Data Science for Chemists

IPL Summer School

Academic Year 2024

Specialized summer school program bridging chemistry and data science. Comprehensive exploration of computational methods, data analysis, machine learning, and Big Data applications in chemical research.
Data Science Programming Analysis & Visualization Machine Learning Data Mining Big Data Introduction Chemistry C₆H₁₂O₆ H₂O CH₄ MOLECULAR COMPUTATIONAL

Course Materials

Overview

Introduction

Welcome to the summer school, course objectives, and overview of data science applications in modern chemistry research and computational chemistry.

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Foundation

Introduction to Data Science

Fundamental concepts of data science, scientific computing workflow, data-driven research methodologies, and the intersection of chemistry with computational analysis.

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Skills

Fundamentals of Programming

Python programming essentials, scientific libraries (NumPy, SciPy), data structures, and computational thinking for chemistry applications.

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Analysis

Data Analysis & Visualization

Statistical analysis, exploratory data analysis, matplotlib, seaborn, and creating publication-quality visualizations for chemical data.

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Discovery

Data Mining

Pattern recognition in chemical datasets, clustering molecular structures, association rules, and extracting insights from large chemical databases.

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Intelligence

Machine Learning

Supervised and unsupervised learning for chemistry, molecular property prediction, QSAR models, neural networks for chemical applications.

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Scale

Big Data in Chemistry

Handling large-scale chemical databases, distributed computing for molecular simulations, cloud platforms, and high-throughput screening data analysis.

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Practical Sessions

GitHub Repository

SummerSchool-DS4C - Practical Exercises

Hands-on laboratory sessions combining chemistry and data science. Python notebooks, chemical datasets, molecular analysis projects, and real-world computational chemistry case studies.

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