Python for Biologists: Beginners Level
Empower Your Research with Python: Program Your Way to Discovery in Biology
Online/ e-LMS
Self Paced
Moderate
1 Month
About
Python for Biologists: Beginners Level is designed to introduce Python programming in a context that is immediately applicable to biological sciences. Over one month, participants will learn how to handle biological data, perform statistical analysis, visualize results, and automate repetitive tasks using Python. The course emphasizes practical, hands-on exercises tailored to common biological data scenarios such as sequence analysis, ecological data interpretation, and genetic data processing.
Aim
This program aims to equip biologists and life science researchers with fundamental Python programming skills to enhance their data analysis capabilities. By the end of the course, participants will be adept at using Python to automate tasks, analyze biological data, and contribute to complex bioinformatics projects.
Program Objectives
- Introduce participants to Python programming concepts and syntax.
- Provide an overview of the applications of Python in different biological domains.
- Teach participants how to analyze gene sequences, proteins, and transcriptomic data using Python.
- Familiarize participants with structural biology techniques such as X-ray crystallography, NMR, and circular dichroism and how Python can aid in their analysis.
- Explore pathway analysis and its significance in understanding cellular dynamics, reconstruction, and biomarker prediction using Python-based tools.
Program Structure
Module 1: Sequence Analysis
- Introduction to Python for Biologists.
- Python Basics: Variables, Data Types, and Control Structures
- Gene and Genome Analysis with Python
- Protein and Proteome Analysis with Python
- Transcriptome Analysis with Python
Module 2: Structure Analysis
- Introduction to Structural Biology and Python’s Role
- Analyzing X-ray Crystallography Data with Python
- NMR Data Analysis with Python
- Circular Dichroism (CD) Spectroscopy and Python Analysis
Module 3: Pathway Analysis
- Introduction to Pathway Analysis and Its Significance.
- Cellular Dynamics Modeling with Python
- Pathway Reconstruction
- Biomarker Prediction using Python
Participant’s Eligibility
- Undergraduate or graduate students in Biology, Biochemistry, Genetics, or related fields.
- Research scientists and academic professionals interested in bioinformatics.
- Healthcare professionals looking to enhance data analysis skills in biological research.
Program Outcomes
- Mastery of Python for biological data analysis
- Ability to automate data processing tasks in biological research
- Enhanced capability to visualize and interpret complex datasets
- Skills in applying computational techniques to real-world biological problems
- Readiness to contribute to interdisciplinary research teams
Fee Structure
Standard Fee: INR 4,998 USD 110
Discounted Fee: INR 2499 USD 55
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
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Certificate
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
Exam | Weightage |
---|---|
Mid Term Assignments | 50 % |
Project Report Submission (Includes Mandatory Paper Publication) | 50 % |
To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.
Program Deliverables
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Future Career Prospects
- Bioinformatician
- Computational Biologist
- Genetic Data Analyst
- Ecological Data Scientist
- Clinical Research Analyst
- Biotechnology Software Developer
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