Diploma in Python for Water Resources and Geoscience - Asynchronous

Hatarilabs presents its educational program designed for mastering Python in real professional and academic environments. The program has an extensive practical work that goes from the basic concepts of Python, Numpy and Pandas to specific applications in water resources and geosciences coupled with geospatial analysis and machine learning. 

We are sure that Python is a tool / asset for hydrologists, hydrogeologist, geoscientist or related professionals and we know that only practice can give you the Python level you need to apply in everyday data analysis or numerical modeling. The amount of hours, the topics covered together with the examination and certification processes give you a strong reference of Python on your professional capabilities.

This diploma is developed in asynchronous mode that allows students to be more flexible in their schedule and enjoy of instructional materials during 06 months.

Note: This diploma is the recorded version of our last synchronous diploma.


Objectives

This diploma is designed to provide you with the following capabilities:

  • Master the basic concepts of Python and the Jupyter environment

  • Become proficient in the common tools of the scientific oriented Python packages as Numpy, Pandas and Scipy

  • Create full feature data visualizations for tabular, geospatial and 3D data.

  • Learn and apply the most common geospatial tools for vector and raster data analysis in Python

  • Have a perspective on the application of machine learning tools in Python for water resources and related fields.

  • Get experience on the application of Python in numerical modeling. 

  • Understand the Python packages development and have the capabilities to apply new packages.

 

Content

The diploma is divided into 6 modules, each module is divided into 6 sessions. See the complete diploma syllabus on this link.

The summarized content of every module is described below:

Module 1: Python for Hydrology - Part 1

This course develops the basic concepts of Python programming under Jupyter. Exercises will cover the basic Python data structures, conditional statements, loops coupled with an introduction to array manipulation in Numpy, tabular data management with Pandas and applied exercises with precipitation data …more info 

  • Session 1: Anaconda interface

  • Session 2: Python data types

  • Session 3: Python loops and data structures

  • Session 4: Numpy and matplotlib for water resources

  • Session 5: Precipitation data analysis with Pandas

  • Session 6: Precipitation and streamflow data analysis and visualization …more info 

Module 2: Python for Hydrology - Part 2

Once we have covered the basic concepts of Python programming and introductory examples with water resources data we will move to more specific precipitation statistics with Scipy, analysis of long term climate data with temporal queries, spatial interpolations, multiple station data exploration and a of machine learning example for filling missing precipitation data …more info 

  • Session 1: Rainfall statistics with Scipy I

  • Session 2: Rainfall statistics with Scipy II

  • Session 3: Filling missing precipitation data

  • Session 4: Long term temperature data analysis

  • Session 5: Interpolation of Precipitation Data with Python and Matplotlib

  • Session 6: Climate variable exploration from multiple climate stations …more info 

Module 3: Data visualization in Python

Following the learning process of Python programming for water resources we will develop a course focused on data visualization using different graphical libraries like Matplotlib, Seaborn, Bokeh, Pyvista, Folium and Altair. This module is aimed to learn the creation and control process of plots for an efficient and interactive data analysis …more info 

  • Session 01: Matplotlib

  • Session 02: Seaborn

  • Session 03: Bokeh

  • Session 04: Pyvista

  • Session 05: Folium

  • Session 06: Altair …more info 

Module 4: Applied geospatial data analysis with Python 

Modeling surface flow, groundwater flow or any physical process on the environment is by itself a distributed process where analytical tools need to be combined with geospatial tools on a programming level. We have compiled the basic information and applied examples of the most common geospatial tools available in Python while assuring functionality on any operating system …more info 

  • Session 01: Introduction to Fiona

  • Session 02: Spatial Analysis of Total Coliforms with Fiona

  • Session 03: Introduction to Shapely

  • Session 04: Raster data management with Rasterio and Python

  • Session 05: Introduction to Geopandas for flooded areas analysis

  • Session 06: Glacier delimitations with Python and Rasterio …more info 

Module 5: Machine learning in Python for water resources and geosciences

Algorithms of machine learning in Python are simple and efficient tools for predictive data analysis and can be applied to any field of water resources related analysis. We have developed some applied cases of machine learning prediction with the Scikit Learn and Scikit Image of a variety of topics that range from water chemistry, fill missing precipitation, crop identification, geological modeling, and land cover classification …more info 

  • Session 01: Water chemistry cluster analysis.

  • Session 02: Crop identification.

  • Session 03: Fill missing precipitation from multiple stations and climate variables.

  • Session 04: Geological modeling.

  • Session 05: Delimitation of water bodies with Canny filters.

  • Session 06: Soil classifications machine learning …more info 


Module 6: Applied numerical modeling with Python

Python is a general purpose language for data analysis and it has extended and specific tools to work and interact with other models, algorithms and softwares. The interaction among Python and other tools can be on the data preprocessing, model simulation, output visualization. We have researched practical examples in Python to simulate groundwater flow, land evolutions, geochemical speciation, hydraulic and hydrogeological modeling …more info 

  • Session 01: Groundwater Modeling with Modflow 06 and Flopy

  • Session 02: Land evolution modeling with Landlab.

  • Session 03: Water speciation calculation with Phreeqc.

  • Session 04: Hydraulic Modeling with HEC RAS and Python

  • Session 05: Hydrological Modeling with SWAT and Python.

  • Session 06: Hydrological Modeling with HEC HMS and Jython in HEC DSS Vue …more info 

Trainer

Saul Montoya M.Sc.

Hydrogeologist - Numerical Modeler

Mr. Montoya is a Civil Engineer graduated from the Catholic University in Lima with postgraduate studies in Management and Engineering of Water Resources (WAREM Program) from Stuttgart University – Germany with mention in Groundwater Engineering and Hydroinformatics. Mr Montoya has a strong analytical capacity for the interpretation, conceptualization and modeling of the surface and underground water cycle and their interaction. 

He is in charge of numerical modeling for contaminant transport and remediation systems of contaminated sites. Inside his hydrological and hydrogeological investigations Mr. Montoya has developed a holistic comprehension of the water cycle, understanding and quantifying the main hydrological dynamic process of precipitation, runoff, evaporation and recharge to the groundwater system. 

Over the last 9 years Saul has developed 2 websites for knowledge sharing in water resources: www.gidahatari.com (Spanish) and www.hatarilabs.com (English) that have become relevant due to its applied tutorials on groundwater modeling, spatial analysis and computational fluid mechanics.

Methodology / Examination

Mode: Offline - Asynchronous

Some details about the diploma methodology:

  • Manuals and files for the exercises will be delivered on our elearning platform.

  • The course will be developed by video recorded videos will be available on our elearning platform.

  • There is support for questions regarding the exercises developed through the forum/email.

  • Video of the classes will be available for 6 months.

The exams are certification is organized as follows:

  • The program has 3 exams that comprise the content of 2 courses.

  • Digital certificate available at the end of the program upon the exam approval.

  • To receive the digital certificate you must submit the exams.

Cost and payment method

The promotional cost of the program is $ 1000 dollars until 09th October 2024.

Diploma in Python for Water Resources/ Geoscience - Asynchronous

Registry

After payment with Paypal, fill out the following registration form including the information related to your payment. We will send you an e-mail to confirm your registration.

For any other information please write to: saulmontoya@hatarilabs.com

Comment

Saul Montoya

Saul Montoya es Ingeniero Civil graduado de la Pontificia Universidad Católica del Perú en Lima con estudios de postgrado en Manejo e Ingeniería de Recursos Hídricos (Programa WAREM) de la Universidad de Stuttgart con mención en Ingeniería de Aguas Subterráneas y Hidroinformática.

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