Python Programming for Developers
11h 14m 25s
English
Paid
Course description
Finally, a Python course that doesn’t insult your intelligence and assume you know nothing. Let’s face it, you know what a variable and function are - you don’t need me to tell you! That’s why this course is designed to be different. It’s a specialist crash course for developers that gets you up-to-speed in no time.
Read more about the course
Why Learn Python?
- Boost your existing skills - growing demand for Python developers
- It's versatile - Mathematicians, scientists and engineers use it for various applications
- Easier to master than languages such as C, C++, JavaScript, etc.
- Universities teach it – both in computer science and other courses
- Big companies use it – Google, Facebook, Dropbox, Reddit, Spotify, Quora, etc.
- Runs cross-platform – Python apps work on Windows, Mac, Linux
What can you do with Python?
- Scripting – easily automate repetitive tasks e.g. web crawling, sending emails…
- App backends – use Python frameworks to build app backends fast with less code
- AI & machine learning – number 1 language in this field – big library & data collection
- Data analysis & visualization – perfect for today’s big data world
- Computation & calculation – simple syntax & many powerful libraries – scientists, engineers, mathematicians can focus on creating algorithms, formulae, etc.
- Desktop apps – Dropbox desktop app is written in Python! Need I say more?!
- Education – Python is popular globally in schools, colleges, universities. It’s so simple that young kids can pick it up, but so powerful PHD students use it.
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/ #1: 1- What is Python
All Course Lessons (170)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | 1- What is Python Demo | 03:22 | |
| 2 | 2- Installing Python | 02:21 | |
| 3 | 3- Code Editors | 00:59 | |
| 4 | 4- Your First Python Program | 02:26 | |
| 5 | 5- Python Extension | 02:53 | |
| 6 | 6- Linting Python Code | 04:15 | |
| 7 | 7- Formatting Python Code | 03:55 | |
| 8 | 8- Running Python Code | 03:00 | |
| 9 | 9- Python Implementations | 02:29 | |
| 10 | 10- How Python Code is Executed | 02:47 | |
| 11 | 11- Summary | 00:22 | |
| 12 | 1- Variables | 02:05 | |
| 13 | 2- Dynamic Typing | 02:37 | |
| 14 | 3- Type Annotation | 01:51 | |
| 15 | 4- Mutable and Immutable Types | 02:59 | |
| 16 | 5- Strings | 04:12 | |
| 17 | 6- Escape Sequences | 03:20 | |
| 18 | 7- Formatted Strings | 02:09 | |
| 19 | 8- Useful String Methods | 03:21 | |
| 20 | 9- Numbers | 02:10 | |
| 21 | 10- Arithmetic Operators | 01:48 | |
| 22 | 11- Working with Numbers | 02:38 | |
| 23 | 12- Type Conversion | 04:23 | |
| 24 | 13- Conditional Statements | 03:25 | |
| 25 | 14- Logical Operators | 03:07 | |
| 26 | 15- Ternary Operator | 01:18 | |
| 27 | 16- For Loops | 04:09 | |
| 28 | 17- For..Else | 02:39 | |
| 29 | 18- While Loops | 01:48 | |
| 30 | 19- Functions | 04:42 | |
| 31 | 20- Arguments- xargs | 02:28 | |
| 32 | 21- Arguments- xxargs | 02:05 | |
| 33 | 22- Scope | 03:38 | |
| 34 | 23- Debugging | 03:33 | |
| 35 | 24- VSCode Coding Tricks - Windows | 02:22 | |
| 36 | 25- VSCode Coding Tricks - Mac | 01:50 | |
| 37 | 26- Exercise | 01:30 | |
| 38 | 27- Solution | 04:42 | |
| 39 | 1- Lists | 03:55 | |
| 40 | 2- Accessing Items | 03:14 | |
| 41 | 3- List Unpacking | 03:52 | |
| 42 | 4- Looping over Lists | 02:55 | |
| 43 | 5- Adding or Removing Items | 02:57 | |
| 44 | 6- Finding Items | 01:29 | |
| 45 | 7- Sorting Lists | 04:36 | |
| 46 | 8- Lambda Functions | 01:50 | |
| 47 | 9- Map Function | 03:26 | |
| 48 | 10- Filter Function | 02:06 | |
| 49 | 11- List Comprehensions | 03:11 | |
| 50 | 12- Zip Function | 01:50 | |
| 51 | 13- Stacks | 04:25 | |
| 52 | 14- Queues | 02:51 | |
| 53 | 15- Tuples | 04:03 | |
| 54 | 16- Swapping Variables | 02:38 | |
| 55 | 17- Arrays | 03:12 | |
| 56 | 18- Sets | 04:04 | |
| 57 | 19- Dictionaries | 05:25 | |
| 58 | 20- Dictionary Comprehensions | 03:20 | |
| 59 | 21- Generator Expressions | 03:52 | |
| 60 | 22- Unpacking Operator | 04:06 | |
| 61 | 23- Exercise | 06:22 | |
| 62 | 1- Exceptions | 02:17 | |
| 63 | 2- Handling Exceptions | 04:11 | |
| 64 | 3- Handling Different Exceptions | 03:06 | |
| 65 | 4- Cleaning Up | 01:58 | |
| 66 | 5- The With Statement | 03:08 | |
| 67 | 6- Raising Exceptions | 03:22 | |
| 68 | 7- Cost of Raising Exceptions | 04:42 | |
| 69 | 1- Classes | 02:36 | |
| 70 | 2- Creating Classes | 03:46 | |
| 71 | 3- Constructors | 04:38 | |
| 72 | 4- Class vs Instance Attributes | 03:59 | |
| 73 | 5- Class vs Instance Methods | 04:06 | |
| 74 | 6- Magic Methods | 03:14 | |
| 75 | 7- Comparing Objects | 03:12 | |
| 76 | 8- Performing Arithmetic Operations | 01:32 | |
| 77 | 9- Making Custom Containers | 06:56 | |
| 78 | 10- Private Members | 03:41 | |
| 79 | 11- Properties | 07:31 | |
| 80 | 12- Inheritance | 04:24 | |
| 81 | 13- The Object Class | 02:24 | |
| 82 | 14- Method Overriding | 03:15 | |
| 83 | 15- Multi-level Inheritance | 02:43 | |
| 84 | 16- Multiple Inheritance | 03:23 | |
| 85 | 17- A Good Example of Inheritance | 04:32 | |
| 86 | 18- Abstract Base Classes | 04:51 | |
| 87 | 19- Polymorphism | 03:57 | |
| 88 | 20- Duck Typing | 02:51 | |
| 89 | 21- Extending Built-in Types | 02:27 | |
| 90 | 22- Data Classes | 04:37 | |
| 91 | 1- Creating Modules | 04:17 | |
| 92 | 2- Compiled Python Files | 02:20 | |
| 93 | 3- Module Search Path | 01:36 | |
| 94 | 4- Packages | 02:28 | |
| 95 | 5- Sub-packages | 01:02 | |
| 96 | 6- Intra-package References | 01:37 | |
| 97 | 7- The dir Function | 01:40 | |
| 98 | 8- Executing Modules as Scripts | 02:56 | |
| 99 | 1- Python Standard Library | 00:52 | |
| 100 | 2- Working With Paths | 04:49 | |
| 101 | 3- Working with Directories | 04:15 | |
| 102 | 4- Working with Files | 04:00 | |
| 103 | 5- Working with Zip Files | 03:16 | |
| 104 | 6- Working with CSV Files | 04:51 | |
| 105 | 7- Working with JSON Files | 03:59 | |
| 106 | 8- Working with a SQLite Database | 09:11 | |
| 107 | 9- Working with Timestamps | 02:25 | |
| 108 | 10- Working with DateTimes | 05:06 | |
| 109 | 11- Working with Time Deltas | 02:42 | |
| 110 | 12- Generating Random Values | 04:10 | |
| 111 | 13- Opening the Browser | 01:13 | |
| 112 | 14- Sending Emails | 06:49 | |
| 113 | 15- Templates | 04:54 | |
| 114 | 16- Command-line Arguments | 01:55 | |
| 115 | 17- Running External Programs | 08:07 | |
| 116 | 1- Pypi | 01:50 | |
| 117 | 2- Pip | 06:24 | |
| 118 | 3- Virtual Environments | 04:05 | |
| 119 | 4- Pipenv | 03:41 | |
| 120 | 5- Virtual Environments in VSCode | 03:50 | |
| 121 | 6- Pipfile | 04:49 | |
| 122 | 7- Managing Dependencies | 03:29 | |
| 123 | 8- Publishing Packages | 08:24 | |
| 124 | 9- Docstrings | 05:49 | |
| 125 | 10- Pydoc | 04:07 | |
| 126 | 1- Introduction | 01:42 | |
| 127 | 2- What are APIs | 02:37 | |
| 128 | 3- Yelp API | 02:52 | |
| 129 | 4- Searching for Businesses | 09:55 | |
| 130 | 5- Hiding API Keys | 02:06 | |
| 131 | 6- Sending Text Messages | 06:03 | |
| 132 | 7- Web Scraping | 09:07 | |
| 133 | 8- Browser Automation | 11:29 | |
| 134 | 9- Working with PDFs | 06:19 | |
| 135 | 10- Working with Excel Spreadsheets | 09:53 | |
| 136 | 11- Command Query Separation Principle | 04:40 | |
| 137 | 12- NumPy | 09:07 | |
| 138 | 1- Introduction | 01:44 | |
| 139 | 2- Your First Django Project | 04:12 | |
| 140 | 3- Your First App | 03:42 | |
| 141 | 4- Views | 08:00 | |
| 142 | 5- Models | 04:58 | |
| 143 | 6- Migrations | 08:01 | |
| 144 | 7- Changing the Models | 05:39 | |
| 145 | 8- Admin | 04:30 | |
| 146 | 9- Customizing the Admin | 06:56 | |
| 147 | 10- Database Abstraction API | 03:53 | |
| 148 | 11- Templates | 10:24 | |
| 149 | 12- Adding Bootstrap | 04:20 | |
| 150 | 13- Customizing the Layout | 02:25 | |
| 151 | 14- Sharing a Template Across Multiple Apps | 03:49 | |
| 152 | 15- Url Parameters | 04:38 | |
| 153 | 16- Getting a Single Object | 03:49 | |
| 154 | 17- Raising 404 Errors | 03:52 | |
| 155 | 18- Referencing Urls | 03:48 | |
| 156 | 19- Creating APIs | 03:52 | |
| 157 | 20- Adding the Homepage | 09:27 | |
| 158 | 21- Getting Ready to Deploy | 04:28 | |
| 159 | 22- Deployment | 09:45 | |
| 160 | 1- What is Machine Learning | 08:00 | |
| 161 | 2- Machine Learning in Action | 01:59 | |
| 162 | 3- Libraries and Tools | 02:48 | |
| 163 | 4- Importing a Data Set | 04:55 | |
| 164 | 5- Jupyter Shortcuts | 06:22 | |
| 165 | 6- A Real Machine Learning Problem | 05:27 | |
| 166 | 7- Preparing the Data | 03:18 | |
| 167 | 8- Learning and Predicting | 03:06 | |
| 168 | 9- Calculating the Accuracy | 04:05 | |
| 169 | 10- Persisting Models | 06:22 | |
| 170 | 11- Visualizing a Decision Tree | 06:27 |
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