Advanced Python: Data Structures & Machine Learning

          Module 1: Python Fundamentals and Environment Setup

Section 1: Introduction to Python  
- Lesson 1: What is Python?  
  Module 1, Section 1, Lesson 1 What is Python?  
- Lesson 2: History and Overview of Python  
  Module 1, Section 1, Lesson 2 History and Overview of Python  

Section 2: Setting Up Your Development Environment  
- Lesson 1: Installing Python and Code Editors  
  Module 1, Section 2, Lesson 1 Installing Python and Code Editors  
- Lesson 2: Using the Python Interactive Shell and IDEs  
  Module 1, Section 2, Lesson 2 Using the Python Interactive Shell and IDEs  

Section 3: Python Basics: Variables, Data Types, and Operators  
- Lesson 1: Understanding Variables and Data Types  
  Module 1, Section 3, Lesson 1 Understanding Variables and Data Types  
- Lesson 2: Basic Operators and Expressions  
  Module 1, Section 3, Lesson 2 Basic Operators and Expressions  

Section 4: Control Structures and Functions  
- Lesson 1: Using Conditionals and Loops  
  Module 1, Section 4, Lesson 1 Using Conditionals and Loops  
- Lesson 2: Defining and Calling Functions  
  Module 1, Section 4, Lesson 2 Defining and Calling Functions  

Section 5: Working with Basic Data Structures  
- Lesson 1: Introduction to Lists and Tuples  
  Module 1, Section 5, Lesson 1 Introduction to Lists and Tuples  
- Lesson 2: Overview of Dictionaries and Sets  
  Module 1, Section 5, Lesson 2 Overview of Dictionaries and Sets  


Module 2: Essential Data Structures in Python

Section 1: Overview of Python Data Structures  
- Lesson 1: Introduction to Core Data Structures  
  Module 2, Section 1, Lesson 1 Introduction to Core Data Structures  
- Lesson 2: Choosing the Appropriate Data Structure  
  Module 2, Section 1, Lesson 2 Choosing the Appropriate Data Structure  

Section 2: Deep Dive into Python Lists  
- Lesson 1: Working with Lists Effectively  
  Module 2, Section 2, Lesson 1 Working with Lists Effectively  
- Lesson 2: Utilizing List Comprehensions  
  Module 2, Section 2, Lesson 2 Utilizing List Comprehensions  

Section 3: Exploring Tuples, Sets, and Dictionaries  
- Lesson 1: Practical Uses for Tuples  
  Module 2, Section 3, Lesson 1 Practical Uses for Tuples  
- Lesson 2: Mastering Sets and Dictionaries  
  Module 2, Section 3, Lesson 2 Mastering Sets and Dictionaries  

Section 4: Implementing Stacks and Queues  
- Lesson 1: Building a Stack in Python  
  Module 2, Section 4, Lesson 1 Building a Stack in Python  
- Lesson 2: Building a Queue in Python  
  Module 2, Section 4, Lesson 2 Building a Queue in Python  

Section 5: Fundamentals of Time Complexity  
- Lesson 1: Introduction to Time Complexity  
  Module 2, Section 5, Lesson 1 Introduction to Time Complexity  
- Lesson 2: Basics of Big-O Notation  
  Module 2, Section 5, Lesson 2 Basics of Big-O Notation  


Module 3: Introduction to Machine Learning Fundamentals

Section 1: Understanding Machine Learning  
- Lesson 1: What is Machine Learning?  
  Module 3, Section 1, Lesson 1 What is Machine Learning?  
- Lesson 2: Overview of Machine Learning Types  
  Module 3, Section 1, Lesson 2 Overview of Machine Learning Types  

Section 2: Data Collection and Preprocessing  
- Lesson 1: The Importance of Data Collection  
  Module 3, Section 2, Lesson 1 The Importance of Data Collection  
- Lesson 2: Basics of Data Cleaning and Preprocessing  
  Module 3, Section 2, Lesson 2 Basics of Data Cleaning and Preprocessing  

Section 3: Regression Fundamentals  
- Lesson 1: Introduction to Regression Analysis  
  Module 3, Section 3, Lesson 1 Introduction to Regression Analysis  
- Lesson 2: Simple Linear Regression Concepts  
  Module 3, Section 3, Lesson 2 Simple Linear Regression Concepts  

Section 4: Classification Fundamentals  
- Lesson 1: Introduction to Classification Techniques  
  Module 3, Section 4, Lesson 1 Introduction to Classification Techniques  
- Lesson 2: Fundamentals of k-Nearest Neighbors (KNN)  
  Module 3, Section 4, Lesson 2 Fundamentals of k-Nearest Neighbors (KNN)  

Section 5: Evaluating Machine Learning Models  
- Lesson 1: Understanding Accuracy and Error Metrics  
  Module 3, Section 5, Lesson 1 Understanding Accuracy and Error Metrics  
- Lesson 2: Introduction to Cross-Validation Techniques  
  Module 3, Section 5, Lesson 2 Introduction to Cross-Validation Techniques  


Module 4: Python in Engineering Applications

Section 1: Engineering Problem Solving with Python  
- Lesson 1: Bridging Engineering Concepts with Python  
  Module 4, Section 1, Lesson 1 Bridging Engineering Concepts with Python  
- Lesson 2: Effective Problem-Solving Strategies  
  Module 4, Section 1, Lesson 2 Effective Problem-Solving Strategies  

Section 2: Exploring Python Libraries for Data Analysis  
- Lesson 1: Introduction to NumPy  
  Module 4, Section 2, Lesson 1 Introduction to NumPy  
- Lesson 2: Introduction to Pandas  
  Module 4, Section 2, Lesson 2 Introduction to Pandas  

Section 3: Data Visualization for Engineering  
- Lesson 1: Basics of Data Visualization with Matplotlib  
  Module 4, Section 3, Lesson 1 Basics of Data Visualization with Matplotlib  
- Lesson 2: Creating Graphs and Charts  
  Module 4, Section 3, Lesson 2 Creating Graphs and Charts  

Section 4: Simulation and Modeling  
- Lesson 1: Introduction to Simulation Techniques  
  Module 4, Section 4, Lesson 1 Introduction to Simulation Techniques  
- Lesson 2: Building Basic Engineering Models  
  Module 4, Section 4, Lesson 2 Building Basic Engineering Models  

Section 5: Integrating Python into Engineering Projects  
- Lesson 1: Managing Python Projects in Engineering  
  Module 4, Section 5, Lesson 1 Managing Python Projects in Engineering  
- Lesson 2: Best Practices for Code Organization  
  Module 4, Section 5, Lesson 2 Best Practices for Code Organization  


Module 5: Data-Driven Projects and Applications

Section 1: Planning a Data-Driven Project  
- Lesson 1: Defining Your Data-Driven Project  
  Module 5, Section 1, Lesson 1 Defining Your Data-Driven Project  
- Lesson 2: Developing a Project Plan and Data Strategy  
  Module 5, Section 1, Lesson 2 Developing a Project Plan and Data Strategy  

Section 2: Mini-Project: Data Structures in Action  
- Lesson 1: Project Overview and Requirements  
  Module 5, Section 2, Lesson 1 Project Overview and Requirements  
- Lesson 2: Applying Data Structures to Solve a Real-World Problem  
  Module 5, Section 2, Lesson 2 Applying Data Structures to Solve a Real-World Problem  

Section 3: Mini-Project: Introduction to Machine Learning Application  
- Lesson 1: Project Overview and Requirements  
  Module 5, Section 3, Lesson 1 Project Overview and Requirements  
- Lesson 2: Implementing a Simple Machine Learning Model  
  Module 5, Section 3, Lesson 2 Implementing a Simple Machine Learning Model  

Section 4: Testing and Debugging Projects  
- Lesson 1: Fundamental Testing Techniques  
  Module 5, Section 4, Lesson 1 Fundamental Testing Techniques  
- Lesson 2: Debugging and Troubleshooting Strategies  
  Module 5, Section 4, Lesson 2 Debugging and Troubleshooting Strategies  

Section 5: Final Project and Future Directions  
- Lesson 1: Project Presentation and Review  
  Module 5, Section 5, Lesson 1 Project Presentation and Review  
- Lesson 2: Exploring Future Learning and Career Paths in Engineering  
  Module 5, Section 5, Lesson 2 Exploring Future Learning and Career Paths in Engineering