Complete Syllabus
Week 1: Python Fundamentals

Week 1: Python Fundamentals

Overview

This week covers the essential Python foundations needed for machine learning in DevOps and SRE contexts. Each topic is presented with real-world infrastructure and operations examples to make the concepts immediately applicable to your daily work.

Learning Objectives

By the end of this week, you will be able to:

  • Write Python scripts for infrastructure automation and monitoring
  • Process and analyze large-scale metrics data efficiently with NumPy
  • Perform log analysis and create reports using Pandas
  • Create professional monitoring dashboards and visualizations with Matplotlib

Topics Covered

Python Basics
Core Python concepts with DevOps applications
NumPy Arrays
Efficient numerical operations for infrastructure metrics
Pandas DataFrames
Log analysis and structured data management
Matplotlib Visualization
Creating monitoring dashboards and reports

Prerequisites

  • Basic command line familiarity
  • Understanding of basic DevOps concepts
  • Python 3.8+ installed
  • Access to a development environment

Setup Instructions 

# Create a virtual environment
python3 -m venv ml-devops-env
source ml-devops-env/bin/activate  # On Windows: ml-devops-env\Scripts\activate

# Install required packages
pip install numpy pandas matplotlib requests psutil pyyaml

# Verify installation
python -c "import numpy, pandas, matplotlib; print('All packages installed successfully!')"

Learning Path

Day 1-2: Python Basics

  • Review Python fundamentals
  • Complete automation exercises
  • Build your first monitoring script

Day 3: NumPy

  • Learn array operations
  • Practice with metrics data
  • Implement anomaly detection

Day 4: Pandas

  • Master DataFrame operations
  • Analyze sample log files
  • Create incident reports

Day 5: Matplotlib

  • Learn visualization basics
  • Build monitoring dashboards
  • Create professional reports

Day 6-7: Integration Project

  • Combine all skills
  • Build a complete monitoring solution
  • Document and test your code

Hands-On Projects

Project 1: Automated Health Check System

Build a complete health check system that:

  • Monitors multiple services (Python basics)
  • Collects and processes metrics (NumPy)
  • Analyzes historical data for trends (Pandas)
  • Generates visual reports (Matplotlib)

Project 2: Log Analysis Pipeline

Create an end-to-end log analysis pipeline that:

  • Parses application logs
  • Detects anomalies and patterns
  • Generates daily/weekly reports
  • Visualizes error trends

Project 3: Capacity Planning Tool

Develop a capacity planning tool that:

  • Collects resource utilization data
  • Predicts future resource needs
  • Identifies optimization opportunities
  • Creates executive dashboards

Assessment Checklist

✅ Python Basics

  • Can write functions with error handling
  • Understand file I/O operations
  • Can work with JSON/YAML configurations
  • Able to create reusable modules

✅ NumPy

  • Can create and manipulate arrays
  • Understand array broadcasting
  • Can perform statistical operations
  • Able to optimize performance with vectorization

✅ Pandas

  • Can load and parse various data formats
  • Understand DataFrame operations
  • Can perform time series analysis
  • Able to aggregate and group data

✅ Matplotlib

  • Can create basic plots
  • Understand subplot layouts
  • Can customize visualizations
  • Able to create dashboard-style reports

Additional Resources

Books

Online Courses

Documentation

Next Steps

After completing Week 1, you’ll be ready to move on to:

  • Week 2: Linear Algebra and Statistics for ML
  • Week 3: Introduction to Machine Learning
  • Week 4: Deep Learning Fundamentals

Remember: The goal is not just to learn Python, but to apply it effectively in DevOps/SRE contexts. Focus on building practical, production-ready solutions!