Master the interplay between Big Data and Machine Learning through 150 hours of the best digital teaching"

One of the major challenges faced by healthcare professionals in  Big Data  management lies in preserving the security of sensitive information. In the course of their respective jobs, doctors have access to private user data to take into account when planning therapies. Therefore, physicians need to learn the most effective tactics to mitigate risk in the handling of this information. In this context, they must acquire advanced skills to successfully overcome data confidentiality challenges in the field of biomedical  Big Data

To help them with this task, TECH implements a Postgraduate certificate that will develop the most cutting-edge practical strategies for the application of  Big Data  in clinical decision making. The curriculum will analyze the implementation of interactivity systems in visualizations to improve understanding. Along the same lines, the curriculum will delve into a wide range of effective communication tactics for graduates to present complex analysis results. In addition, didactic materials will include the exploration of success stories in the implementation of biomedical big data in clinical research.

Along these lines, TECH offers a 100% online educational environment, tailored to the needs of busy professionals seeking to advance their careers. In addition, it will employ the  Relearning methodology, based on the repetition of key concepts to fix knowledge and facilitate learning. In this way, the combination of flexibility and a robust pedagogical approach makes it highly accessible. Students will also have access to a library full of multimedia resources in different multimedia formats such as interactive summaries, explanatory videos and infographics. All that will be required is that experts have an electronic device with Internet access to access the Virtual Campus, where they will find the most dynamic academic content on the market.

You will develop Artificial Intelligence algorithms to predict clinical outcomes, optimize treatment protocols and improve efficiency in the identification of relevant biomarkers"

This Postgraduate certificate in Big Data Analytics and Machine Learning in Clinical Research  contains the most complete and up-to-date program on the market. The most important features include:

• Development of practical cases presented by experts in Big Data Analytics and Machine Learning in Clinical Research
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

You will address the integration of Big Data and Machine Learning in Clinical Research, improving your understanding about the most complex diseases"

The program’s teaching staff includes professionals from the field who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the students will be assisted by an innovative interactive video system created by renowned and experienced experts.

You will delve into Data Mining in clinical records to extract valuable patterns, all through innovative multimedia resources"

Thanks to the Relearning system used by TECH you will reduce the long hours of study and memorization"

This Postgraduate certificate will focus on the Big Data tools most commonly used in Clinical Research, thus immersing in Data Mining in clinical and biomedical records. The academic itinerary will delve into various predictive analysis techniques that will improve clinical prognoses. The syllabus will also address Machine Learning models in epidemiology and public health, as well as the analysis of biological networks to understand the patterns of pathologies. In addition, the didactic contents will develop predictive tools, advanced visualization skills and communication of complex data.

You will acquire skills to address significant challenges, such as the efficient management of large volumes of information, analyzing their practical applications in the biomedical sector"

Module 1. Big Data Analytics and Machine Learning in Clinical Research

1.1. Big Data in Clinical Research: Concepts and Tools

1.1.1. The Explosion of Data in Clinical Research
1.1.2. Concept of Big Data and Main Tools
1.1.3. Applications of Big Data  in Clinical Research

1.2. Data Mining in Clinical and Biomedical Registries

1.2.1. Main Methodologies for Data Mining
1.2.2. Data Integration from Clinical and Biomedical Registries
1.2.3. Detection of Patterns and Anomalies in Biomedical and Clinical Records

1.3. Machine Learning Algorithms in Biomedical Research

1.3.1. Classification Techniques in Biomedical Research
1.3.2. Regression Techniques in Biomedical Research
1.3.4. Unsupervised Techniques in Biomedical Research

1.4. Predictive Analytics Techniques in Clinical Research

1.4.1. Classification Techniques in Clinical Research
1.4.2. Regression Techniques in Clinical Research
1.4.3. Deep Learning in Clinical Research

1.5. AI Models in Epidemiology and Public Health

1.5.1. Classification Techniques in Epidemiology and Public Health
1.5.2. Regression Techniques in Epidemiology and Public Health
1.5.3. Unsupervised Techniques in Epidemiology and Public Health

1.6. Analysis of Biological Networks and Disease Patterns

1.6.1. Exploration of Interactions in Biological Networks for the Identification of Disease Patterns
1.6.2. Integration of Omics Data in Network Analysis to Characterize Biological Complexities
1.6.3. Application of machine learning  Algorithms for Disease Pattern Discovery

1.7. Development of Tools for Clinical Prognostics

1.7.1. Creation of Innovative Tools for Clinical Prognosis Based on Multidimensional Data
1.7.2. Integration of Clinical and Molecular Variables in the Development of Prognostic Tools
1.7.3. Evaluating the Effectiveness of Prognostic Tools in Various Clinical Contexts

1.8. Advanced Visualization and Communication of Complex Data

1.8.1. Use of Advanced Visualization Techniques to Represent Complex Biomedical Data
1.8.2. Development of Effective Communication Strategies for Presenting Complex Analysis Results
1.8.3. Implementation of Interactivity Tools in Visualizations to Enhance Comprehension

1.9. Data Security and Challenges inBig DataManagement

1.9.1. Addressing Data Security Challenges in the Context of Biomedical Big Data
1.9.1. Strategies for Privacy Protection in the Management of Large Biomedical Data Sets
1.9.3. Implementation of Security Measures to Mitigate Risks in the Management of Sensitive Data

1.10. Practical Applications and Case Studies in Biomedical Big Data

1.10.1. Exploration of Successful Cases in the Implementation of Biomedical  Big Data n Clinical Research
1.10.2. Development of Practical Strategies for the Application of Big Data  in Clinical Decision Making
1.10.3. Impact Assessment and Lessons Learned through Case Studies in the Biomedical Domain

As it is an online Postgraduate certificate, you will be able to combine your studies with the rest of your daily activities”