05/08/2026
๐๐๐ฑ๐ญ๐๐๐ง ๐๐ซ๐ฎ๐ ๐๐ข๐ฌ๐๐จ๐ฏ๐๐ซ๐ฒ ๐ฐ๐ข๐ญ๐ก ๐๐
There is a big difference between โproducing literatureโ and solving real-world problems. If we want to solve real challenges in computational drug discovery, we must go beyond our comfort zone. In the age of AI, learning advanced methods such as machine learning and deep learning is no longer optionalโit is essential.
For example, building a model that achieves 99% accuracy on a small, clean dataset is easy. But when the same model is tested on real patient or molecular data, it often fails because real data are noisy, complex, and unpredictable.
At NextGen Drug Discovery with AI, we go beyond tutorials. We teach you how to think like a scientist, solve real problems, and use modern AI tools to build publication-ready and real-world drug discovery workflows.
Challenges
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Limited computing power: Many students in Bangladesh do not have access to high-performance PCs or laptops required for deep learning and computational drug discovery.
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Lack of hands-on learning: Many students attend live Zoom classes or watch recorded lectures, but they do not get enough practical experience by writing code, running analyses, and solving real problems.
Our Solution
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Google Colab Pro: We use Google Colab Pro so students can access powerful cloud GPUs without needing expensive hardware.
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End-to-end hands-on notebooks: We have developed end-to-end Google Colab notebooks for every module. Students can run every code cell, explore the outputs, and learn alongside the instructor and teaching assistants (TAs) during live sessions.
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Learn by doing: Every concept is taught through practical exercises and real-world case studies, helping students build confidence and develop problem-solving skills instead of just watching lectures.
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Explore a Sample Google Colab Notebook: https://tinyurl.com/drug-discovery-with-ai
This Program Is for You If:
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You are serious about building a career in computational drug discovery or AI-driven biomedical research.
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You plan to pursue an MS or PhD at an international university or research institute.
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You enjoy solving real-world scientific problems, not just following tutorials.
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You are willing to learn modern AI, machine learning, and deep learning techniques.
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You can dedicate 10+ hours per week to hands-on learning and projects.
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You are ready to challenge yourself and grow beyond your comfort zone.
This Program Is NOT for You If:
โ You are looking for a quick certificate with minimal effort.
โ You want guaranteed publications or instant results.
โ You prefer watching lectures instead of writing code and solving problems.
โ You are looking for shortcuts or ready-made solutions.
โ You cannot commit to a practical, project-based, 12-week learning journey.
Join Our Research Team
Outstanding participants who successfully complete the NextGen Drug Discovery with AI program and its core projects may be invited to join DeepBio as a Research Assistant. This is an excellent opportunity for students who want to build a strong research portfolio and prepare
Minimum Eligibility (Mandatory)
To be considered, you must meet both of the following requirements:
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85% or higher attendance in live mentoring sessions
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85% or higher completion of assignments and projects
These are mandatory requirements. Participants who do not meet both criteria will not be considered.
Program Details
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Duration: 3 Months
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Class Schedule: 3 live classes per week
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Total Class: 40
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Class Time: 9:00 PM โ 11:00 PM (Bangladesh Time)
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Computing Resources: Google Colab Pro
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Fee: 10,200 BDT/Month, Total: 30,600 (The program fee is payable monthly and must be paid by the 5th of each month.)
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Seats: 30-40
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Register by: 25 August, 2026
Step 1: Register for Free: Visit https://deepbioacademy.github.io/ and click "Apply Now" to complete the registration form. There is no registration fee.
Step 2: Join Our Live Q&A Session: After the registration deadline, we will email all registered participants the Zoom link for a Live Q&A Session. You can ask any questions about the course, curriculum, teaching style, or career opportunities.
We believe you should fully understand the program before investing your time and money. That's why you can also join the first two classes for free. If you find the course valuable and suitable for your goals, you can enroll. If not, there is absolutely no obligation to join.