Learn Python Programming Masterclass (updated 1/2023)

This Python For Beginners Course Teaches You The Python Language Fast. Includes Python Online Training With Python 3

What you'll learn

Have a fundamental understanding of the Python programming language.

Have the skills and understanding of Python to confidently apply for Python programming jobs.

Acquire the pre-requisite Python skills to move into specific branches - Machine Learning, Data Science, etc..

Add the Python Object-Oriented Programming (OOP) skills to your résumé.

Understand how to create your own Python programs.

Learn Python from experienced professional software developers.

Understand both Python 2 and Python 3.

Requirements

You’ve either already got it or it’s FREE. Here’s the checklist:

A computer - Windows, Mac, and Linux are all supported. Setup and installation instructions are included for each platform.

Your enthusiasm to learn this go-to programming language. It’s a valuable lifetime skill which you can’t un-learn!

Everything else needed to start programming in Python is already included in the course.

Description

Whether you want to:- build the skills you need to get your first Python programming job- move to a more senior software developer position- get started with Machine Learning, Data Science, Django or other hot areas that Python specialises in- or just learn Python to be able to create your own Python apps quickly.…then you need a solid foundation in Python programming. And this course is designed to give you those core skills, fast.This course is aimed at complete beginners who have never programmed before, as well as existing programmers who want to increase their career options by learning Python.The fact is, Python is one of the most popular programming languages in the world – Huge companies like Google use it in mission critical applications like Google Search.And Python is the number one language choice for machine learning, data science and artificial intelligence. To get those high paying jobs you need an expert knowledge of Python, and that’s what you will get from this course.By the end of the course you’ll be able to apply in confidence for Python programming jobs. And yes, this applies even if you have never programmed before. With the right skills which you will learn in this course, you can become employable and valuable in the eyes of future employers.Here’s what a few students have told us about the course after going through it.“I had very limited programming experience before I started this course, so I have really learned a lot from the first few sections. It has taken me from essentially zero programming skill to a level where I'm comfortable using Python to analyze data for my lab reports, and I'm not even halfway done the course yet. There are other courses out there which focus on data analysis, but those courses are usually targeted at people who already know how to program which is why I chose this course instead. “ – Christian DiMaria “I have been puttering through your Python course . In that time, though, and without finishing it yet I've been able to automate quite a bit at my work. I work in a school system and unifying data from our various student information systems can be incredibly frustrating, time consuming, and at times challenging. Using your course, I've learned enough to write applications that turn massive text files into dictionaries that get "stitched" together like a database and output to properly formatted CSV files and then uploaded via SFTP to various systems for secure processing. Our teachers, students, and the tech department have greatly benefitted from this automation. I just wanted to drop you a note thanking you for helping me learn this skill.” – Keith Medlin “This course was great. Within 3 weeks I was able to write my own database related applications.” – Theo Coenen And there are many more students who love the course – check out all the reviews for yourself.Will this course give you core python skills?Yes it will.  There are a range of exciting opportunities for Python developers. All of them require a solid understanding of Python, and that’s what you will learn in this course.Will the course teach me data science, machine learning and artificial intelligence?No, it won’t do that – All of these topics are branches of Python programming.  And all of them require a solid understanding of the Python language.Nearly all courses on these topics assume that you understand Python, and without it you will quickly become lost and confused.This course will give you that core, solid understanding of the Python programming language.By the end of the course you will be ready to apply for Python programming positions as well as move on to specific areas of Python, as listed above. Why should you take this course?There are a lot of Python courses on Udemy – Your instructors, Tim and Jean-Paul are pretty unique in that between them they have around 70 years of professional programming experience.  That’s more than a lifetime of skills you get to learn Python from.You can enrol in the course safe in the knowledge that they are not just teachers, but professional programmers with real commercial programming experience, having worked with big companies like IBM, Mitsubishi, Fujitsu and Saab in the past.As such you will not only be learning Python, but you will be learning industry best practices for Python programming that real employers demand.  And if that’s not enough take a read of some of the many reviews from happy students – there are around 100,000 students who have left around 19,000 reviews.This is one of the most popular courses on Python programming on Udemy.Here’s just some of what you’ll learn(It’s okay if you don’t understand all this yet, you will in the course)·       All the essential Python keywords, operators, statements, and expressions needed to fully understand exactly what you’re coding and why - making programming easy to grasp and less frustrating·       You will learn the answers to questions like What is the Python For Loop, what is Python used for, how Python switch the traditional syntax of code, and more.·       Complete chapters on object-oriented programming and many other aspects of Python, including tKInter (for building GUI Interfaces) and using databases with Python.·       Although this is primarily a Python 3 course, a python developer will need to work with Python 2 projects from time to time – We’ll show the difference in both versions to make sure you understand how things work differently in each version.·        How to develop powerful Python applications using one of the most powerful Integrated Development Environments on the market, IntelliJ IDEA! - Meaning you can code functional programs easier.  IntelliJ has both a FREE and PAID version, and you can use either in this course.  PyCharm will also work just fine.(Don’t worry if you want to use another IDE. You’re free to use any IDE and still get the most out of this course). Does the course get updated?It’s no secret how technology is advancing at a rapid rate. New, more powerful hardware and software are being released every day, meaning it’s crucial to stay on top with the latest knowledge. A lot of other courses on Udemy get released once, and never get updated.  Learning from an outdated course and/or an outdated version of Python can be counter productive and even worse it could teach you the wrong way to do things.For example if you apply some parts of Python 2 to Python 3 code, you will get completely different results.We cover differences like this in the course and also continually update the course as well.What if you have questions?As if this course wasn’t complete enough, we offer full support, answering any questions you have 7 days a week (whereas many instructors answer just once per week, or not at all). This means you’ll never find yourself stuck on one lesson for days on end. With our hand-holding guidance, you’ll progress smoothly through this course without any major roadblocks. That’s just one reason why Tim was voted top 10 in the  Udemy instructor awards (out of a whopping 18,000 instructors), and quickly became a top-rated, bestselling instructor on the Udemy site.  Student Quote: “Tim and JP are excellent teachers and are constantly answering questions and surveying students on new topics they will like to learn. This isn't a Python course it’s THE Python course you need.” – Sean BurgerThere’s no risk either!This course comes with a full 30 day money-back guarantee. Meaning if you are not completely satisfied with the course or your progress, simply let Tim or J-P know and they will refund you 100%, every last penny no questions asked.You either end up with Python skills, go on to develop great programs and potentially make an awesome career for yourself, or you try the course and simply get all your money back if you don’t like it… You literally can’t lose. Ready to get started, developer?Enrol now using the “Add to Cart” button on the right, and get started on your way to creative, advanced Python brilliance. Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you. See you on the inside (hurry, your Python class is waiting!)

Overview

Section 1: Course Introduction

Lecture 1 Introduction To The Course

Lecture 2 Remaster in Progress

Lecture 3 Video Quality

Lecture 4 Subtitles

Lecture 5 How to Get Help

Lecture 6 Important Tip - Source Code

Section 2: Install and Setup

Lecture 7 Python for Windows

Lecture 8 Installing IntelliJ IDEA for Windows

Lecture 9 Python for Mac

Lecture 10 Install IntelliJ IDEA for Mac

Lecture 11 Python for Linux

Lecture 12 Install IntelliJ IDEA for Linux

Lecture 13 Configuring IntelliJ IDEA - WINDOWS, MAC and LINUX

Lecture 14 Further configuration of IntelliJ

Section 3: Stepping into the World of Python

Lecture 15 Introduction

Lecture 16 Our First Python Program

Lecture 17 Printing in Python

Lecture 18 Strings in Python

Lecture 19 The Escape Character

Lecture 20 More on Escape Characters in Strings

Lecture 21 Variables and Types

Lecture 22 Python is a Strongly Typed Language

Lecture 23 Numeric Data Types in Python

Lecture 24 Numeric Operators

Lecture 25 Expressions

Lecture 26 Operator Precedence

Lecture 27 The str String Data Type

Lecture 28 Negative Indexing in Strings

Lecture 29 Slicing

Lecture 30 Slicing with Negative Numbers

Lecture 31 Using a Step in a Slice

Lecture 32 Slicing Backwards

Lecture 33 Challenge Solution and Slicing Idioms

Lecture 34 String Operators

Lecture 35 String Replacement Fields

Lecture 36 String Formatting

Lecture 37 f-strings

Lecture 38 Python 2 String Interpolation

Lecture 39 Section Summary

Section 4: Program Flow Control in Python

Lecture 40 Introduction to Blocks and Statements

Lecture 41 if Statements

Lecture 42 elif

Lecture 43 Using a Debugger in IntelliJ or Pycharm

Lecture 44 More on if, elif and else

Lecture 45 if, elif, and else in the Debugger

Lecture 46 Adding a Second Guess

Lecture 47 Conditional Operators

Lecture 48 Challenge Solution

Lecture 49 Using and, or, in Conditions

Lecture 50 Simplify Chained Comparison

Lecture 51 Boolean Expression True and False

Lecture 52 Truthy Values

Lecture 53 in and not in

Lecture 54 if Challenge

Lecture 55 Solution to if Challenge

Lecture 56 for loops

Lecture 57 Stepping through a for loop

Lecture 58 for loops Extracting Values from User Input

Lecture 59 Iterating Over a Range

Lecture 60 More About Ranges

Lecture 61 Nested for loops

Lecture 62 continue

Lecture 63 break

Lecture 64 Initialising Variables and None

Lecture 65 while loops

Lecture 66 More on while loops

Lecture 67 Break in a while loop

Lecture 68 The Random Module and Import

Lecture 69 Challenge Solution

Lecture 70 Binary Search

Lecture 71 Hi Lo Game

Lecture 72 Pass Statement and Complete the Hi Lo Game

Lecture 73 Testing the Hi Lo Game

Lecture 74 Augmented Assignment

Lecture 75 PEP8: The Python Style Guide

Lecture 76 Refactoring Code

Lecture 77 else in a loop

Lecture 78 else in the Hi Lo Game

Lecture 79 Conditional Debugging

Lecture 80 Another else Example

Lecture 81 Section Summary and Challenge

Lecture 82 Section Challenge Solution

Lecture 83 Optional Extra Challenge Solution

Lecture 84 Changing the Condition

Section 5: Lists and Tuples

Lecture 85 Introduction to Sequence Types

Lecture 86 Lists

Lecture 87 Immutable Objects

Lecture 88 Mutable Objects

Lecture 89 Binding Multiple Names to a List

Lecture 90 Common Sequence Operations

Lecture 91 Operations on Mutable Sequences

Lecture 92 Appending to a List

Lecture 93 Mini Challenge Solution

Lecture 94 Iterating Over a List

Lecture 95 The enumerate Function

Lecture 96 Improving our Code

Lecture 97 Removing Items from a List

Lecture 98 Sorting Lists

Lecture 99 Built-in Functions

Lecture 100 Sorting Things

Lecture 101 Case-Insensitive Sorting

Lecture 102 Creating Lists

Lecture 103 Replacing a slice

Lecture 104 Deleting Items from a List

Lecture 105 Safely removing values from a list

Lecture 106 Removing the High Values

Lecture 107 Test, Test and Test. Then Test Again!

Lecture 108 Testing the Program

Lecture 109 Removing Items from a List Backwards

Lecture 110 The Reversed Function

Lecture 111 Algorithms Performance

Lecture 112 Summary so far

Lecture 113 Nested Lists & Code Style

Lecture 114 Processing Nested Lists

Lecture 115 Solution to nospam Challenge

Lecture 116 Function Signatures

Lecture 117 print revisited

Lecture 118 The join Method

Lecture 119 The split Method

Lecture 120 Solution to Mini Challenge

Lecture 121 Tuples

Lecture 122 Tuples are Immutable

Lecture 123 Unpacking a Tuple

Lecture 124 Practical uses for Unpacking Tuples

Lecture 125 More Unpacking

Lecture 126 Nested Tuples and Lists

Lecture 127 Solution to Unpacking Challenge

Lecture 128 Nesting Further

Lecture 129 Nested Data Structures

Lecture 130 Nested Indexing

Lecture 131 Simple Jukebox - Demonstration

Lecture 132 Simple Jukebox - Importing Data

Lecture 133 Simple Jukebox - The Code

Lecture 134 Constants in Python

Lecture 135 Finishing the Code

Lecture 136 Challenge

Lecture 137 Challenge Solution

Lecture 138 Summary

Section 6: Functions - An Introduction

Lecture 139 Introduction

Lecture 140 Defining a function

Lecture 141 Program flow when calling a function

Lecture 142 Parameters and arguments

Lecture 143 Debugging with parameters

Lecture 144 Palindromes

Lecture 145 Palindrome challenge solution

Lecture 146 Sentence challenge solution

Lecture 147 Functions calling functions

Lecture 148 Returning values

Lecture 149 get_integer Challenge solution

Lecture 150 Returning None

Lecture 151 Functions that perform actions

Lecture 152 Handling invalid arguments

Lecture 153 width challenge solution

Lecture 154 Default parameter values

Lecture 155 Keyword arguments

Lecture 156 Docstrings

Lecture 157 Writing a Docstring

Lecture 158 How professional is that!

Lecture 159 Solution to Docstrings challenge

Lecture 160 Fibonacci Numbers

Lecture 161 Writing a fibonacci function

Lecture 162 Function annotations and type hints

Lecture 163 Function annotations with default values

Lecture 164 Solution to banner_text Docstring challenge

Lecture 165 A history lesson

Lecture 166 Printing in colour

Lecture 167 Running your program like a user

Lecture 168 Windows Only - Installing pre-release version of colorama

Lecture 169 colorama module and virtual environments

Lecture 170 Activating a virtual environment

Lecture 171 A function to test our HiLo game

Lecture 172 Counting correct guesses

Lecture 173 Playing Fizz Buzz

Lecture 174 Playing Fizz Buzz Solution

Lecture 175 *args

Lecture 176 colour_print with multiple arguments

Lecture 177 Rules for variable number of arguments

Lecture 178 Defining different parameter types

Lecture 179 Section Summary

Section 7: Dictionaries and Sets

Lecture 180 Introduction

Lecture 181 What is a dictionary?

Lecture 182 Iterating over a dictionary

Lecture 183 Adding items to a dictionary

Lecture 184 Changing values in a dictionary

Lecture 185 Removing items from a dictionary

Lecture 186 Using `in` with a dictionary

Lecture 187 Dictionary menu challenge solution

Lecture 188 Using a list with a dictionary

Lecture 189 Adding items to a dictionary

Lecture 190 Smart fridge

Lecture 191 What's for tea?

Lecture 192 Using several dictionaries together

Lecture 193 Checking the pantry

Lecture 194 Checking quantities - choosing a data structure

Lecture 195 Checking quantities - the code

Lecture 196 Solution: Create a shopping list challenge

Lecture 197 Wrong decisions don't have to be fatal

Lecture 198 The setdefault method

Lecture 199 APIs and a mobile phone demo

Lecture 200 The `dict` documentation

Lecture 201 The remaining `dict` methods

Lecture 202 The dict `update` method

Lecture 203 The dict `values` method

Lecture 204 References to mutable objects

Lecture 205 Shallow copy

Lecture 206 Shallow copy step-by-step

Lecture 207 Deep copy

Lecture 208 Simple deep copy solution

Lecture 209 Hash functions

Lecture 210 A really bad hashing function

Lecture 211 Hash tables

Lecture 212 Completing our simple dictionary implementation

Lecture 213 Hash functions and security

Lecture 214 hashlib, the secure hash module

Lecture 215 Introduction to Android-Tim

Lecture 216 Introduction to sets

Lecture 217 Python sets

Lecture 218 Implications of sets being unordered

Lecture 219 set membership

Lecture 220 Testing set membership is fast

Lecture 221 Adding items to a set

Lecture 222 Using a set to remove duplicate values

Lecture 223 Deleting items from a set

Lecture 224 The `discard` method

Lecture 225 The `remove` method

Lecture 226 The `pop` method

Lecture 227 set union

Lecture 228 Set union in practice

Lecture 229 Union update

Lecture 230 Advantage of the set operation methods over the operators

Lecture 231 Set intersection

Lecture 232 Set intersection in practice

Lecture 233 Set difference

Lecture 234 Set difference in practice

Lecture 235 Set symmetric difference

Lecture 236 subsets and supersets

Lecture 237 subsets and supersets in Python

Lecture 238 Practical application of subsets and supersets

Lecture 239 Summary

Section 8: Reading and writing files in Python

Lecture 240 Introduction

Lecture 241 Files and directories

Lecture 242 Introduction to the command prompt or terminal

Lecture 243 Paths

Lecture 244 Text files

Lecture 245 Reading from a text file

Lecture 246 Opening a file using `with`

Lecture 247 read, readline and readlines

Lecture 248 strip, lstrip and rstrip

Lecture 249 removeprefix and removesuffix in Python 3.9

Lecture 250 Parsing data in a text file

Lecture 251 Working with text data

Lecture 252 Solution to capital city challenge

Lecture 253 Dictionary values with multiple keys

Lecture 254 Printing data to a text file

Lecture 255 Writing data to a text file

Lecture 256 File modes

Lecture 257 Unicode – a brief history

Lecture 258 Unicode in Python

Lecture 259 File encodings

Lecture 260 Serializing data using JSON

Lecture 261 Limitations of JSON

Lecture 262 Practical application - parsing JSON data

Lecture 263 Practical application - parsing JSON data from the internet

Lecture 264 The CSV format

Lecture 265 Reading a CSV file

Lecture 266 quoting in a CSV file

Lecture 267 Sniffer and Dialect

Lecture 268 CSV Dialect

Lecture 269 Writing a CSV file

Lecture 270 The csv DictReader

Lecture 271 Solution to DictReader challenge

Lecture 272 Field names with DictReader and DictWriter

Lecture 273 Reading and writing multiple files

Lecture 274 The csv DictWriter

Lecture 275 The `zip` function

Lecture 276 Reading and writing to the same text file

Lecture 277 Solution to parsing functions challenge

Lecture 278 The record_invoice function

Lecture 279 Using the `record_invoice` function

Lecture 280 seek and tell

Lecture 281 Improving the `record_invoice` function

Lecture 282 Summary of working with text files

Lecture 283 Working with binary files - bytes and bytearray

Lecture 284 Reading a bitmap file

Lecture 285 Little endian and big endian

Lecture 286 Making sense of binary data

Lecture 287 Reading tags in an mp3 file

Lecture 288 The ID3v2 specification

Lecture 289 The code

Lecture 290 Filling in the blanks

Lecture 291 Extracting images

Lecture 292 Testing our read_id3 program

Lecture 293 Checking the hash of a file

Lecture 294 Summary of working with binary files

Lecture 295 End of Remaster

Section 9: Modules and Functions in Python

Lecture 296 Introduction to the Section

Lecture 297 Modules and import

Lecture 298 The standard Python library

Lecture 299 WebBrowser Module

Lecture 300 Time and DateTime in Python

Lecture 301 Time (Continued) and Challenge.

Lecture 302 Timezones

Lecture 303 Check Path In Windows

Lecture 304 Check Path on a Mac

Lecture 305 FAQ: Installing packages in IntelliJ IDEA and PyCharm

Lecture 306 Installing the pytz module (Windows/Mac/Linux)

Lecture 307 Using Timezones

Lecture 308 More on Timezones

Lecture 309 Timezone Challenge

Lecture 310 Introduction to Tkinter

Lecture 311 TkInter - Pack Geometry Manager

Lecture 312 TkInter - Grid Geometry Manager

Lecture 313 Advanced GUI Example Part 1

Lecture 314 Advanced GUI Example Part 2

Lecture 315 Advanced GUI Example Part 3

Lecture 316 Tkinter Challenge

Lecture 317 Functions in Python

Lecture 318 Functions Part 2

Lecture 319 Functions Part 3

Lecture 320 Parabola - More on Functions

Lecture 321 Scope in Functions

Lecture 322 Fix Function and Draw Circles

Lecture 323 Enhanced Circles and Challenge

Lecture 324 Blackjack Setup

Lecture 325 Load Cards

Lecture 326 Deal Cards

Lecture 327 Global Variables

Lecture 328 Global Keyword

Lecture 329 Test Blackjack Game

Lecture 330 Blackjack Challenge

Lecture 331 Importing Techniques

Lecture 332 Underscores in Python code

Lecture 333 Namespaces, more on Scope and Recursion

Lecture 334 Recursion with OS Module and Filesystem and Nonlocal keyword

Lecture 335 Nonlocal keyword, Free and LEGB

Section 10: Object Oriented Python

Lecture 336 Object Orientated Programming and Classes

Lecture 337 Instances, Constructors, Self and more

Lecture 338 Class Attributes

Lecture 339 Methods Part 1

Lecture 340 Methods Part 2

Lecture 341 Non Public and Mangling

Lecture 342 DocStrings and Raw Literals

Lecture 343 Album class and More on DocStrings

Lecture 344 Artist class and import Albums

Lecture 345 Load data and Write Checkfile

Lecture 346 Compare Files and Algorithm Flowcharts

Lecture 347 Implement Revised Load_Data Algorithm

Lecture 348 Write OOP Version

Lecture 349 Getters and Properties

Lecture 350 Remove Circular References Challenge

Lecture 351 Getters and Setters

Lecture 352 Data Attributes and Properties

Lecture 353 Alternate Syntax for Properties

Lecture 354 Inheritance

Lecture 355 Subclasses and Overloading

Lecture 356 Calling Super Methods

Lecture 357 Changing Behavior of Methods

Lecture 358 Overriding Methods

Lecture 359 Inheritance Challenge

Lecture 360 Polymorphism

Lecture 361 Duck Test

Lecture 362 Composition

Lecture 363 Composition Continued

Lecture 364 Test Code and Challenge

Lecture 365 Aggregation

Section 11: Using Databases in Python

Lecture 366 Introduction to Databases

Lecture 367 Database Terminology

Lecture 368 Sqlite3 Install on Windows

Lecture 369 Sqlite3 Install on a Mac

Lecture 370 SQLite3 Install on Ubuntu Linux

Lecture 371 Introduction to SQLite

Lecture 372 More with SQL using SQLite

Lecture 373 Querying data with Sqlite

Lecture 374 Order by and Joins

Lecture 375 More complex Joins

Lecture 376 Wildcards and Views

Lecture 377 Housekeeping and the Challenge

Lecture 378 SQL in Python

Lecture 379 Connections, Cursors and Transactions

Lecture 380 SQL Injection Attacks

Lecture 381 Placeholders and Parameter Substitution

Lecture 382 Exceptions

Lecture 383 Exceptions Challenge

Lecture 384 Exceptions Continued

Lecture 385 Raising Exceptions

Lecture 386 More on Exceptions

Lecture 387 Exceptions and TODO

Lecture 388 Rolling back Transactions

Lecture 389 Adding Database code to the Account Class

Lecture 390 GUI Database Editing Overview

Lecture 391 Ultimate Edition Database View

Lecture 392 Problems with Community Edition database plugin

Lecture 393 Update Deposit and Withdrawal Methods

Lecture 394 Displaying Time in Different Timezones

Lecture 395 SQLite3 strftime Function

Lecture 396 Challenge

Lecture 397 Problems Storing Timezones

Lecture 398 Rolling Back Transactions

Lecture 399 Simple Database Browser

Lecture 400 Scrollbars

Lecture 401 Star Args

Lecture 402 Kwargs

Lecture 403 More on KWArgs

Lecture 404 Scrollable Listbox

Lecture 405 Populating a Listbox from a Database

Lecture 406 Show Songs from Album

Lecture 407 The DataListbox Class Code

Lecture 408 Linking our DataListBoxes

Lecture 409 Linking our DataListBoxes Continued

Lecture 410 DataListbox Challenge

Section 12: Generators, Comprehensions and the timeit module

Lecture 411 Introduction

Lecture 412 Generators and Yield

Lecture 413 Next and Ranges

Lecture 414 Generator Examples - Fibonacci numbers and Calculating Pi

Lecture 415 The os.walk Generator

Lecture 416 Searching the Filesystem

Lecture 417 Reading Mp3 Tags

Lecture 418 List Comprehensions

Lecture 419 List Comprehensions and Side-Effects

Lecture 420 Challenge Solutions

Lecture 421 Conditional Comprehensions

Lecture 422 Conditional Expressions

Lecture 423 Challenges

Lecture 424 Challenge 1 Solution

Lecture 425 Challenge 2 Solution

Lecture 426 Nested Comprehensions

Lecture 427 Nested Comprehensions Challenge

Lecture 428 The timeit Module

Lecture 429 More on timeit

Lecture 430 timeit Continued and Challenge

Lecture 431 timeit Challenge

Lecture 432 Map Intro

Lecture 433 Map Challenge Completion

Lecture 434 The Filter Function

Lecture 435 The Reduce Function

Lecture 436 any and all

Lecture 437 Named Tuples

Lecture 438 any and all with Comprehensions

Section 13: Big O notation

Lecture 439 Big O notation

Lecture 440 Big O tables and graphs

Lecture 441 Bubble sort

Lecture 442 Big O of Bubble sort, and an optimisation

Lecture 443 Big O of our improved Bubble sort

Lecture 444 Bubble sort optimisation

Lecture 445 Best, worst and average cases

Lecture 446 Big O summary

Section 14: Section 9 Remaster in Progress

Lecture 447 Introduction to the section

Lecture 448 The turtle module

Lecture 449 Importing specific objects

Lecture 450 Namespaces and global scope

Lecture 451 Local scope

Lecture 452 Builtins

Lecture 453 Nested functions

Lecture 454 Enclosing scope

Lecture 455 A little white lie, or an oversimplification

Lecture 456 Changing the value of a free variable

Lecture 457 Investigating changes to a free variable

Lecture 458 The `nonlocal` keyword

Lecture 459 The `global` keyword

Lecture 460 Importing and the global namespace

Lecture 461 I nearly forgot

Lecture 462 import *

Lecture 463 if name == '__main__':

Lecture 464 An optimisation you may see in code

Lecture 465 The webbrowser module

Lecture 466 Dates and times in Python

Lecture 467 The datetime module's date class

Lecture 468 `timedelta` objects

Lecture 469 The datetime module's time class

Lecture 470 `datetime.date`, and another note about importing

Lecture 471 Aware and naive times

Lecture 472 zoneinfo backport

Lecture 473 timezone objects

Lecture 474 Timezone challenge solution

Lecture 475 Some behaviour you might not expect

Lecture 476 Perform arithmetic in UTC (most of the time)

Section 15: ARCHIVED-Install and Setup

Lecture 477 Python for Windows

Lecture 478 Installing IntelliJ IDEA for Windows

Lecture 479 Python for Mac

Lecture 480 Install IntelliJ IDEA for Mac

Lecture 481 Python for Linux

Lecture 482 Install IntelliJ IDEA for Linux

Lecture 483 FAQ: Change to IntelliJ project structure screen

Lecture 484 Configuring IntelliJ IDEA - WINDOWS, MAC and LINUX

Section 16: ARCHIVED-The Basics of Python

Lecture 485 Your Programming Careers Questions Answered

Lecture 486 Important Videos To Watch on Youtube

Lecture 487 Introduction

Lecture 488 Getting To Know Python

Lecture 489 Understanding More About Python

Lecture 490 Storing Items In Variables

Lecture 491 More About Variables And Strings

Lecture 492 String Formatting - Displaying Numbers And Strings

Section 17: ARCHIVED-Program Flow Control in Python

Lecture 493 Introduction

Lecture 494 An Introduction To Program Flow Control

Lecture 495 Test Conditions With If, ElIf & Else

Lecture 496 More Advanced If, ElIf & Else Processing

Lecture 497 Challenge - If Then Else

Lecture 498 For Loops

Lecture 499 Extending For Loops

Lecture 500 Understanding Continue, Break And Else

Lecture 501 Augmented Assignment

Lecture 502 Challenge - Program Flow - Part 1

Lecture 503 Challenge - Program Flow - Part 2

Lecture 504 While Loops

Lecture 505 Challenge - While Loop

Section 18: ARCHIVED-Lists, Ranges & Tuples in Python

Lecture 506 Introduction

Lecture 507 Lists In Python

Lecture 508 More About Lists

Lecture 509 Challenge - Lists

Lecture 510 Understanding Iterators

Lecture 511 Understanding and using Ranges

Lecture 512 More About Ranges

Lecture 513 Tuples

Lecture 514 More On Tuples

Section 19: ARCHIVED-The Binary number system explained

Lecture 515 Introduction to the Section

Lecture 516 Binary Basics

Lecture 517 What is binary

Lecture 518 Hexadecimal and Octal and the Challenge

Section 20: ARCHIVED-Python Dictionaries and Sets

Lecture 519 Introduction to the Section

Lecture 520 Change in the ordering of dictionary keys

Lecture 521 Python Dictionaries

Lecture 522 Dictionaries Part 2

Lecture 523 Dictionaries Part 3

Lecture 524 Dictionaries Challenge

Lecture 525 More on Dictionaries

Lecture 526 The Second Dictionary Challenge

Lecture 527 Sets

Lecture 528 Python Sets Part 2 and Challenge

Section 21: ARCHIVED-Input and Output (I/O) in Python

Lecture 529 Introduction to the Section

Lecture 530 Reading and writing text files

Lecture 531 Writing Text Files

Lecture 532 Appending to Files and Challenge

Lecture 533 Writing Binary Files Manually

Lecture 534 Using Pickle To Write Binary Files

Lecture 535 Shelve

Lecture 536 Manipulating Data With Shelve

Lecture 537 Updating With Shelve

Lecture 538 Shelve Challenge

Lecture 539 Challenge Continued

Section 22: Extra Information - Source code, and other stuff

Lecture 540 Source code for all Programs

Section 23: Bonus - Including Slides

Lecture 541 Bonus Downloads including slides

Lecture 542 Spacer

Lecture 366 Introduction to Databases

Lecture 367 Database Terminology

Lecture 368 Sqlite3 Install on Windows

Lecture 369 Sqlite3 Install on a Mac

Lecture 370 SQLite3 Install on Ubuntu Linux

Lecture 371 Introduction to SQLite

Lecture 372 More with SQL using SQLite

Lecture 373 Querying data with Sqlite

Lecture 374 Order by and Joins

Lecture 375 More complex Joins

Lecture 376 Wildcards and Views

Lecture 377 Housekeeping and the Challenge

Lecture 378 SQL in Python

Lecture 379 Connections, Cursors and Transactions

Lecture 380 SQL Injection Attacks

Lecture 381 Placeholders and Parameter Substitution

Lecture 382 Exceptions

Lecture 383 Exceptions Challenge

Lecture 384 Exceptions Continued

Lecture 385 Raising Exceptions

Lecture 386 More on Exceptions

Lecture 387 Exceptions and TODO

Lecture 388 Rolling back Transactions

Lecture 389 Adding Database code to the Account Class

Lecture 390 GUI Database Editing Overview

Lecture 391 Ultimate Edition Database View

Lecture 392 Problems with Community Edition database plugin

Lecture 393 Update Deposit and Withdrawal Methods

Lecture 394 Displaying Time in Different Timezones

Lecture 395 SQLite3 strftime Function

Lecture 396 Challenge

Lecture 397 Problems Storing Timezones

Lecture 398 Rolling Back Transactions

Lecture 399 Simple Database Browser

Lecture 400 Scrollbars

Lecture 401 Star Args

Lecture 402 Kwargs

Lecture 403 More on KWArgs

Lecture 404 Scrollable Listbox

Lecture 405 Populating a Listbox from a Database

Lecture 406 Show Songs from Album

Lecture 407 The DataListbox Class Code

Lecture 408 Linking our DataListBoxes

Lecture 409 Linking our DataListBoxes Continued

Lecture 410 DataListbox Challenge

Section 12: Generators, Comprehensions and the timeit module

Lecture 411 Introduction

Lecture 412 Generators and Yield

Lecture 413 Next and Ranges

Lecture 414 Generator Examples - Fibonacci numbers and Calculating Pi

Lecture 415 The os.walk Generator

Lecture 416 Searching the Filesystem

Lecture 417 Reading Mp3 Tags

Lecture 418 List Comprehensions

Lecture 419 List Comprehensions and Side-Effects

Lecture 420 Challenge Solutions

Lecture 421 Conditional Comprehensions

Lecture 422 Conditional Expressions

Lecture 423 Challenges

Lecture 424 Challenge 1 Solution

Lecture 425 Challenge 2 Solution

Lecture 426 Nested Comprehensions

Lecture 427 Nested Comprehensions Challenge

Lecture 428 The timeit Module

Lecture 429 More on timeit

Lecture 430 timeit Continued and Challenge

Lecture 431 timeit Challenge

Lecture 432 Map Intro

Lecture 433 Map Challenge Completion

Lecture 434 The Filter Function

Lecture 435 The Reduce Function

Lecture 436 any and all

Lecture 437 Named Tuples

Lecture 438 any and all with Comprehensions

Section 13: Big O notation

Lecture 439 Big O notation

Lecture 440 Big O tables and graphs

Lecture 441 Bubble sort

Lecture 442 Big O of Bubble sort, and an optimisation

Lecture 443 Big O of our improved Bubble sort

Lecture 444 Bubble sort optimisation

Lecture 445 Best, worst and average cases

Lecture 446 Big O summary

Section 14: Section 9 Remaster in Progress

Lecture 447 Introduction to the section

Lecture 448 The turtle module

Lecture 449 Importing specific objects

Lecture 450 Namespaces and global scope

Lecture 451 Local scope

Lecture 452 Builtins

Lecture 453 Nested functions

Lecture 454 Enclosing scope

Lecture 455 A little white lie, or an oversimplification

Lecture 456 Changing the value of a free variable

Lecture 457 Investigating changes to a free variable

Lecture 458 The `nonlocal` keyword

Lecture 459 The `global` keyword

Lecture 460 Importing and the global namespace

Lecture 461 I nearly forgot

Lecture 462 import *

Lecture 463 if name == '__main__':

Lecture 464 An optimisation you may see in code

Lecture 465 The webbrowser module

Lecture 466 Dates and times in Python

Lecture 467 The datetime module's date class

Lecture 468 `timedelta` objects

Lecture 469 The datetime module's time class

Lecture 470 `datetime.date`, and another note about importing

Lecture 471 Aware and naive times

Lecture 472 zoneinfo backport

Lecture 473 timezone objects

Lecture 474 Timezone challenge solution

Lecture 475 Some behaviour you might not expect

Lecture 476 Perform arithmetic in UTC (most of the time)

Section 15: ARCHIVED-Install and Setup

Lecture 477 Python for Windows

Lecture 478 Installing IntelliJ IDEA for Windows

Lecture 479 Python for Mac

Lecture 480 Install IntelliJ IDEA for Mac

Lecture 481 Python for Linux

Lecture 482 Install IntelliJ IDEA for Linux

Lecture 483 FAQ: Change to IntelliJ project structure screen

Lecture 484 Configuring IntelliJ IDEA - WINDOWS, MAC and LINUX

Section 16: ARCHIVED-The Basics of Python

Lecture 485 Your Programming Careers Questions Answered

Lecture 486 Important Videos To Watch on Youtube

Lecture 487 Introduction

Lecture 488 Getting To Know Python

Lecture 489 Understanding More About Python

Lecture 490 Storing Items In Variables

Lecture 491 More About Variables And Strings

Lecture 492 String Formatting - Displaying Numbers And Strings

Section 17: ARCHIVED-Program Flow Control in Python

Lecture 493 Introduction

Lecture 494 An Introduction To Program Flow Control

Lecture 495 Test Conditions With If, ElIf & Else

Lecture 496 More Advanced If, ElIf & Else Processing

Lecture 497 Challenge - If Then Else

Lecture 498 For Loops

Lecture 499 Extending For Loops

Lecture 500 Understanding Continue, Break And Else

Lecture 501 Augmented Assignment

Lecture 502 Challenge - Program Flow - Part 1

Lecture 503 Challenge - Program Flow - Part 2

Lecture 504 While Loops

Lecture 505 Challenge - While Loop

Section 18: ARCHIVED-Lists, Ranges & Tuples in Python

Lecture 506 Introduction

Lecture 507 Lists In Python

Lecture 508 More About Lists

Lecture 509 Challenge - Lists

Lecture 510 Understanding Iterators

Lecture 511 Understanding and using Ranges

Lecture 512 More About Ranges

Lecture 513 Tuples

Lecture 514 More On Tuples

Section 19: ARCHIVED-The Binary number system explained

Lecture 515 Introduction to the Section

Lecture 516 Binary Basics

Lecture 517 What is binary

Lecture 518 Hexadecimal and Octal and the Challenge

Section 20: ARCHIVED-Python Dictionaries and Sets

Lecture 519 Introduction to the Section

Lecture 520 Change in the ordering of dictionary keys

Lecture 521 Python Dictionaries

Lecture 522 Dictionaries Part 2

Lecture 523 Dictionaries Part 3

Lecture 524 Dictionaries Challenge

Lecture 525 More on Dictionaries

Lecture 526 The Second Dictionary Challenge

Lecture 527 Sets

Lecture 528 Python Sets Part 2 and Challenge

Section 21: ARCHIVED-Input and Output (I/O) in Python

Lecture 529 Introduction to the Section

Lecture 530 Reading and writing text files

Lecture 531 Writing Text Files

Lecture 532 Appending to Files and Challenge

Lecture 533 Writing Binary Files Manually

Lecture 534 Using Pickle To Write Binary Files

Lecture 535 Shelve

Lecture 536 Manipulating Data With Shelve

Lecture 537 Updating With Shelve

Lecture 538 Shelve Challenge

Lecture 539 Challenge Continued

Section 22: Extra Information - Source code, and other stuff

Lecture 540 Source code for all Programs

Section 23: Bonus - Including Slides

Lecture 541 Bonus Downloads including slides

Lecture 542 Spacer

Beginners with no previous programming experience looking to obtain the skills to get their first programming job.,Anyone looking to to build the minimum Python programming skills necessary as a pre-requisites for moving into machine learning, data science, and artificial intelligence.,Existing programmers who want to improve their career options by learning the Python programming language.,If you are an expert Python programmer with extensive knowledge, and many years’ experience, then this course is probably not for you.