This intensive course is designed to provide a deep understanding and practical experience in biomedical data analysis. Participants will explore advanced statistical methods, data visualisation techniques, and machine learning applications tailored for biomedical research. The course combines theoretical knowledge with hands-on sessions, enabling participants to analyse complex biomedical datasets effectively and make data-driven decisions in their research and practice.
Upon completion of this course, participants will be able to:
- Master advanced statistical methods for biomedical data analysis.
- Develop skills in data visualisation and interpretation.
- Apply machine learning techniques to biomedical datasets.
- Gain practical experience with data analysis tools and software.
- Enhance their ability to conduct and publish high-quality biomedical research.
This course is intended for Biomedical researchers:
- Medical professionals
- Data scientists and analysts
- Graduate students in biomedical and life sciences
- Healthcare professionals interested in data analysis
The course employs a blend of instructional methods, including:
- Interactive lectures
- Hands-on data analysis sessions
- Group discussions and case studies
- Expert-led Q&A sessions
- Comprehensive course materials and resources
Day 5 of each course is reserved for a Q&A session, which may occur off-site. For 10-day courses, this also applies to day 10
Section 1: Foundations of Biomedical Data Analysis
- Types of biomedical data: clinical, genomic, imaging, etc.
- Data collection and preprocessing techniques
- Descriptive and inferential statistics
- Data cleaning and preparation
Section 2: Advanced Statistical Methods
- Linear and logistic regression
- Survival analysis and mixed-effects models
- Bayesian statistics and applications
- Multivariate analysis techniques
Section 3: Data Visualization and Interpretation
- Principles of effective data visualisation
- Tools for data visualisation: R, Python, specialised software
- Creating plots, charts, and dashboards
- Communicating findings to diverse audiences
Section 4: Machine Learning in Biomedical Research
- Overview of machine learning concepts
- Supervised learning: decision trees, random forests, neural networks
- Unsupervised learning: clustering, dimensionality reduction
- Practical applications of machine learning in biomedical research
Section 5: Practical Applications and Case Studies
- Hands-on data analysis with real biomedical datasets
- Applying statistical and machine learning techniques
- Real-world case studies from biomedical research
- Course review, Q&A session, and certification ceremony
عند إتمام هذه الدورة التدريبية بنجاح، سيحصل المشاركون على شهادة إتمام التدريب من Holistique Training. وبالنسبة للذين يحضرون ويكملون الدورة التدريبية عبر الإنترنت، سيتم تزويدهم بشهادة إلكترونية (e-Certificate) من Holistique Training.
شهادات Holistique Training معتمدة من المجلس البريطاني للتقييم (BAC) وخدمة اعتماد التطوير المهني المستمر (CPD)، كما أنها معتمدة وفق معايير ISO 9001 وISO 21001 وISO 29993.
يتم منح نقاط التطوير المهني المستمر (CPD) لهذه الدورة من خلال شهاداتنا، وستظهر هذه النقاط على شهادة إتمام التدريب من Holistique Training. ووفقًا لمعايير خدمة اعتماد CPD، يتم منح نقطة CPD واحدة عن كل ساعة حضور في الدورة. ويمكن المطالبة بحد أقصى قدره 50 نقطة CPD لأي دورة واحدة نقدمها حاليًا.
التصنيفات
الصحة والسلامة والبيئة, الرعاية الصحية والصيدلانية, تطبيقات تكنولوجيا المعلومات والكمبيوتر,العلامات
- كود الكورس PI1 - 129
- نمط الكورس
- المدة 5 أيام
الدورات المميزة
