely-recognised opportunities that data can bring to biomedicine and healthcare. It is acknowledged there is a shortage of data skills in the healthcare sector and this is the perfect course for someone looking to gain these knowledge. The course provides an introduction to key concepts, principles and methods of data science in health, enabling exploration of the potential for data to transform healthcare. Learn how to use current data science tools to process healthcare data for effective analysis and reporting and gain practical experience in working with data. Gain critical understandings of ethical and legal implications of working with healthcare data. Further information can be found in the University's course catalogue: Health Data Science Who is the course for? This course is for anyone working in health or social care or computational roles who is interested in starting a career in data science OR graduates who are seeking to develop data science skills that can be applied in health, social and care services. This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection. Accreditation This course is accredited by the Federation for Informatics Professionals in Health and Social Care (FEDIP). FEDIP accreditation highlights educational providers who are furthering the development of the health and care informatics profession. The Federation is comprised of the leading professional bodies in health and care informatics and accredits this course as part of our recommended learning for health and care informatics professionals in this field. Entry requirements As this course is designed mainly for health and care professionals, we expect our students to have qualifications or work experience in such environments (e.g. NHS National Services, Acute/Community/Public health), Third sector organisations, Social Services, Nursing homes, pharmaceutical companies, diagnostic laboratories, etc.). An understanding of the fundamentals of maths and statistics (at Higher level) would be advantageous but is not a prerequisite for joining the course. You should be educated to a degree level as this course is catering for those seeking postgraduate academic credit. However, professionals who are involved with managing services and caseloads and have 5 years of work experience may also apply even if they do not hold a degree qualification. Check whether your international qualifications meet our general entry requirements: Entry requirements by country You must be comfortable studying and learning in English if it is not your first language. Learning Outcomes Explain and critically discuss key concepts, principles and methods of data science in health. Apply a range of specialised data science techniques to different medical and healthcare scenarios. Analyse health data with the use of the R programming language, including summarisation, visualisation and interpretation. Critically examine the ethical, societal and regulatory principles and implications of data science in health. How will the course be delivered? This is a 10-week online course (plus 2 weeks for assessment), comprising a total of 100 hours of study. It is based around short recorded videos, which are complemented with readings and discussions in the forums. Hands-on programming tasks in R will equip students with key data skills, and online tutorials will allow students to ask questions and discuss topics of interest. Health Data Science is designed for busy health professionals and all live lectures will be recorded so students can view them at a convenient time. There are two assignments which need to be completed and some live tutorials, usually scheduled at 10am and 6pm. These will also be recorded, but it is recommended you try to attend at least one of the time slots. The course will require engagement throughout. Usually, live tutorials are scheduled for Wednesdays, 6pm but there are weeks (week 2, 6, and 8) in which we also offer a 10am session. The course organiser also offers regular online drop-in sessions: Thursdays at 6pm. All tutorials and drop-in sessions are recorded and available afterwards. There are no exams for this course - assessment is 100% coursework. Your final mark will be based on the following: Weekly Quizzes with a short number of questions on the topics covered each week (20% i.e. 10 weeks x 2%) Programming Assignment where you use R to process, analyse and visualise data, as well as report on your analysis (50%) Essay-Style Assignment where you discuss the societal and ethical implications of data science in health (30%) 1,000 words Course fees and funding Course fees for 22/23 are £1010 but funded places are available for people employed or unemployed in Scotland (residency requirements apply). Funding Through the Scottish Funding Council (SFC) Upskilling Fund, a limited number of fully-funded places are available on Data Upskilling Short Courses at The University of Edinburgh. Eligibility Funded places are available to those who meet SFC fee waiver criteria: “Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.” If you are from outside Scotland, you need to have settled status in the UK and meet other residency criteria: be ordinarily resident in the United Kingdom, the Channel Islands or the Isle of Man for the three years immediately before course start date, and have ‘settled status’ in the UK (as set out in the Immigration Act 1971) at the course start date, and be ordinarily resident in Scotland at the course start date. You can find out more about residency criteria on the SAAS website or in this summary. Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. You can check your likely fee status here: https://www.ed.ac.uk/tuition-fees/fee-status/work-out Please email us at upskilling@ed.ac.uk if you would like to discuss your funding eligibility before applying. Please note that full-time students (including full-time PhD students) are not eligible for funding. What will I receive upon completion? You will receive a certificate of completion after the final assessment date if you have submitted your coursework. How to apply Applications for September 2022 are now closed. Health Data Science will run again in this academic year (January and April 2023). To be kept up to date on when this, and other courses within the Data Upskilling Short Courses portfolio, are running please join our Mailing List Related courses Big Data and Analytics in Health and Social Care Data Ethics in Health and Social Care Entrepreneurship and Data-Driven Innovation in Health and Social Care Implementation Science in Health and Social Care Practical Image Analysis 1 Practical Introduction to Data Science Systems Thinking in Health and Social Care User-Driven Service Design in Health and Social Care Further Study with UoE This course is offered as part of Data Science for Health and Social Care, an innovative online programme looking to equip students with the data science skills, capabilities and competencies to realise the value of data in a healthcare setting. You can use credits achieved on this course towards postgraduate study on this programme (MSc, PG Diploma or PG Certificate), subject to approval by the Programme Director. You may also be able to use credits achieved on this course towards other University of Edinburgh postgraduate programmes, subject to the approval of the relevant Programme Director. Degree Finder Contact Us Image Sep 19 2022 00.00 - Nov 25 2022 23.59 Health Data Science (September 2022) Learn the key foundations and data skills that are needed for data-driven innovation with this online course for health and social care professionals. Subscribe to our Mailing List
Sep 19 2022 00.00 - Nov 25 2022 23.59 Health Data Science (September 2022) Learn the key foundations and data skills that are needed for data-driven innovation with this online course for health and social care professionals.
