Curso_Python

https://www.youtube.com/watch?v=qtWEm5NEZBg&list=PL1mPu0A4F0dCE_5kJxYyHq_4k16o3GhnP

Applied Programming

Contents:

1. Language Basics (One or Two of: Python, JavaScript, Rust, ...)

   • Elements of the Program
     • Flow, Control Sentences, and Functions
     • Testing and Documentation
     • Data Types
     • Iterator Pattern
     • Applications
       • Distance Metrics: L1, L2, and Max
       • Variance and Covariance
   • Packages and Libraries for Science and Matrix Operations
     • Probability
     • Linear Regression
     • Principal Component Analysis (PCA)
   • Persistence Formats (Plain Text, CSV, JSON, ...)

2. Numerical Methods

   • Floating-Point Numbers
   • Definition of Algorithmic Complexity and Types of Problems
   • Significant Figures and Error Propagation in Iterated Equations
     • Gaussian Elimination using kiRi + kjRj -> Rj with ki and kj as integers
     • Ill-conditioned system of linear equations
     • Chaos
   • Roots of Polynomials
     • Analytical Formulas (Degree 2, 3, and 4)
     • Iterative Algorithms
   • Matrix Operations (Inverse and Pseudoinverse)
     • Comparison of Iterative and Non-Iterative Algorithms in Terms of Complexity and Error

3. Machine Learning

• Unsupervised method
  • k-mean clustering algorithm
• Supervised method
  • Nearest Neighbors
    • Classification and Confusion Matrix
    • Regression and Accuracy
  • Bayesian Methods (Classification and Regression)
  • Gradient Descent and Lasso (Classification and Regression)

6. Applying the 'Model View Controller' Pattern to Web Development
   • Database Operations (CRUD)
   • Frontend Development
   • Backend Development
   • Sockets and Websockets

Laboratories (ESP32, Raspberry Pico W, ...)

• Machine I/O

  • PIO (Programable Input/Output)
  • ADC (Analog-to-Digital Conversion)
  • DAC (Digital-to-Analog Conversion) using R-2R Network
  • PWM (Pulse Width Modulation)
  • IRQ (Interrupt Request)
  • FSM (Finite State Machine)
  • IoT (Internet of Things) using Sockets or MQTT

• Tools and Markup Languages** (1 week)

  • Examples of Markup Languages (HTML, LaTeX, Markdown)
  • GitHub
  • Git (clone, add, commit, status, checkout, push, pull)
  • Jupyter and Colab
  • IDEs (IDLE, Thonny, VSCode, ...)
  • SCRUM Methodology

Suggested Schedule for Computer Lab and Classroom

Week 1

Computer Lab:

• Introduction to GitHub
  • Signing Up on GitHub
  • Managing Issues and Using Project Boards
  • Understanding Markdown and Working with .md Files
• Git Fundamentals
  • Cloning Repositories, Adding Changes, Committing, Checking Status
  • Checking Out Branches, Pushing Changes, Pulling Updates
• Introduction to Colab and Jupyter Notebooks
• Exploring Integrated Development Environments (IDEs) like IDLE, Thonny, VSCode
• Activity: Working in Colab:
  • Create a GitHub account video
  • Create a private repository "Programacion_Aplicada" and add GerardoMunoz-UD as a collaborator
  • Log in at your personal Colab account
  • Copy in your Colab account the Language Basics Jupyter and add a cell at the top with your personal information and links to each section of the same Jupyter.
  • Save this Jupyter in the GitHub account

Classroom:

• Introduction to SCRUM Methodology
• Activity: Creating the Project Backlog for a New Product
• Homework: Uploading the Backlog to GitHub