Introductory programming course: Python
Aimed at professionals who want to work in data analytics and are interested in adding Python programming to their job skills.
Asynchronous online learning
5 weeks (64h.)
No son necesarios conocimientos previos
Why study this course?
- Most widespread languagePython is, according to the TIOBE (The Importance of Being Earnest) index, the most widely used programming language today, making it a key skill in the job market.
- Versatility and clarityIt is one of the most versatile, cross-platform and easy-to-use programming languages. IEEE Spectrum defines it as a multi-paradigm, dynamic, multi-purpose language, designed to be fast to learn, use and understand, with a clean and uniform syntax.
- Interpreted languagePython is an interpreted language, which means that it does not require compilation, unlike other languages such as Java or C/C++, which facilitates real-time development and execution.
- Learning curvePython is easy to read and write due to its high similarity to the human language. Moreover, being cross-platform and open source, it is free and accessible, allowing unrestricted software development.
Program aims
- Understand the Python framework and its configuration.
- Identify and use the main variables and data types in Python.
- To introduce the concepts of object-oriented programming.
- Apply functions, loops and control structures to solve problems in Python.
- Become familiar with the main Python libraries, such as Pandas, datetime and NumPy, for data analysis.
- Learn how to create effective visualisations with tools such as Plotnine, Matplotlib and Plotly.
Methodology
- Actividades prácticas desde el minuto 1.
- Cada unidad incluye un cuestionario tipo test.
- Al final del curso resolverás un caso práctico guiado.
Study plan
1. Python basics
This unit is designed to facilitate the learning and understanding of fundamental programming concepts using the Python language. Python is a versatile and easy-to-learn language that has become a popular choice for both beginners and experienced developers due to its clear and readable syntax.
- Variables
- Types of objects
- Control structures
- Functions
2. Intermediate Python
This unit covers a variety of key concepts and techniques in data analysis using the Pandas library in Python. From manipulating DataFrames to performing advanced operations such as merging and aggregating datasets, the content covers a broad spectrum of essential skills for any data professional.
- Basic Pandas
- Pandas intermediate
- Advanced Pandas
3. Advanced Python
This unit explores two fundamental tools for data processing in Python: the datetime library and NumPy. The datetime library provides functionality for handling dates and times accurately, allowing arithmetic operations and comparisons between them. NumPy, on the other hand, stands as a pillar of scientific computing, providing support for multidimensional arrays and high-performance mathematical functions.
- Datetime in Python
- The NumPy library
4. Visualisation in Python
This unit covers various aspects related to the creation and customisation of graphics using tools such as Plotnine, Matplotlib and Plotly. It starts with the installation of key libraries and the loading of data for further manipulation. Different types of charts are explored, from line and bar charts to box, histograms and scatter plots. In addition, methods for adding titles, customising axes and modifying the appearance of graphs are highlighted.
- Plotnine
- Matplotlib
- Plotly
* Los docentes realizarán la selección del alumnado.
English (UK)