Geo-ICT Training Center, The Netherlands

200 courses, 20 online supports,

60 moocs, 30 trainees

Course: Data-analysis and GIS

  • Desciption
  • Planning and Registration

This course in Data Analysis and GIS lasts 8 days and costs € 2995. The content focuses on practical exercises so that the professionals are well prepared for their (future) working environments.

Day 1: Introduction to data science training, R intro
The teacher gives an introduction to data analysis and how Python, R and SQL play a role in this. How are Matlab and SPSS applied and how does this compare to Python, for example? You will receive an overview of and a view of the entire training process.

Then an introduction is given to the basics of R programming. After the first day, you will be able to read data, perform operations, and answer simple statistical questions using data selection, descriptive statistics and plots.

Day 2: R Base
On the second R-day you will learn to make tables, interpret them and calculate margins. You will also gain insight into S3 / S4 methods. They are also taught to deal with missing values ​​and exceptional cases such as Inf. and NULL. Finally, you will learn to work with R Studio projects and you will learn how to write scripts and functions in R.

Day 3: R Advanced
During the third R day, the basic knowledge of R Programming is refined. At the end of this day, you can perform independence tests on categorical data and perform and interpret advanced (linear) regression methods.

In addition, you are able to perform automatic model selection methods with R. Furthermore, extensive attention is paid to a number of principles behind graphical analysis methods. You can independently produce, modify and interpret a number of commonly used plot types.

Finally, attention is paid to the geographical component. It tells how to read geographic data and plot it on maps.

Day 4: GIS Analyzes
You will get to know the QGIS package and use it to visualize the results of various data analyzes. You will learn how to overlay layers in vector format and raster format. You will also learn to set the scale at which the objects become visible in the map. Attention is also paid to text labels, exchange with other systems, and thematic presentations.

Thematic representations can also be made. You do various GIS analyzes with maps from different disciplines.

Day 5: Python intro

Day 5 starts with the introduction of Python. You will learn the essential aspects of programming in this object-oriented scripting language. You will also learn the syntax of this programming language and learn to work with the extensive library, which is standard in Python.

Day 6: Python Base
After an introduction to the installation of Python and the different ways of executing Python scripts, the basic concepts of Python, such as declarations, variables and control flow structures, are discussed. Attention is also paid to the collection structures in Python, such as lists, tuples and dictionaries.

Day 7: SQL
SQL is the question language for querying relational databases. Data scientists will certainly have to deal with it. During this day you will install the open source database PostGre SQL. After that, a practice database is loaded on which you will run all basic SQL queries. The SELECT, INNER and OUTER JOINS, UPDATE, DELETE, VIEWS, OPERATORS, VARIABLES, and CREATE statements are covered in detail. You will learn to define tables, draw up queries and perform data manipulations. You will fully master SQL.

Day 8: Python Advanced
During this day, the focus is on using functions in Python with the different methods of parameter passing, such as by value and by reference. The scope of variables and lambda functions are also discussed. Subsequently, attention is paid to the division of Python software into modules and the use of namespaces and packages is discussed.

Object-oriented programming with classes and objects is also discussed in detail. In this respect concepts like encapsulation, inheritance and polymorphism are discussed. In addition, the handling of errors in Python scripts using exception handling is discussed.

Also, the functionality of various Python library functions for accessing files is on the program and attention is paid to database access with the Python Database API.

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