Microsoft Python Development Professional Certificate Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Python Programming Fundamentals
Estimated time: 20 hours
- Python syntax and data structures
- Control flow and functions
- Object-oriented programming in Python
- Error handling and debugging
Module 2: Python for Web Development
Estimated time: 30 hours
- Building web apps with Django and Flask
- Front-end integration using HTML, CSS, and JavaScript
- API development with FastAPI
- Handling requests and responses in web applications
Module 3: Python for Data Solutions
Estimated time: 30 hours
- Data analysis with Pandas and NumPy
- Data visualization using Matplotlib and Seaborn
- Machine learning basics with scikit-learn
- Working with structured and unstructured data
Module 4: Azure Cloud Integration
Estimated time: 30 hours
- Deploying Python applications to Microsoft Azure
- Serverless computing with Azure Functions
- Integrating AI/ML services via Azure Cognitive Services
- Connecting Python apps to cloud databases
Module 5: DevOps for Python
Estimated time: 25 hours
- Setting up CI/CD pipelines for Python applications
- Testing and quality assurance best practices
- Containerization with Docker and Azure integration
- Monitoring and optimizing deployed Python apps
Module 6: Final Project
Estimated time: 40 hours
- Design and develop a full-stack Python application
- Deploy the application on Microsoft Azure
- Implement DevOps practices including CI/CD and containerization
Prerequisites
- Familiarity with basic programming concepts
- Basic understanding of command-line tools
- Access to a computer with internet and an Azure subscription (free tier available)
What You'll Be Able to Do After
- Develop robust Python applications using industry best practices
- Build and deploy web applications using Django, Flask, and FastAPI
- Analyze and visualize data using Python’s data science stack
- Deploy and manage Python applications on Microsoft Azure
- Implement DevOps workflows for automated testing, deployment, and monitoring