AI Camp: Python Programming Essentials for Data-driven Applications - AI-Driven LMS + Atey Tutor

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AI Camp: Python Programming Essentials for Data-driven Applications

Categories Automation, Programming, Python

Learn Python fundamentals: Understand data types, control structures, error handling, and reusable functions.
Work with real-world data: Use Python to read, write, and manipulate data from files like CSV and JSON.
Build core app functionality: Design and implement features for your project, such as data tracking and automation.
Integrate external APIs: Retrieve real-time data and connect it seamlessly to your application.
Automate workflows: Use Python to automate repetitive tasks and improve app functionality.
Deploy your application: Package your app with Docker and prepare it for sharing or deployment.
Solve real-world problems: Apply everything you learn to create a functional, data-driven application by the end of the course.

Course Curriculum

Introduction to the Project, Python Fundamentals, and Git Version Control
Begin by exploring the project goals and architecture. Learn Python fundamentals (data types, loops, conditionals) and set up the application structure. Introduce Git version control for managing the codebase, setting up a Git repository, and learning basic commands like git init, git commit, and git push.

Reading and Writing Data
Learn to work with CSV and JSON for storage and retrieval. Introduce the Git workflow for managing changes to data-related code.

Building Core Application Logic
Add key features such as calculating expenses or tracking tasks. Introduce branching in Git for implementing new features without affecting the main codebase.

Error Handling and Validation
Add error handling and input validation to ensure the app handles unexpected inputs. Learn about collaborative Git workflows (e.g., pulling updates, resolving merge conflicts).

Data Processing and Transformation
Learn how to clean and process data using Pandas for use in the application. Track changes in data processing scripts with Git, including updating requirements files.

Automation Features
Add automation to the app, such as sending reminders or updating data. Learn how to use Git tags for marking specific release versions of the app.

Modularizing and Refactoring Code
Modularize the code into reusable functions or classes for better structure and maintainability. Use Git history to track refactoring changes and improve code efficiency.

Debugging and Testing
Learn debugging techniques to identify and fix issues. Implement unit tests and track test cases in Git.

API Integration
Learn to integrate external APIs (e.g., currency exchange rates, weather updates) and manage the integration through Git for version control.

Adding a Command-Line Interface (CLI)
Build a CLI for the app, allowing users to interact with features like viewing expenses, adding tasks, or generating summaries. Introduce collaborative Git workflows for team projects, including feature branches and pull requests.

Deployment with Docker
Learn to containerize your app using Docker for easy deployment and portability. Use Git tags and branches to manage deployment-ready versions.

Capstone: Finalize and Present Your Data-Driven Application
Finalize your Python application, integrating all features and ensuring it is production-ready. Use Git best practices throughout the process, committing and tagging final releases.

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Level

All Levels
Duration

72 hours
Last Updated

December 6, 2024
Certificate

Certificate of completion

A course by

DataU Instructor

Instructor

Aspiring data-driven app developers who want to learn Python by building real-world applications.
Beginners with no prior coding experience, eager to start their journey in Python programming.
Students and professionals looking to create automated workflows and data-driven solutions.
Anyone from any background who wants to master Python and develop applications that solve practical problems.

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