This course is designed specifically for data scientists and life scientists who want to master Python for reproducible research. Starting from the setup of a robust Docker-based working environment, the curriculum covers essential programming concepts including variables, control structures, and functions. Special emphasis is placed on practical applications for data analysis, such as file handling, regular expressions (Regex), and bioinformatics workflows using Biopython to parse FASTA and FASTQ files. Whether you are a beginner or looking to refine your coding practices, this course provides the tools to work efficiently and reproducibly.
Struttura del Corso (5 Giorni)
Day 1 – Environmental Setup & Bash (Modules 1 & 2)
Day 2 – Python Basics: Variables, Lists (Modules 3.1, 3.3)
Day 3 – Control Flow: For, If/Else, While (Modules 3.4, 3.6, 3.7)
Day 4 – Error Handling & Data Structures: Try/Except, Dictionaries (Modules 3.9, 3.14)
Day 5 – Advanced Topics: Loops, Files, Regex, Biopython & Numpy (Modules 3.10, 3.12, 3.13, 3.16)
At the end of the course, students will be able to:
Set up and manage a reproducible working environment using Docker to ensure consistent analysis across different operating systems.
Navigate and manipulate the file system efficiently using the command line interface (Bash).
Develop structured Python scripts utilizing core programming concepts such as variables, data structures (lists, dictionaries), control flow (loops, conditionals), and error handling.
Process and parse biological data formats (FASTA, FASTQ, metadata files) using text manipulation techniques and Regular Expressions.
Apply specialized libraries like Biopython and NumPy to handle biological sequences and perform introductory numerical data analysis.
Completing the requested exercises.
None
Dott. Luca Alessandrì
luca.alessandrì@unito.it
edvancedeh@unito.it