Course Overview
This course teaches you to actually understand Python, not just copy code.
Most tutorials show you what to type. You follow along, it works, and then you're stuck the moment you try to do something on your own. That's because they never explain why things work the way they do. This course is different. I explain the reasoning behind every concept so you can think through problems yourself instead of constantly Googling for answers. If you want real understanding that sticks, not just syntax you'll forget next week, you're in the right place.
What makes this course different? You get over 30 hours of video instruction, but that's just the start. Every section includes fully annotated Jupyter notebooks that read like a textbook, complete with explanations, examples, and code you can run and modify. You also get all course slides as reference material. Between the videos, notebooks, and slides, you're getting a complete learning package, not just someone coding on screen.
What You'll Learn
Write clean, readable Python code following professional best practices
Master Python's core data structures: strings, lists, tuples, dictionaries, and sets
Create well-organized programs using functions, modules, and packages
Understand how Python actually works (variables, memory, scope) so debugging becomes intuitive
Handle files, errors, dates/times, and external APIs
Structure your code like a professional, not a beginner copying examples
What's Included
30+ hours of video instruction with clear explanations of both "how" and "why"
Fully annotated Jupyter notebooks for every topic, essentially a complete textbook you can run and experiment with
All course slides as downloadable reference material
Challenging exercises with solutions at the end of each section
Lifetime access to learn at your pace and revisit anytime
Direct Q&A support where I personally respond to questions
Topics Covered
Python Foundations, Numeric Types, Strings, Lists, Tuples, Dictionaries, Sets, Conditionals, Loops, Functions, File I/O, Exception Handling, Modules & Packages, Classes and OOP Basics, Working with APIs (requests library), Dates and Timezones.
Prerequisites
No prior Python experience required. You should be comfortable with basic computer tasks and have some familiarity with the command line. If you've never used a terminal, spend 20 minutes on a beginner tutorial first and you'll be ready.
Ready to learn Python the right way?
Enroll now and build the foundation that will serve your entire programming career.
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Course curriculum
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Introduction
160 Xem trước -
What is Python?
410 Xem trước -
Installing Python
355 Xem trước -
Installation - Mac
506 Xem trước -
Installation - Windows
440 Xem trước -
Using the Windows Python Launcher
239 -
Course Materials (Jupyter Notebooks)
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Course Materials (Slides)
-
Virtual Environments - What? Why? How? Overview
732 -
Virtual Environments
950 -
Creating Virtual Environments - Mac & Linux
702 -
Creating Virtual Environments - Windows
918 -
Installing Packages - Lecture
688 -
Installing Packages - Coding
960 -
Running Python - Lecture
779 -
Running Python - Coding
1506
-
Introduction - Python Basics
67 -
Basic Data Types - Lecture
629 -
Basic Data Types - Coding
457 -
Objects - Lecture
534 -
Objects - Coding
476 -
Variables - Lecture
1015 -
Variables - Coding
643 -
Arithmetic Operators - Lecture
524 -
Arithmetic Operators - Coding
529 -
Operator Precedence - Lecture
362 -
Operator Precedence - Coding
442 -
Integer Division and Modulus - Lecture
520 -
Integer Division and Modulus - Coding
543 -
Comparison Operators - Lecture
628 -
Comparison Operators - Coding
734 -
Boolean Operators - Lecture
504 -
Boolean Operators - Coding
372 -
Exercises
-
Introduction - Sequence Types
319 -
Lists - Lecture
344 -
Lists - Coding
309 -
Tuples - Lecture
381 -
Tuples - Coding
664 -
Strings - Lecture
188 -
Strings - Coding
894 -
Slicing - Lecture
852 -
Slicing - Coding
875 -
Manipulating Sequences - Lecture
437 -
Manipulating Sequences - Coding
1032 -
Copying Sequences - Lecture
491 -
Copying Sequences - Coding
540 -
Unpacking Sequences - Lecture
280 -
Unpacking Sequences - Coding
436 -
Exercises
-
Introduction - Functions
377 -
Custom Functions - Lecture
745 -
Custom Functions - Coding
1788 -
Star Arguments - Lecture
254 -
Star Arguments - Coding
741 -
Default Values - Lecture
202 -
Default Values - Coding
1882 -
Keyword-Only Arguments - Lecture
533 -
Keyword-Only Arguments - Coding
1730 -
Lambda Functions - Lecture
229 -
Lambda Functions - Coding
591 -
Exercises
-
Introduction - Dates and Times
926 -
The time Module - Lecture
1115 -
The time Module - Coding
1188 -
The datetime Module - Lecture
338 -
The datetime Module - Coding
919 -
Date Arithmetic - Lecture
220 -
Date Arithmetic - Coding
1309 -
Naive and Aware Times - Lecture
584 -
Naive and Aware Times - Coding
1221 -
Custom Representations - Lecture
92 -
Custom Representations - Coding
538 -
Exercises
-
Introduction - CSV Module
104 -
Reading CSV Files - Lecture
539 -
Reading CSV Files - Coding
254 -
Dialects - Lecture
166 -
Dialects - Coding
477 -
More Examples Reading CSV Files - Lecture
29 -
More Examples Reading CSV Files - Coding
849 -
Writing CSV Files - Lecture
169 -
Writing CSV Files - Coding
345 -
Exercises
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Introduction - Custom Classes
805 -
Defining Classes - Lecture
467 -
Defining Classes - Coding
589 -
Initializing Classes - Lecture
460 -
Initializing Classes - Coding
808 -
Instance Methods - Lecture
236 -
Instance Methods - Coding
1774 -
Special Methods - Lecture
442 -
Special Methods - Coding
1247 -
Properties - Lecture
603 -
Properties - Coding
1306 -
Exercises
-
Introduction - 3rd Party Libraries
306 -
The pytz Library - Lecture
316 -
The pytz Library - Coding
815 -
The dateutil Library - Lecture
341 -
The dateutil Library - Coding
1741 -
JSON Data - Lecture
732 -
JSON Data - Coding
953 -
REST APIs - Lecture
1852 -
REST APIs - Coding
735 -
The requests Library - Lecture
638 -
The requests Library - Coding
2544 -
Exercises
-
Introduction - NumPy
1280 -
Creating Arrays from Lists - Lecture
538 -
Creating Arrays from Lists - Coding
898 -
Creating Arrays from Scratch - Lecture
237 -
Creating Arrays from Scratch - Coding
958 -
Reshaping Arrays - Lecture
240 -
Reshaping Arrays - Coding
549 -
Stacking Arrays - Lecture
323 -
Stacking Arrays - Coding
1005 -
Indexing - Lecture
281 -
Indexing - Coding
312 -
Slicing - Lecture
745 -
Slicing - Coding
1272 -
Fancy Indexing - Lecture
867 -
Fancy Indexing - Coding
1254 -
Masking - Lecture
560 -
Masking - Coding
1260 -
Universal Functions - Lecture
401 -
Universal Functions - Coding
1607 -
Additional Math and Stats Functions - Lecture
752 -
Additional Math and Stats Functions - Coding
1011 -
Exercises
-
Introduction - Pandas
227 -
Indexes - Lecture
870 -
Indexes - Coding
952 -
Series - Lecture
1006 -
Series - Coding
1258 -
DataFrames - Lecture
462 -
DataFrames - Coding
1680 -
Selecting Data - Lecture
402 -
Selecting Data - Coding
1100 -
Missing Data - Lecture
807 -
Missing Data - Coding
1766 -
Loading Data - Lecture
333 -
Loading Data - Coding
871 -
Basic Data Analysis - Lecture
170 -
Basic Data Analysis - Coding
1338 -
Sorting and Filtering - Lecture
748 -
Sorting and Filtering - Coding
1848 -
Manipulating Data - Lecture
382 -
Manipulating Data - Coding
2082 -
Exercises
Requirment
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No prior Python experience required
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Basic computer skills (navigating folders, installing software)
-
Some command line familiarity (or 20 minutes with a beginner tutorial)
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Willingness to work through exercises and think through problems
Outcomes
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Write clean, professional Python code with confidence
-
Understand how Python actually works, not just the syntax
-
Master strings, lists, dictionaries, sets, and tuples
-
Build well-organized programs using functions and modules
-
Handle files, errors, and external data gracefully
-
Work with dates, timezones, and REST APIs
-
Think through problems instead of Googling every error
-
Debug effectively by understanding what Python is doing
-
Read and write JSON and CSV files
-
Create your own classes and objects
-
Structure projects the way professionals do
-
Use Python's standard library effectively
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