Analyzing Data with Python & Docker

Overview

Explore powerful data analysis workflows by combining Python and Docker. Learn to create robust, repeatable systems for small and large-scale data processing using containerization techniques.

Syllabus

• Introduction to Data Analysis with Python & Docker
Overview of data analysis workflows
Introduction to Python for data analysis
Introduction to Docker and containerization
• Setting Up Your Environment
Installing Python and essential libraries (pandas, NumPy, etc.)
Installing Docker and understanding Docker Desktop
Setting up a development environment
• Python for Data Analysis
Data manipulation with pandas
Data visualization techniques (matplotlib, seaborn)
Applying statistical analysis using Python
Case studies and hands-on exercises
• Introduction to Docker
Understanding Docker architecture
Key Docker concepts: images, containers, Dockerfile
Building your first Docker container
• Docker for Data Analysis
Using Docker to create isolated data processing environments
Building Docker images for Python-based data analysis
Containerizing a Python data analysis application
• Advanced Containerization Techniques
Working with Docker Compose for multi-container applications
Managing data with Docker volumes
Networking and communication between containers
• Integrating Python and Docker
Developing and deploying data processing workflows in Docker
Automating data tasks with Docker
Scaling data analysis with swarm mode and orchestration tools
• Best Practices and Optimization
Optimizing Docker images for performance
Security considerations in containerized environments
Testing and debugging Python applications in Docker
• Project: Building a Dockerized Data Analysis Pipeline
Defining project goals and requirements
Designing the pipeline architecture
Implementing and testing the system
Presenting and discussing project outcomes
• Conclusion and Further Learning
Recap of key learnings and skills
Resources for further study in Python and Docker
Discussion on emerging trends in data analysis and containerization

Subjects

Conference Talks