Programme Parameters
Graduate / Intermediate
3 Days (4.5 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Biology is a data-intensive field, with applications spanning genomics, ecology, bioinformatics, and laboratory research. With the growing need for accessible, user-friendly tools, the development of mobile and web applications has become increasingly important. These apps can aid in everything from data visualization and analysis to collaboration and communication in the lab and field. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Biology is a data-intensive field, with applications spanning genomics, ecology, bioinformatics, and laboratory research. With the growing need for accessible, user-friendly tools, the development of mobile and web applications has become increasingly important. These apps can aid in everything from data visualization and analysis to collaboration and communication in the lab and field.
📋 Course Objectives
1. Translate biotechnology theory into practical, reproducible analysis.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in biotechnology
• R&D engineers and working professionals applying biotechnology in industry
• Academics and educators building research or teaching capacity in biotechnology
🚀 Key Learning Outcomes
• A portfolio-grade biotechnology deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Designing for a Research Workflow
• Observing the actual lab or field process before specifying anything
• Web, mobile or desktop chosen on where the work physically happens
• Scoping to a tool that gets finished rather than a platform that does not
Modelling Biological Information
• Sample, experiment and result entities and the relationships between them
• Standard identifiers and formats — FASTA, FASTQ, ontology terms
• Validation at entry, since biological data is entered by hand more than expected
Interface and Visualisation
• Forms designed for gloved hands, small screens and interruption
• Plotting libraries and interactive visualisation of experimental data
• Offline capability and synchronisation for field work without connectivity
Connecting to Bioinformatics
• Calling NCBI, Ensembl and UniProt APIs, with rate limits and caching
• Running or queuing analysis jobs from an application
• Handling long-running tasks without freezing the interface
Beyond the First Release
• Ethics, consent and data protection when human subject data is involved
• Testing, documentation and the abandonment that afflicts research software
• Deployment, citation and handover when the developer leaves the lab
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Jupyter Notebook |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Microsoft Excel |
| Covered Tool / Platform | Relevant Online Databases |
Frequently Asked Questions
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