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Python – Complete Python, Django, Data Science and ML Guide [Video]
Python – Complete Python, Django, Data Science and ML Guide [Video]

Python – Complete Python, Django, Data Science and ML Guide: Dive into Programming, Django, Jupyter, Pygame, and AI Essentials [Video]

By Bogdan Stashchuk
Mex$2,666.99
Video Nov 2023 50 hours 30 minutes 1st Edition
Video
Mex$2,666.99
Subscription
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Video
Mex$2,666.99
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Product Details


Publication date : Nov 1, 2023
Length 50 hours 30 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781835465141
Category :

Key benefits

  • Dive into over 50 hours of comprehensive Python content
  • Perfect for developers, data scientists, and game creators
  • Build dynamic web applications with Django and games harnessing Pygame

Description

Join us on an immersive Python programming journey, spanning over 50 hours of learning. Whether you're a novice or experienced, this course equips you with vital Python skills for careers and projects. Starting from the basics, grasp Python's core principles and proficiency in real-world functions. As Python's popularity grows, this course readies you for the rising demand for Python developers. You'll practice hand-on examples using Python's interpreter and Visual Studio Code with Code Runner to solidify your skills. With a focus on Data Science and Machine Learning, you'll master essential packages such as NumPy, Pandas, Matplotlib, and Scikit-learn, using the versatile Jupyter Notebook. The course extensively covers Python's fundamental aspects, spanning variables, lists, dictionaries, and venturing into advanced topics like classes, loops, modules, and creating virtual environments. The goal is to provide you with a solid Python foundation. You'll also gain insight into functional and object-oriented Python programming, making you a versatile coder. The course is thoughtfully structured, explaining not just "how" but also "why" we use specific methods and best practices. By course end, you'll harness Python's full potential for web and mobile app development, data science, machine learning, and game creation.

What you will learn

Grasp concepts such as data types, loops, and conditional statements to build a robust coding foundation Understand OOP principles like inheritance, encapsulation, and polymorphism for streamlined code Manipulate files, directories, and efficiently manage external modules through Python Master real-world datasets with NumPy, Pandas, Matplotlib and more Ensure code reliability through Python's error handling and master the nuances of PIP and virtual project isolation

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Nov 1, 2023
Length 50 hours 30 minutes
Edition : 1st Edition
Language : English
ISBN-13 : 9781835465141
Category :

Table of Contents

91 Chapters
1. Introduction to Python Chevron down icon Chevron up icon
2. Installing and Using Pycharm IDE Chevron down icon Chevron up icon
3. Basics Concepts in Python Chevron down icon Chevron up icon
4. Introduction to Functions and Built-in Functions in python Chevron down icon Chevron up icon
5. Code formatting and PEP8 Chevron down icon Chevron up icon
6. Comments Chevron down icon Chevron up icon
7. Expressions and Instructions Chevron down icon Chevron up icon
8. Variables Chevron down icon Chevron up icon
9. Data Types and structures Chevron down icon Chevron up icon
10. Strings Chevron down icon Chevron up icon
11. String Concatenation Chevron down icon Chevron up icon
12. Numeric Types Chevron down icon Chevron up icon
13. Boolean Values Chevron down icon Chevron up icon
14. Magic Methods Chevron down icon Chevron up icon
15. Lists Chevron down icon Chevron up icon
16. Dictionaries Chevron down icon Chevron up icon
17. Tuples Chevron down icon Chevron up icon
18. Sets Chevron down icon Chevron up icon
19. Ranges Chevron down icon Chevron up icon
20. Working with Sequences Chevron down icon Chevron up icon
21. Modifying Objects in Python Chevron down icon Chevron up icon
22. Functions Chevron down icon Chevron up icon
23. Function Arguments Chevron down icon Chevron up icon
24. Args and kwargs in Functions Chevron down icon Chevron up icon
25. Default Function Parameters Chevron down icon Chevron up icon
26. Docstrings Chevron down icon Chevron up icon
27. Callback Functions Chevron down icon Chevron up icon
28. Global and local Variables Chevron down icon Chevron up icon
29. Operators Chevron down icon Chevron up icon
30. Falsy and Truthy Values Chevron down icon Chevron up icon
31. Logical and Comparison Operators Chevron down icon Chevron up icon
32. Lambda Functions Chevron down icon Chevron up icon
33. Error handling Chevron down icon Chevron up icon
34. Sequence Unpacking Chevron down icon Chevron up icon
35. Unpacking Dictionary Chevron down icon Chevron up icon
36. Conditional Statements Chevron down icon Chevron up icon
37. Ternary Operator Chevron down icon Chevron up icon
38. For-In loop Chevron down icon Chevron up icon
39. While Loop Chevron down icon Chevron up icon
40. For-In Expression (Comprehension) Chevron down icon Chevron up icon
41. Generators Chevron down icon Chevron up icon
42. Decorator Functions Chevron down icon Chevron up icon
43. Classes and Objects Chevron down icon Chevron up icon
44. Instance and Class method Chevron down icon Chevron up icon
45. Magic Methods in Classes Chevron down icon Chevron up icon
46. Classes Extension Chevron down icon Chevron up icon
47. Classes in Practice Chevron down icon Chevron up icon
48. Key Principles in Object-Oriented Programming (OOP) Chevron down icon Chevron up icon
49. Modules Chevron down icon Chevron up icon
50. Built-in Modules Chevron down icon Chevron up icon
51. What is __name__ and __main__ Chevron down icon Chevron up icon
52. JavaScript Object Notation (JSON) Chevron down icon Chevron up icon
53. Working with Files Chevron down icon Chevron up icon
54. Working with zip archives Chevron down icon Chevron up icon
55. Working with CSV Files Chevron down icon Chevron up icon
56. Working with Dates and Times Chevron down icon Chevron up icon
57. Generating Random Sequences and Passwords Chevron down icon Chevron up icon
58. Math Module and Recursive Functions Chevron down icon Chevron up icon
59. Regular Expressions Chevron down icon Chevron up icon
60. Sending Emails Chevron down icon Chevron up icon
61. Working with SQLite Database Chevron down icon Chevron up icon
62. Other Built-in Modules Chevron down icon Chevron up icon
63. Virtual Environments Chevron down icon Chevron up icon
64. Pipenv for Virtual Environments Management Chevron down icon Chevron up icon
65. Introduction to the Django web framework Chevron down icon Chevron up icon
66. Creating a Django project Chevron down icon Chevron up icon
67. Creating a Django Application Chevron down icon Chevron up icon
68. Database and Migrations in Django Chevron down icon Chevron up icon
69. Creating Templates in Django Chevron down icon Chevron up icon
70. Extending Other Templates in Django Chevron down icon Chevron up icon
71. Creating Multiple routes and View Functions Chevron down icon Chevron up icon
72. Routing between Pages in Django Chevron down icon Chevron up icon
73. Creating an API Django Application Chevron down icon Chevron up icon
74. Managing Authentication for API Requests Chevron down icon Chevron up icon
75. Django Project Refactoring and Admin Settings Chevron down icon Chevron up icon
76. Creating Games with Pygame Chevron down icon Chevron up icon
77. Creating a Shooter Game with Pygame Chevron down icon Chevron up icon
78. Interaction of the Elements in the Pygame Chevron down icon Chevron up icon
79. Game Refactoring using Classes and OOP Chevron down icon Chevron up icon
80. Jupyter Notebook Chevron down icon Chevron up icon
81. Jupyter Lab Chevron down icon Chevron up icon
82. NumPy - Creating Arrays Chevron down icon Chevron up icon
83. NumPy – Random Values Chevron down icon Chevron up icon
84. NumPy – Examples Chevron down icon Chevron up icon
85. Pandas – Working with DataFrames and Series Chevron down icon Chevron up icon
86. Pandas – Random Data Working with CSV Chevron down icon Chevron up icon
87. Pandas – Analysing CSV- Loaded DataFrames Chevron down icon Chevron up icon
88. Matplotlib – Creating Charts Chevron down icon Chevron up icon
89. Scikit – Learn - Machine Learning Chevron down icon Chevron up icon
90. Machine Learning Model for Real Data Chevron down icon Chevron up icon
91. Making Machine Learning Model More Real Chevron down icon Chevron up icon

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