HOT

Python for IoT Applications and Machine Learning

Development

Rating4.4
Enroll Now

Python for IoT Applications and Machine Learning, available at $19.99, has an average rating of 4.35, with 75 lectures, based on 489 reviews, and has 41558 subscribers.

You will learn about Python programming fundamentals for IoT applications and machine learning. Data types, operators, and control structures in Python. Object-oriented programming concepts and their application in IoT and ML. File handling techniques and reading/writing data from/to files. Connecting IoT devices and programming them using Python. Applying machine learning algorithms for data analysis and decision making in IoT systems. Understanding and implementing decorators for enhancing functions. Practical examples and projects demonstrating real-world IoT applications and machine learning integration. This course is ideal for individuals who are Beginners interested in learning Python programming for IoT applications and machine learning. or IoT enthusiasts looking to apply Python for controlling and managing connected devices. or Individuals aspiring to build machine learning models and integrate them into IoT systems. or Students or professionals seeking to enhance their skills in Python programming and its application in emerging technologies like IoT and machine learning. It is particularly useful for Beginners interested in learning Python programming for IoT applications and machine learning. or IoT enthusiasts looking to apply Python for controlling and managing connected devices. or Individuals aspiring to build machine learning models and integrate them into IoT systems. or Students or professionals seeking to enhance their skills in Python programming and its application in emerging technologies like IoT and machine learning.

Enroll now: Python for IoT Applications and Machine Learning

Summary

Title: Python for IoT Applications and Machine Learning

Price: $19.99

Average Rating: 4.35

Number of Lectures: 75

Number of Published Lectures: 75

Number of Curriculum Items: 75

Number of Published Curriculum Objects: 75

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

  • Python programming fundamentals for IoT applications and machine learning.
  • Data types, operators, and control structures in Python.
  • Object-oriented programming concepts and their application in IoT and ML.
  • File handling techniques and reading/writing data from/to files.
  • Connecting IoT devices and programming them using Python.
  • Applying machine learning algorithms for data analysis and decision making in IoT systems.
  • Understanding and implementing decorators for enhancing functions.
  • Practical examples and projects demonstrating real-world IoT applications and machine learning integration.

Who Should Attend

  • Beginners interested in learning Python programming for IoT applications and machine learning.
  • IoT enthusiasts looking to apply Python for controlling and managing connected devices.
  • Individuals aspiring to build machine learning models and integrate them into IoT systems.
  • Students or professionals seeking to enhance their skills in Python programming and its application in emerging technologies like IoT and machine learning.

Target Audiences

  • Beginners interested in learning Python programming for IoT applications and machine learning.
  • IoT enthusiasts looking to apply Python for controlling and managing connected devices.
  • Individuals aspiring to build machine learning models and integrate them into IoT systems.
  • Students or professionals seeking to enhance their skills in Python programming and its application in emerging technologies like IoT and machine learning.

Welcome to the Python for Internet of Things (IoT) course! This comprehensive program is designed to equip you with the necessary skills to leverage the power of Python in IoT projects. Whether you’re a beginner or an experienced programmer, this course will provide you with the knowledge and tools needed to develop innovative IoT solutions using Python.

Throughout this course, you will learn how to install and set up Python for IoT development, explore fundamental programming concepts such as variables, data types, operators, and functions, and delve into advanced topics like object-oriented programming (OOP) and file handling. Additionally, you’ll gain hands-on experience through practical examples and projects, enabling you to apply your newfound skills in real-world scenarios.

By the end of this course, you’ll be proficient in using Python to build IoT applications, manipulate data, interact with sensors and actuators, and solve complex problems in the IoT domain. Whether you’re interested in home automation, industrial IoT, or wearable technology, this course will empower you to bring your ideas to life and make meaningful contributions to the rapidly evolving field of IoT. Let’s embark on this exciting journey together and unlock the full potential of Python for IoT innovation!

Section 1: Introduction

This section provides an introduction to Python for Internet of Things (IoT) applications. It covers the basics of Python programming and its suitability for IoT projects. The lectures introduce the library support available in Python for IoT development.

Section 2: Installation and Startup

In this section, students learn how to install and start using Python for IoT projects. It includes practical examples demonstrating the setup process and provides a simple example of Python code execution. The section also explores built-in functions in Python.

Section 3: Variables and Datatype

Here, students delve into variables and data types in Python. The lectures cover the fundamentals of declaring variables and the various data types supported in Python. It extends into more advanced topics like type casting and data type conversion.

Section 4: Operator

This section focuses on operators in Python. It covers arithmetic, comparison, logical, bitwise, and assignment operators. Students learn through examples how to perform operations using these operators.

Section 5: Default Parameters in Functions

Students learn about default parameters in Python functions. The lectures explain how to define functions with default parameters and how to utilize them effectively in function calls.

Section 6: Examples on Arithmetic Operator and Functions

This section provides practical examples demonstrating the use of arithmetic operators and functions in Python. Students learn how to calculate the area of a triangle and perform arithmetic operations using Python functions.

Section 7: Returning Multiple Values from Functions

Here, students explore how to return multiple values from functions in Python. The lectures include examples illustrating various scenarios where functions can return multiple values.

Section 8: Formatted Output

In this section, students learn about formatting strings in Python. The lectures cover different formatting techniques and provide examples to demonstrate their usage.

Section 9: Format Method

Students delve into the format method in Python, which is used for string formatting. The lectures explain the syntax of the format method and its various functionalities with examples.

Section 10: Comparison Operators and Statements

This section covers comparison operators and conditional statements in Python. Students learn how to use comparison operators to compare values and how to construct conditional statements using if, elif, and else statements.

Section 11: Loop

Here, students explore looping statements in Python, including while and for loops. The lectures provide examples illustrating the usage of these loops for repetitive tasks and iterating over data structures.

Section 12: Strings in Python

Students learn about strings in Python, including string manipulation and various string methods. The lectures cover topics such as string concatenation, slicing, and searching within strings.

Section 13: Lists in Python

In this section, students learn about lists, one of the fundamental data structures in Python. The lectures cover list creation, manipulation, and common list operations.

Section 14: Examples on Lists

Students are presented with examples showcasing the usage of lists in Python. The lectures demonstrate how to perform various operations on lists and solve problems using list comprehension.

Section 15: Sets in Python

This section introduces sets, a collection of unique elements in Python. Students learn about set operations, set methods, and practical applications of sets in Python programming.

Section 16: OOP in Python

Students delve into Object-Oriented Programming (OOP) concepts in Python. The lectures cover classes, objects, inheritance, encapsulation, and polymorphism, providing a solid foundation in OOP principles.

Section 17: Packages and Modules

Here, students learn about packages and modules in Python, which are used for organizing and reusing code. The lectures cover module creation, importing modules, and exploring standard Python packages.

Section 18: Packages and OOP Example

Students are presented with examples demonstrating the usage of packages and Object-Oriented Programming concepts together. The lectures provide practical insights into structuring and modularizing Python projects.

Section 19: Dictionaries and Packages

This section explores dictionaries, a key-value pair data structure in Python. Students learn about dictionary operations, dictionary methods, and how dictionaries can be used effectively in Python programming.

Section 20: Global and Local Variables

Students delve into the concepts of global and local variables in Python. The lectures explain the scope of variables, global keyword usage, and best practices for variable declaration and usage.

Section 21: Decorators

In this advanced section, students learn about decorators in Python. The lectures cover decorator syntax, defining decorators, and practical examples demonstrating the use of decorators in Python programming.

Section 22: Reading From a File

Here, students learn about file management in Python. The lectures cover file handling operations such as opening, reading from, and writing to files, providing essential skills for data manipulation and processing tasks.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Python for IOT

Lecture 2: Library Support in Python

Chapter 2: Installation and Startup

Lecture 1: How to Install and Startup IOT using Python

Lecture 2: Simple Example of Python

Lecture 3: Build in Function in Python

Chapter 3: Variables and Datatype

Lecture 1: Variables and Datatype in Python

Lecture 2: Variables and Datatype in Python Continues

Chapter 4: Operator

Lecture 1: Operator in Python

Lecture 2: Example of Arithmetic Operators

Lecture 3: Example of Arithmetic Operators Continues

Lecture 4: More on Operators

Chapter 5: Default Parameters in Functions

Lecture 1: Default Parameters in Functions

Lecture 2: Default Parameters in Functions Continues

Chapter 6: Examples on Arithmetic Operator and Functions

Lecture 1: Calculating Area of Triangle using Arithmetic Operators

Lecture 2: Calculate the Arithmetic Function

Lecture 3: Example of Operators

Lecture 4: Example of Operators Continues

Chapter 7: Returning Multiple Values from Functions

Lecture 1: Reverse of Number Example in Python

Lecture 2: More on Reverse of Number Example in Python

Lecture 3: More on Reverse of Number Example in Python Continues

Chapter 8: Formatted Output

Lecture 1: How to Create a Formatting String in Python

Lecture 2: Example of Formatting String

Chapter 9: Format Method

Lecture 1: Format Methods

Lecture 2: Format Methods Example

Chapter 10: Comparison Operators and Statements

Lecture 1: Comparison Operators in Python

Lecture 2: Conditional Statements in Python

Lecture 3: Logical Operators

Lecture 4: Bitwise and Assignment Operators

Lecture 5: Bitwise and Assignment Operators Example

Chapter 11: Loop

Lecture 1: Looping Statements – The While Loop

Lecture 2: Examples on While Loop

Lecture 3: Examples on While Loop Continues

Lecture 4: For Loop

Lecture 5: Example of For Loop

Lecture 6: More on Looping Example

Chapter 12: Strings in Python

Lecture 1: Strings in Python

Lecture 2: Working with Strings in Python

Chapter 13: Lists in Python

Lecture 1: Data Structures in Python

Lecture 2: Data Structures in Python Continues

Chapter 14: Examples on lists

Lecture 1: Python Lists

Lecture 2: Examples on Python Lists

Lecture 3: More on Python Lists

Chapter 15: Sets in Python

Lecture 1: Sets in Python

Lecture 2: Dictionaries in Python

Lecture 3: Tuples in Python

Chapter 16: OOP in Python

Lecture 1: OOP in Python

Lecture 2: Example of OOP

Chapter 17: Packages and Modules

Lecture 1: More on Packages and Modules

Lecture 2: More on Packages and Modules Continues

Lecture 3: Standard Packages in Python

Chapter 18: Packages and OOP Example

Lecture 1: OOP Example

Lecture 2: Packages Example

Lecture 3: Packages Example Continues

Chapter 19: Dictionaries and Packages

Lecture 1: More on Dictionaries and packages

Lecture 2: List Comprehensions

Lecture 3: Argument packing and Unpacking

Lecture 4: Argument packing and Unpacking Continues

Chapter 20: Global and Local Variables

Lecture 1: Global and Local Variables

Lecture 2: Examples on Global and Local Variables

Lecture 3: Concept of Inheritance

Chapter 21: Decorators

Lecture 1: Decorators in Python

Lecture 2: Defining a New Function

Lecture 3: Function as an Object

Lecture 4: Importing Math Module

Lecture 5: Returning Functions

Lecture 6: Function of Polynomial Creator

Lecture 7: Defining Function Decorator

Lecture 8: Use Cases for Decorators

Lecture 9: Overview on Blink App

Lecture 10: Connecting Nodemcu and Programming

Lecture 11: Decorators with Parameters

Lecture 12: Elements in Decorators

Chapter 22: Reading From a File

Lecture 1: File Management

Lecture 2: Opening A File

Lecture 3: Writing into a File

Instructors

Rating Distribution

  • 1 stars: 24 votes
  • 2 stars: 30 votes
  • 3 stars: 119 votes
  • 4 stars: 182 votes
  • 5 stars: 134 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

You may also like

Google Shopping Ads Digital Marketing Course

Complete Copywriting System : write to sell with ease

Product Positioning Masterclass: Unlock Market Traction