Learn Python, Cheminformatics, and Machine Learning designed specifically for life scientists in India. No coding background required.
import rdkit
from rdkit import Chem
from sklearn.ensemble import RandomForestRegressor
# Define a molecule using SMILES representation
smiles = "CC(=O)OC1=CC=CC=C1C(=O)O" # Aspirin
mol = Chem.MolFromSmiles(smiles)
# Predict drug absorption (ADMET) using AI
predicted_solubility = model.predict(mol)
print(f"Solubility: {predicted_solubility}")
>>> Solubility predicted in 0.04 seconds!
Most AI courses are written by computer scientists for other computer scientists. They are filled with complex math equations and general software concepts that have nothing to do with drug molecules, assay results, or clinical trials. Meanwhile, life scientists have the biology domain expertise but feel locked out by the coding syntax.
With modern AI coding assistants, you can streamline writing code for data analysis. Instead of starting from scratch, you can use these tools to scaffold pipelines, allowing you to focus on the biological and chemical concepts. Moleculytics teaches you how to guide and validate these models successfully.
The absolute starting point. Learn the foundations of scientific Python, data structures, and how to clean molecular datasets.
How to represent chemistry as code. Learn to use RDKit, represent chemical structures in Python, and calculate molecular descriptors.
Build QSAR and predictive models. Train machine learning algorithms to predict ADMET properties and molecule toxicity automatically.
We wrote a short, practical 5-page guide to help you orient your learning path. Discover which skills matter most in the industry, myths to avoid, and how AI tools act as your shortcut.
Tell us about your background, career goals, and which topics interest you most. We use this information to design custom, interactive live workshops that bridge the gap.
Fill Out the 2-Minute Interest Form