Learn to Code in Python 3 Programming beginner to advanced
- Description
- Curriculum
- Notice
- Reviews
Requirements
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It is not required to have any previous experience in IT or programming
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You only need a computer
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Description
Master one of the world’s most versatile programming languages with this comprehensive “zero-to-hero” Python 3 course, designed to transform absolute beginners into advanced problem-solvers. Starting with the fundamentals of syntax and logic, you will rapidly advance through core concepts like data structures and error handling before diving into high-level applications such as file automation, web API integration, and JSON processing. Beyond traditional programming, the course introduces you to the essentials of Data Science and Machine Learning, teaching you to visualize data with Matplotlib and implement predictive models like KNN and Logistic Regression. By the end of this program, you will have developed the mindset of a professional developer, capable of building real-world software solutions and backed by a verified certificate to enhance your career profile.
Course Overview
This comprehensive course is designed for absolute beginners and covers everything from basic syntax to advanced topics like Machine Learning and Web APIs. It emphasizes practical learning through exercises, challenges, and real-life examples.
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Total Duration: 5.5 Hours (On-demand video)
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Lectures: 45 Lessons
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Level: Beginner to Advanced
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Prerequisites: None (Just a computer)
Course Outline
Module 1: Getting Started
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1-2. Installation: Setting up Python on both Mac and Windows.
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3-5. Fundamentals: Understanding Statements, Variables, and the
input()function. -
6. Hands-on Project: Building a Km to Miles Converter.
Module 2: Mastering Data Types
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7-10. Strings & Numbers: Working with text and numerical data through theory and exercises.
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11-14. Collections: Comprehensive guide to Lists, Tuples, and Dictionaries.
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15-16. Logic: Understanding Boolean values and their application.
Module 3: Control Flow & Logic
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17-19. Conditionals: Mastering
if,elif,elsestatements and logical operators (AND,OR). -
20-22. Loops: Automating tasks with
WhileandForloops including practical exercises.
Module 4: Advanced Programming Concepts
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23-25. Robust Coding: Learning Data Validation and Error Handling (
try-except). -
26. Modularity: Creating and using Functions to write clean code.
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27-29. Specialized Libraries: Working with Time and Data Visualization using Matplotlib/Pyplot.
Module 5: Working with External Data & APIs
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30-34. Web Integration: Sending HTTP Requests to servers, working with APIs, and handling JSON data structures.
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35-36. File Handling: Creating, reading, and writing files (TXT and Excel sheets).
Module 6: Introduction to Data Science & Machine Learning
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37-38. The Basics: Introduction to ML concepts and the Iris Dataset.
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39-41. KNN Model: Applying the K-Nearest Neighbors model and data splitting (Train/Test).
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42-44. Regression: Implementing Logistic Regression and future paths in ML.
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45. Capstone: Final Project Overview.
Key Learning Outcomes
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Core Proficiency: Master Python 3 syntax and fundamental programming logic.
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Data Interaction: Efficiently read/write files and handle structured JSON data.
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API Integration: Connect your programs to the web by sending and receiving data via APIs.
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Analytical Skills: Visualize data with Matplotlib and apply basic Machine Learning models like KNN and Logistic Regression.
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Professional Mindset: Learn to troubleshoot, validate data, and think like a software developer.
Certification
The course includes an online quiz to test your knowledge and awards a verified digital certificate upon completion to boost your professional profile.
Who this course is for:
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Any person who wants to learn to code from absolute beginner level
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Any person who wants to solve problems and create great services using Python programs
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1
Installing Python on Mac -
2
Installing Python on Windows
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3
Statements
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4
Variables
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5
The Input Function
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6
Exercise - Km to Miles Converter
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7
Data Types Strings
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8
Exercise - Strings
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9
Data Types Numbers
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10
Exercise - Numbers
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11
Data Types Lists and Tuples
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12
Exercise - Lists and Tuples
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13
Data Types Dictionaries
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14
Exercise - Dictionaries
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15
Data Types Booleans
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16
Exercise - Booleans
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17
Conditionals (if, elif, else)
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18
AND OR operators
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19
Exercise - Conditionals
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20
While Loops
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21
For Loops
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22
Exercise - Loops
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23
Data Validation
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24
Error Handling
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25
Exercise - Error Handling
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26
Functions
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27
Time
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28
Matplotlib
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29
Exercise - Time & MatplotlibPyplot
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30
Requests
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31
Sending HTTP Requests to APIs
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32
Working With JSON
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33
Exercise - Requests & Json (Part 1)
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34
Exercise - Requests & Json (Part 2)
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35
File Handling Basics - Create, Read, Write & Append
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36
Reading Excel Sheets
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37
Introduction to Machine Learning
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38
The Iris Dataset
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39
Applying the KNN Model
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40
Splitting Data Intro Train and Test Groups
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41
Exercise KNN - Picking the Best Value Of K
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42
The Logistic Regression Model
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43
Applying the Logistic Regression Model
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44
What's next in Machine Learning
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45
Project Overview
What you'll learn
- Learn Python 3, one of the most popular programming languages.
- Understand the fundamental concepts of programming.
- Learn to read and write files, such as Excel sheets and TXT files.
- Work with JSON data for handling structured data.
- Send HTTP requests to web servers and APIs.
- Explore data visualization and statistics in Python.
- Get an introduction to machine learning in Python.
- Start writing your own programs and think like a programmer.
- Enhance your professional life with valuable programming skills.
- Test your abilities with an online quiz.
- Earn a verified certificate to enhance your professional profile.
