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Python All-in-One

Learn everything you need in one course and start coding in the Python programming language.

(COMP-PYTHON.AE1) / ISBN : 978-1-64459-537-4
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Über diesen Kurs

This Python Programming course is your ultimate training plan for mastering everything from basic to advanced machine learning and AI. 

You’ll start with Python’s syntax and build your first app. Then, zoom through real-world applications like robotics, data sciences, and even neural networks. 

So, whether you’re dissecting data, tinkering with a Raspberry Pi, or creating intelligent robots, we’ve got you covered with hands-on labs. 

Fähigkeiten, die Sie erwerben werden

  • Simplified Python programming basics, including syntax, variables, and operators. 
  • Build Python applications from scratch using real-world coding practices. 
  • Manipulate data with Python’s powerful tools for working with numbers, text, and dates. 
  • Develop logic-driven solutions using conditional statements and loops. 
  • Optimize code with lists, tuples, and dictionaries for data handling. 
  • Implement object-oriented programming concepts with classes and objects. 
  • Interact with external files, including text, binary, and CSV files. 
  • Work with JSON data to serialize and deserialize complex data structures. 
  • Explore Python libraries, packages, and modules for enhanced functionality. 
  • Analyze and visualize data with NumPy, Pandas, and Matplotlib. 
  • Design neural networks and machine learning models with TensorFlow. 
  • Experiment with AI techniques for robotics and automation. 
  • Control physical devices like LEDs, motors, and sensors using Python. 
  • Integrate Python with Raspberry Pi for physical computing projects. 
  • Automate web interactions and connect Python with online APIs. 
  • Develop strong understanding of big data and cloud computing. 
Kursübersicht herunterladen

1

Introduction

  • About This Course
  • What to Buy
  • Icons Used in This Course
  • Where to Go from Here
2

Starting with Python

  • Why Python Is Hot
  • Choosing the Right Python
  • Tools for Success
  • Writing Python in VS Code
  • Using Jupyter Notebook for Coding
3

Interactive Mode, Getting Help, and Writing Apps

  • Using Python's Interactive Mode
  • Creating a Python Development Workspace
  • Creating a Folder for Your Python Code
  • Typing, Editing, and Debugging Python Code
  • Writing Code in a Jupyter Notebook
4

Python Elements and Syntax

  • The Zen of Python
  • Introducing Object-Oriented Programming
  • Discovering Why Indentations Count, Big Time
  • Using Python Modules
5

Building Your First Python Application

  • Opening the Python App File
  • Typing and Using Python Comments
  • Understanding Python Data Types
  • Working with Python Operators
  • Creating and Using Variables
  • Understanding What Syntax Is and Why It Matters
  • Putting Code Together
6

Working with Numbers, Text, and Dates

  • Calculating Numbers with Functions
  • Still More Math Functions
  • Formatting Numbers
  • Grappling with Weirder Numbers
  • Manipulating Strings
  • Uncovering Dates and Times
  • Accounting for Time Zones
  • Working with Time Zones
7

Controlling the Action

  • Main Operators for Controlling the Action
  • Making Decisions with if
  • Repeating a Process with for
  • Looping with while
8

Speeding Along with Lists and Tuples

  • Defining and Using Lists
  • What's a Tuple and Who Cares?
  • Working with Sets
9

Cruising Massive Data with Dictionaries

  • Understanding Data Dictionaries
  • Creating a Data Dictionary
  • Looping through a Dictionary
  • Data Dictionary Methods
  • Copying a Dictionary
  • Deleting Dictionary Items
  • Having Fun with Multi-Key Dictionaries
10

Wrangling Bigger Chunks of Code

  • Creating a Function
  • Commenting a Function
  • Passing Information to a Function
  • Returning Values from Functions
  • Unmasking Anonymous Functions
11

Doing Python with Class

  • Mastering Classes and Objects
  • Creating a Class
  • Creating an Instance from a Class
  • Giving an Object Its Attributes
  • Giving a Class Methods
  • Understanding Class Inheritance
12

Sidestepping Errors

  • Understanding Exceptions
  • Handling Errors Gracefully
  • Being Specific about Exceptions
  • Keeping Your App from Crashing
  • Adding an else to the Mix
  • Using try … except … else … finally
  • Raising Your Own Exceptions
13

Working with External Files

  • Understanding Text and Binary Files
  • Opening and Closing Files
  • Reading a File’s Contents
  • Looping through a File
  • Reading and Copying a Binary File
  • Conquering CSV Files
  • Converting from CSV to Objects and Dictionaries
14

Juggling JSON Data

  • Organizing JSON Data
  • Understanding Serialization
  • Loading Data from JSON Files
  • Dumping Python Data to JSON
15

Interacting with the Internet

  • Seeing How the Web Works
16

Libraries, Packages, and Modules

  • Understanding the Python Standard Library
  • Exploring Python Packages
  • Importing Python Modules
  • Making Your Own Modules
17

Exploring Artificial Intelligence

  • AI Is a Collection of Techniques
  • Current Limitations of AI
18

Building a Neural Network

  • Understanding Neural Networks
  • Building a Simple Neural Network in Python
  • Building a Python Neural Network in TensorFlow
19

Doing Machine Learning

  • Learning by Looking for Solutions in All the Wrong Places
  • Creating a Machine-Learning Network for Detecting Clothes Types
  • Visualizing with MatPlotLib
  • Learning More Machine Learning
20

Exploring AI

  • Limitations of the Raspberry Pi and AI
  • Adding Hardware AI to the Raspberry Pi
  • AI in the Cloud
  • AI on a Graphics Card
  • Where to Go for More AI Fun in Python
21

Understanding the Five Areas of Data Science

  • Working with Big, Big Data
  • Cooking with Gas: The Five-Step Process of Data Science
22

Exploring Big Data

  • Introducing NumPy, Pandas, and MatPlotLib
  • Doing Your First Data Science Project
23

Using Big Data from Google Cloud

  • What Is Big Data?
  • Understanding Google Cloud and BigQuery
  • Reading the Medicare Big Data
  • Looking for the Most Polluted City in the World on an Hourly Basis
24

Introducing Physical Computing

  • Physical Computing Is Fun
  • What Is a Raspberry Pi?
  • Building Projects That Move and Sense the Environment
  • Sensing the Environment with the Raspberry Pi
  • Controlling an LED with Python
  • But Wait, There's More
25

No Soldering! Using Grove Connectors for Building

  • Working with the Grove System
  • Grove Connectors
  • Connecting with Grove Cables
26

Sensing the World

  • Understanding I2C
  • Measuring Oxygen and a Flame
  • Building a Dashboard on Your Phone with Blynk
  • Where to Go from Here
27

Making Things Move

  • Exploring Electric Motors
  • Controlling a DC Motor
  • Running a Servo Motor
  • Making a Stepper Motor Step
28

Introducing Robotics

  • A Robot Is Not Always Like a Human
  • Not Every Robot Has Arms or Wheels
  • Understanding the Main Parts of a Robot
  • Programming Robots
29

Building Your First Python Robot

  • Introducing the Mars Rover PiCar-B
  • Assembling the Robot
  • Testing Your Robot
30

Programming Your Robot Rover

  • Building a Simple, High-Level Python Interface
  • Making a Single Move with Python
  • Functions of the RobotInterface Class
  • The Python Robot Interface Test
  • Coordinating Motor Movements with Sensors
  • Making a Python Brain for Our Robot
  • Overview of the Included Adeept Software
  • Where to Go from Here
31

Using Artificial Intelligence in Robotics

  • This Lesson’s Projects: Going to the Dogs
  • Setting Up the First Project
  • Machine Learning Using TensorFlow
  • Testing the Trained Network
  • Taking Cats and Dogs to Our Robot
  • Setting Up the Second Project
  • The FindAndChaseTheBall.py Python Program
  • The Main Program
  • AI and the Future of Robotics

1

Interactive Mode, Getting Help, and Writing Apps

  • Getting Started with Visual Studio Code
  • Getting Started with Jupyter Notebook
2

Python Elements and Syntax

  • Generating a Random Integer
3

Building Your First Python Application

  • Using Boolean Operators
  • Working with Escape Characters
  • Using Arithmetic Operators
  • Using Variable Assignment
4

Working with Numbers, Text, and Dates

  • Using the round() Function
  • Printing the Absolute Value
  • Calculating the Square Root
  • Converting the Decimal Number to Binary, Octal, and Hexadecimal
  • Manipulating Strings Using the strip() Method
5

Controlling the Action

  • Using Conditional Statements
  • Using the for Loop
  • Using Nested Loops
  • Using the while Loop
6

Speeding Along with Lists and Tuples

  • Working with Lists
  • Working with Tuples
7

Cruising Massive Data with Dictionaries

  • Working with Dictionaries
8

Wrangling Bigger Chunks of Code

  • Working with Functions
  • Using a lambda Expression
9

Doing Python with Class

  • Working with Classes
10

Sidestepping Errors

  • Creating the Custom Exception Class
11

Working with External Files

  • Opening and Reading a File
  • Opening a CSV File
12

Juggling JSON Data

  • Loading Data from JSON Files
  • Dumping Python Data to JSON
13

Interacting with the Internet

  • Opening a URL
14

Libraries, Packages, and Modules

  • Using the math Module
15

Building a Neural Network

  • Creating an Activation Function
  • Exploring a Two-Layer Neural Network using NumPy
  • Training and Evaluating a Model in TensorFlow
  • Exploring a Two-Layer Neural Network using TensorFlow
16

Doing Machine Learning

  • Creating Convolutional Neural Network
  • Training and Evaluating a Network in Machine Learning
17

Exploring Big Data

  • Visualizing the Diamonds Dataset using MatPlotLib Library
  • Working with the Diamonds Dataset
  • Using the Pandas Library
  • Creating a Correlation Heat Chart
18

Introducing Physical Computing

  • Controlling an LED
19

No Soldering! Using Grove Connectors for Building

  • Simulating Traffic Light System Optimization
20

Making Things Move

  • Controlling a Stepper Motor
  • Controlling a DC Motor
21

Building Your First Python Robot

  • Controlling a Servo Motor
22

Using Artificial Intelligence in Robotics

  • Training a CNN Model Using the Image Dataset

Warum lieben Lernende diesen Kurs?

Haben Sie Fragen? Schauen Sie sich die FAQs an

Got doubts? Read further about our Python programming course for beginners here.

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No. This Python programming training course is perfect for total newcomers and experienced programmers looking to upskill. We start with the basics and build up to the cool, advanced stuff.

Just a computer and some curiosity. We’ll guide you through setting up everything you need, like Python, Visual Studio Code, and Jupyter Notebook.

Most courses at “Hello, World!” or basic apps. This is the best Python programming course for beginners which dishes out real-world applications – AI, robotics, data sciences, physical computing – you’ll walk away with advanced Python skills.

Absolutely! We’ll take you through the basics of AI, teach you how to build neural networks and get you started with machine learning using Python and TensorFlow.

Yes, absolutely! The course includes Python libraries like NumPy, Pandas, and Matplotlib to help you work with big data, analyze information, and create stunning visualizations. You'll also get hands-on experience using these libraries in real-world projects.

Totally! Python is one of the most in-demand skills in tech right now. Also, you’ll gain hands-on experience in areas like AI, data science, and robotics – big resume boosters!

Python Skills That Actually Impress!

  Take this Python programming language course to brush up your skills and build apps, analyze data, and even control gadgets.

$239.99

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