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Python Bootcamp: Zero to Hero with Django, Data & ML

Name: Python Bootcamp: Zero to Hero with Django, Data & ML
Rating: 5.0 (3 reviews)

Learn Python step by step with coding demos, exercises, Django projects, data science, and machine learning.

Created byNdimangwa Ngoya

Last updated 10/2026

English

What you'll learn

Write clean, well-structured Python code from scratch using functions, modules, object-oriented programming, and best practices.
Analyze and visualize data, and build machine learning models using Python libraries such as pandas, NumPy, Matplotlib, and scikit-learn.
Build web applications with Django, working with URLs, views, templates, static files, models, and databases.
Apply Python skills through hands-on exercises and projects, including testing, APIs, and practical application development.

Course content

15 sections • 159 lectures • 47h 20m total length

Welcome & Course Overview8:23
Installing Python on Windows, Mac, and Linux10:09
IDE Setup: VS Code & PyCharm17:02
Jupyter Notebook Introduction23:23
Your First Python Program7:29
Verify Your Python Environment0:18

Variables and Data Types6:26
DEMO : Variables and Data Types6:11
Numbers: Integers and Floats5:48
DEMO : Numbers, Integers and Floats10:03
Strings and Strings Methods6:36
DEMO : Strings and Strings Methods9:38
Type Conversion and Type Checking5:37
DEMO : Type Conversion and Type Checking6:23
Basic Input/Output Operations5:18
DEMO : Basic Input/Output Operations7:48
PRACTICE SHEET : Python Fundamentals0:16
Practice Instructions
Complete the Practice Sheet (section_02_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_02_solutions.pdf). Try each exercise yourself, run your code, and correct any errors you find.
After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.
Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Python Fundamentals

Condition Statements if/elif/else19:00
DEMO : Condition Statements if/elif/else17:03
Logical Operators and/or/not19:58
DEMO : Logical Operators and/or/not34:27
Loops : while loop and for loop20:11
DEMO : Loops, while loop and for loop31:34
Loop Control break/continue16:38
DEMO : Loop Control break/continue24:54
Nested Loops and Loops Patterns11:51
DEMO : Nested Loops and Loops Patterns33:49
List Comprehensions21:06
DEMO : List Comprehensions21:26
PRACTICE SHEET : Control Flow and List Comprehensions0:16
Practice Instructions
Complete the Practice Sheet (section_03_student_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_03_solutions_sheet.pdf). Try each exercise yourself, run your code, and correct any errors you find.
After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.
Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Control Flow and List Comprehensions

Introduction to Functions17:00
DEMO : Introduction to Functions21:47
Function Arguments13:05
DEMO : Function Arguments31:30
Variable Scope12:24
DEMO : Variable Scope13:36
Lambda Functions9:45
DEMO : Lambda Functions18:14
Practical Function Design7:59
DEMO : Practical Function Design12:47
Import Modules10:32
DEMO : Import Modules20:39
Create Your Own Modules6:42
DEMO : Create Your Own Modules22:14
PRACTICE SHEET : Functions and Modular Programming0:16
Practice Instructions
Complete the Practice Sheet (section_04_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_04_solutions.pdf). Try each exercise yourself, run your code, and correct any errors you find.
After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.
Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Functions and Modular Programming

Python Lists7:56
DEMO : Python Lists22:24
List Methods7:18
DEMO : List Methods13:52
Tuples in Python10:21
DEMO : Tuples in Python22:45
Python Sets14:06
DEMO : Python Sets24:54
Dictionaries in Python12:01
DEMO : Dictionaries in Python14:08
Args and Kwargs12:53
DEMO : Args and Kwargs20:21
PRACTICE SHEET : Data Structures in Python0:16
Practice Instructions
Complete the Practice Sheet (section_05_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_05_solutions.pdf). Try each exercise yourself, run your code, and correct any errors you find.
After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.
Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Data Structures in Python

Reading and Writing Files15:01
DEMO : Reading and Writing Files14:48
Working with CSV and JSON Files12:57
DEMO : Working with CSV and JSON Files20:26
Exception Handling12:43
DEMO : Exception Handling21:47
Working with File Paths and the os module9:58
DEMO : Working with File Paths and the os module11:14
Practical File Processing Project10:36
DEMO : Practical File Processing Project20:39
PRACTICE SHEET : File Handling and Error Management0:16
Practice Instructions

Complete the Practice Sheet (section_06_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_06_solutions_sheet.pdf). Try each exercise yourself, run your code, and correct any errors you find.

After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.

Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
File Handling and Error Management

Introduction to Object Oriented Programming10:51
Classes and Objects in Python13:23
DEMO : Classes and Objects in Python20:36
Class Variables and Instance Variables10:03
DEMO : Class Variables and Instance Variables19:20
Class Methods and Static Methods11:59
DEMO : Class Methods and Static Methods16:52
PRACTICE SHEET : Object Oriented Programming, Part 10:16
Practice Instructions

Complete the Practice Sheet (section_07_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_07_solutions_sheet.pdf). Try each exercise yourself, run your code, and correct any errors you find.

After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.

Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Object Oriented Programming, Part 1

Inheritance in Python11:47
DEMO : Inheritance in Python12:39
Method Overriding in Python10:12
DEMO : Method Overriding in Python10:04
Using super function in Python Inheritance11:28
DEMO : Using super function in Python Inheritance7:50
Multiple Inheritance10:54
DEMO : Multiple Inheritance10:14
Polymorphism in Python8:32
DEMO : Polymorphism in Python5:01
Encapsulation and Private Variables9:20
DEMO : Encapsulation and Private Variables15:19
Magic and Dunder Methods11:06
DEMO : Magic and Dunder Methods24:02
PRACTICE SHEET : Object Oriented Programming, Part 20:16
Practice Instructions

Complete the Practice Sheet (section_08_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_08_solutions_sheet.pdf). Try each exercise yourself, run your code, and correct any errors you find.

After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.

Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Object Oriented Programming, Part 2

Why Testing Matters10:47
Installing and Setting Up pytest28:06
Writing Your First Test9:14
DEMO : Writing Your First Test19:48
Test Fixtures11:45
DEMO : Test Fixtures15:03
Parametrized Tests11:55
DEMO : Parametrized Tests26:35
Mocking and Patching11:43
DEMO : Mocking and Patching39:04
PRACTICE SHEET : Python Testing with pytest0:16
Practice Instructions

Complete the Practice Sheet (section_09_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_09_solutions_sheet.pdf). Try each exercise yourself, run your code, and correct any errors you find.

After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.

Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Python Testing with pytest

Introduction to Data Science9:02
Numpy Arrays and Operations34:30
Numpy Indexing and Slicing35:45
Pandas Series and Dataframes41:42
Reading and Writing Data with Pandas29:05
Data Cleaning and Preparation54:35
Data Filtering and Selection40:47
GroupBy and Aggregation36:19
PRACTICE SHEET : Data Science with NumPy and Pandas0:16
Practice Instructions

Complete the Practice Sheet (section_10_practice_sheet.pdf) on your own before opening the Solutions Sheet (section_10_solutions_sheet.pdf). Try each exercise yourself, run your code, and correct any errors you find.

After completing the exercises, open the Solutions Sheet to compare your approach with the provided solutions.

Remember: The goal is not just to get the correct answer, but to practice writing and understanding Python code yourself.
Data Science with NumPy and Pandas

Requirements

No prior programming experience is required. You only need a computer (Windows, macOS, or Linux), an internet connection for downloading tools and course materials, and a willingness to learn and practice Python step by step.

Description

Learn Python from Beginner to Advanced — With Hands-On Projects

Want to learn Python the right way — from absolute beginner level to building real projects with confidence?

Python Bootcamp — Zero to Hero with Django, Data & Machine Learning gives you a complete, structured learning path. Instead of jumping between disconnected tutorials, you will progress step by step from Python fundamentals to practical applications in software development, data science, machine learning, and web development.

What You Will Learn

1. Python Programming Fundamentals

Start from scratch and build a solid foundation in Python, including:

Variables, data types, strings, and operators
Conditional statements and loops
Functions, modules, and packages
Lists, tuples, sets, and dictionaries
File handling, CSV, and JSON
Object-oriented programming (OOP)
Exception handling and Python best practices

2. Professional Python Development Skills

Learn how to write, organize, and test Python programs through practical demonstrations covering:

Virtual environments and project organization
Testing with pytest
Mocking and patching
Working with APIs
Writing clean, maintainable Python code

3. Data Science and Data Visualization

Discover how Python is used to explore, process, and visualize data using popular libraries:

NumPy for numerical computing
pandas for data analysis
Matplotlib and Seaborn for data visualization
Data cleaning and preparation
Exploratory data analysis

4. Machine Learning with Python

Understand the foundations of machine learning and gain hands-on experience with scikit-learn, including:

Preparing data for machine learning
Feature engineering
Training and testing models
Regression and classification
Evaluating model performance

5. Web Development with Django

Learn how to develop dynamic, database-driven web applications with Django, including:

Django project and application structure
URLs, views, and templates
Static files and forms
Models and database integration
User authentication, registration, and login

Learn by Doing

This course combines clear explanations with hands-on coding demonstrations, exercises, and practical projects.

You will not simply watch lectures. You will write code, test your understanding, solve problems, and apply what you learn to realistic scenarios.

Who Is This Course For?

This bootcamp is designed for:

Complete beginners who want to learn Python from scratch
Students seeking a structured introduction to programming
Aspiring Python and Django developers
Learners interested in data science and machine learning
Developers who want to strengthen their Python fundamentals and practical skills

No prior Python programming experience is required.

What Will You Achieve?

By the end of this bootcamp, you will have practiced the skills needed to:

Write clean, well-structured Python programs
Work with files, APIs, and automated tests
Analyze and visualize datasets
Build and evaluate introductory machine learning models

Develop database-driven Django web applications
Continue learning more advanced Python specializations with a stronger technical foundation

Understand it. Practice it. Build with it.

Start your Python learning journey today and develop practical skills through structured, hands-on learning.

Who this course is for:

Complete beginners with no previous programming experience.
Students and career changers looking for a structured path to learning Python.
Aspiring Python developers who want hands-on coding exercises and practical projects.
Learners interested in Python automation, data analysis, machine learning, and Django web development.
Self-learners who want a comprehensive Python bootcamp that starts with the fundamentals and progresses step by step.

Python Bootcamp: Zero to Hero with Django, Data & ML

What you'll learn

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Course content

Course Introduction & Setup6 lectures • 1hr 7min

Python Fundamentals11 lectures • 1hr 10min

Control Flow and List Comprehensions13 lectures • 4hr 32min

Functions and Modular Programming15 lectures • 3hr 39min

Data Structures in Python13 lectures • 3hr 3min

File Handling and Error Management11 lectures • 2hr 30min

Object Oriented Programming : Part 18 lectures • 1hr 43min

Object Oriented Programming : Part 215 lectures • 2hr 39min

Python Testing with pytest11 lectures • 3hr 4min

Data Science with NumPy and Pandas9 lectures • 4hr 42min

Requirements

Description

Who this course is for: