Bioinformatics Foundational and biological data Analysis Course: Theory and Practical
- Duration:
- Certificate:
- Next Course:
- The “Bioinformatics Foundational and Biological Data Analysis Course” is an eight-day online training that offers both theoretical and practical insights into handling biological and genetic data. This knowledge have many potential applications, including disease research, genome analysis, medicinal development, and more.
- Over 32 hours, participants will engage with advanced data analysis methodologies and receive hands-on training using the latest analytical tools for specific biological data types.
- The course targets researchers, biomedical professionals, data scientists, and others with backgrounds in biosciences or computer sciences, aiming to enhance their skills in bioinformatics, data management, and Python programming.
Learning Objectives
By the end of the program, participants will be able to learn the following:
- Outline what bioinformatics.
- Describe the importance of data management.
- Recall which resources are available by the course.
- Know where to find information about genes and proteins
- Coding cells
- Working with python
- Integration with Drive
Accreditation
- Candidate will receive completion certificate issued by Itqan Academy
Who Should Attend This Course?
Researchers who want to analysis their data this may include but not restricted to:
- Natural science/technology
- Biomedical researchers
- Data scientist and analysts
- Doctors, pharmacists, public health
- Computer science or engineering, school of math
- Any Branch with a background of biosciences or computer sciences
Course Format
- Online tutoring and lectures
- Online practical exercise
- 2 Sessions per week for 4 weeks, each session is 4 hours
How Can I Get a Completion Certificate
Attend
70% of the course lectures.
Pass
The required assessment
Participate
In Case scenarios, quizzes and discussion
Instructors
Doctor
Omnia Yousif
- PhD in Molecular Biology, Department of Molecular Biology, Institute of Endemic Diseases (IEND). Head of research at research directorate.
Mr
Mudather Salih Ibrahim Hassan
- MSc, Department of Computer Science, School of Mathematical Science, Database administrator & Data analyst, Bio informatics lab, Institute of Endemic Disease (IEND).
Mr.
Muiz Mohamed
- B.Sc. in Statistics and Computer Science, bioinformatician and researcher, Database administrator & Data analyst, Bio informatics lab, Institute of Endemic Disease (IEND).
FAQ
How will this course enhance my ability to analyze biological or genetic data?
The course provides practical training on handling and analyzing biological datasets, focusing on tools and techniques like Python programming. You’ll learn to apply these skills directly to real-world challenges in research, genomics, and biotechnology.
Do I need prior experience in bioinformatics or coding to join?
No prior experience is necessary. The course is designed to accommodate beginners by starting with foundational concepts and gradually building up to advanced techniques in bioinformatics and Python programming.
What practical skills will I gain that can be applied to my career or research?
You will learn to:
- Extract and analyze genetic data.
- Use Python for data management and processing.
- Identify valuable bioinformatics resources for research.
- Apply data integration techniques for large datasets.
- These skills are in high demand in medical research, genomics, and computational biology.
What makes this course different from other bioinformatics courses?
This course offers a unique blend of:
- Hands-on experience with real-world datasets.
- Guidance from expert instructors with strong academic and practical backgrounds.
- Focus on actionable skills, from coding to data interpretation, ensuring you can immediately apply what you learn.
Will I work on real-world projects, and how will they help me?
You’ll engage in a real-world simulated exercises like analyzing genetic sequences and building bioinformatics pipelines using Python. These projects will prepare you to solve practical problems in academic research or industry applications, boosting your confidence and expertise.
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