No Code & Agentic AI
for Life Sciences
Accelerate your biomedical discovery workflow. Learn Generative AI and Agentic AI — no coding required.
Why this program?
The evolution of AI from Machine Learning to Deep Learning, and now to Generative and Agentic AI, is transforming the Life Sciences. This program bridges the gap.
Designed for undergraduates, graduate students, and early-career professionals, you will learn to build multi-step agentic systems, automate literature reviews, and analyze Omics data—all without writing a single line of code.
Tools You Will Master
Claude
Advanced reasoning and coding agent
NotebookLM
Multi-document synthesis and research
Google Colab + Gemini
AI-assisted coding and analysis
Why No Code?
In today's fast-evolving AI landscape, the power to analyze complex biological data and automate literature reviews is no longer limited to computational experts. No-code platforms are democratizing bioinformatics by enabling researchers, clinicians, and students to harness advanced Agentic AI, Generative AI, and ML without any coding expertise.
Accelerate Discovery
Eliminate the coding barrier to rapidly deploy AI solutions for target identification and biomarker classification.
Lower Costs and Risks
Validate biological hypotheses quickly using standardized, no-code analytical pipelines before expensive lab investments.
Enable Rapid Prototyping
Quickly build and test agentic workflows for literature synthesis without waiting on bioinformatics cores.
Tap into Agentic AI
Leverage autonomous agents that can plan, decide, and act to synthesize complex biomedical literature independently.
Bridge the Biology-Computation Gap
Empower domain experts—biologists and clinicians—to interact directly with Omics data and experiment with AI.
No Code AI Landscape
Agentic AI
Design autonomous workflows that handle complex, multi-step tasks such as orchestrating Omics pipelines, literature synthesis, and experimental planning.
Generative AI
Automatically generate comprehensive research summaries, draft clinical protocols, or design novel molecular structures using state-of-the-art foundation models.
Machine Learning
Predict clinical outcomes, discover novel biomarkers, segment single-cell populations, and optimize drug targeting with no-code ML prediction platforms.
Who Is This Program For?
Undergraduates
Break into the high-demand field of computational biology and gain a massive competitive edge by mastering AI workflows without needing to learn Python or R.
Grad Students & Researchers
Accelerate your thesis, literature reviews, and Omics data analysis. Spend less time struggling with code and more time interpreting groundbreaking biological results.
Professionals & Clinicians
Integrate powerful Generative and Agentic AI into your drug discovery, clinical research, or daily workflows without the overhead of hiring a dedicated bioinformatics team.
Program Benefits
Live Mentorship from an Industry Expert
Work directly with Md. Jubayer Hossain (Founder & CEO, DeepBio Ltd) throughout all 4 weeks—no teaching assistants, no substitutes.
Concrete Research Output
Move from curiosity to discovery with a highly structured roadmap designed to yield a concrete, submittable biological research output.
100% No-Code Architecture
Master state-of-the-art tools like Claude, NotebookLM, and Google Colab + Gemini without needing to write a single line of code.
Hands-On Omics & Clinical Projects
Analyze real scRNA-seq datasets, evaluate predictive clinical models, and execute pathway analysis using industry-standard graphical platforms.
Accelerated Biomedical Discovery
Learn to build automated, multi-step agentic workflows that drastically accelerate literature reviews and drug discovery pipelines.
Curriculum
AI Foundations & Prompt Engineering
- No-Code Tools Setup & Foundations
- Agentic AI Landscape for Life Sciences
- Prompt and Context Engineering Frameworks
- Plan → Approve → Execute → Iterate Framework
Literature Search, Review, and Synthesis & Omics Data
- Agentic Literature Research Review
- PubMed Monitor to Claude Summarizer
- Omics Data Analysis — No Code Pipeline (Bulk RNA-seq)
- scRNA-seq intro: Seurat/Scanpy workflow
Deep Learning Prediction Methods
- Prepare Claude for AI Workflows
- Model Selection and Prompt Engineering
- Biomarker Classification
- Responsible AI: bias in predictive models
Drug Discovery & Image Analysis
- Target identification with AI (Open Targets)
- AlphaFold for drug target structure
- Biomedical Image Analysis
- AI vs Radiologist Accuracy Case Studies
Tools & Packages
Industry-standard libraries — used through a no-code workflow
Python Packages
R Packages
✦ No prior coding experience needed — all workflows are guided and abstracted
Program Outcomes
After this program, you will be able to:
Design and run multi-step agentic AI workflows for biomedical literature reviews and drug discovery pipelines
Analyze real single-cell RNA-seq and multi-omics datasets using no-code graphical platforms
Evaluate and interpret predictive clinical models without writing a single line of code
Execute pathway enrichment and network analysis using industry-standard visual tools
Produce a complete, submittable biological research output from raw data to final report
Use Claude, NotebookLM, Google AI Studio, and Colab + Gemini as an integrated research stack
Navigate the full AI-for-life-sciences tool landscape and select the right tool for any research task
Accelerate your research output and compete at the frontier of computational biology — no coding background required
Certificate of Completion
Awarded to every participant who completes the program
No Code & Agentic AI for Life SciencesCERTIFICATE OF COMPLETION
This is to certify that
has successfully completed the 4-Week Live Program on
No Code & Agentic AI for Life Sciences,
demonstrating proficiency in Generative AI, Agentic Workflows,
and AI-powered biomedical research tools.
Jubayer
Md. Jubayer Hossain
Founder & CEO, DeepBio Ltd
June 30, 2025
Date of Completion
Sample date
* Sample certificate — recipient name and date filled upon completion
Enroll Now
For undergraduate and graduate students
- ✓4 weeks live sessions
- ✓Direct mentorship
- ✓Hands-on projects
- ✓Certificate of completion
- ✓Community access
For researchers, clinicians & industry professionals
- ✓4 weeks live sessions
- ✓Direct mentorship
- ✓Hands-on projects
- ✓Certificate of completion
- ✓Community access
- ✓Priority Q&A access
Exclusive for DeepBio Lab Members (RA, Ambassador)
- ✓4 weeks live sessions
- ✓Direct mentorship
- ✓Hands-on projects
- ✓Certificate of completion
- ✓Community access
- ✓Priority Q&A access
- ✓Member-exclusive support
Md. Jubayer Hossain
Founder & CEO, DeepBio Ltd
Meet Your Mentor
Md. Jubayer Hossain is a bioinformatician and computational biologist with five years of experience spanning both active research and teaching. Since 2020, he has trained over 3,000 students — from complete beginners to graduate researchers — in the practical skills required to work with real biological data.
As Founder & CEO of DeepBio Ltd, Jubayer combines research rigor with a structured approach to education. His teaching is grounded in what he does daily: designing and running computational analyses on real datasets. Every student in this program works directly with him — not a TA, not a substitute — toward a concrete, submittable research output.
"My role is to accelerate your journey from question to discovery. You bring the curiosity; I bring the roadmap, the tools, and the accountability to ensure you succeed."