Introduction to Python for IA

Dr. Luis García, CNyN-UNAM

Known for its simplicity and versatility, Python has become the language of choice for many developers and data scientists working in the field of AI. This course explores the basic AI concepts and algorithms for creating a QSAR model using Python. After completing the course students will be able to prepare data (analyze and clean), select the best features using different strategies and build classification models. As example problem we will build a QSAR model for predict activities in small compounds.

Content:

1. Environment setting
2. Python scientific libraries
3. Data analysis
4. Feature selection algorithms
5. Modeling algorithms

For taking the workshop, It is desired to have basic knowledge of Python

Non-Covalent Interactions

Dr. Rodrigo Ponce Pérez, CNyN-UNAM

The non-covalent interactions (NCI) are weak interactions present in several processes that help stabilize the systems and favor chemical reactions such as hydrogen bonds, Van der Waals forces, or steric effects, among others. In this short course, we focus on studying the NCI from the point of view of the Density Functional Theory (DFT) framework. We will start with the basic concept of DFT, the origin of the NCI within the DFT, and the use of computational codes devoted to visualizing the non-covalent interactions.

The short course aims to teach the assistants the use of the critic2 software to visualize the NCI. We focus on how to graph and understand the s(ρ) vs sig(λ₂)ρ plots and their corresponding NCI isosurfaces. This is with the purpose of visualize, understanding, and interpret properly the results. In the course, we address several systems where NCI appears from two molecules interacting to more complex systems. 

What do we need?

-A PC with Linux software

for taking the workshop, it desired to have basic knowledge of:

-Basic Linux commands.

-Preinstall the VESTA visualization software.

-Preinstall some plotting software, such as Gnuplot.

Optical properties of materials

Dr. Jose Mario Galicia Hernandez, CNyN-UNAM

In this workshop, we will learn about the so-called “beyond-DFT” theoretical techniques used to correctly describe the excited states of systems. It is well known that standard DFT lacks accuracy when computing the electronic and optical properties of systems out of the ground state. For this reason, several approximations based on Green’s function have been developed to overcome the standard DFT limitations.

The workshop will focus on teaching the basic concepts of the GW approach to computing the electronic band gap. On the other hand, we will learn about the RPA theory for computing some optical properties, such as the real and imaginary parts of the dielectric function, as well as some other useful quantities for linear optical analysis, such as the real and imaginary parts of the refractive index, the absorption coefficient, the energy loss function, and the reflectivity. Finally, we will learn about the BSE approach, which allows us to compute the dielectric function by considering the excitonic effects.

Workshop content

1. Basic concepts of DFT.
2. Computation of electronic band structures within standard DFT approach.
3. Basic concepts of systems out of ground state.
4. Basics concepts of GW approximation.
5. Exercises for computing the band gap within the GW approximations.
6. Basic concepts of optical properties.
7. Computation of linear optical properties within the RPA theory.
8. Exercises for computing the dielectric function by using the BSE approximation.

For taking the workshop, it desired to have basic knowledge on:

1. Density Functional Theory.
2. Basic Linux commands.
3. Preinstall the VESTA visualization software.
4. Preinstall some plotting software, such as Origin Lab, Magic Plot, and Gnuplot.
5. Preinstall a Worksheet software such as Excel or Open Office.