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Introduction to Python

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  1. The Course

    Meet the Instructors
  2. Introduction to the Course
  3. Introduction
    Why Python?
    1 Quiz
  4. Introduction to IDEs
    1 Quiz
  5. Introduction to Colab
    1 Quiz
  6. Important Concepts
    Program/Script
    1 Quiz
  7. Variable
    1 Quiz
  8. Bug
    1 Quiz
  9. Design Philosophy
  10. Interpreted Language
    1 Quiz
  11. Dynamic Typing
    1 Quiz
  12. Dynamic Typing - practical
    1 Quiz
  13. Indentation to define blocks
    1 Quiz
  14. Indentation - practical
    1 Quiz
  15. Object-Oriented Programming
    1 Quiz
  16. Object-Oriented - practical
    1 Quiz
  17. Important Concepts - recap
  18. Basic Syntax
    Data Types
    1 Quiz
  19. Arithmetic Operators
    1 Quiz
  20. Comparison Operators
    1 Quiz
  21. Logical Operators
    1 Quiz
  22. Assignment Operators
    1 Quiz
  23. Membership & Identity Operators
    1 Quiz
  24. Basic Data Structure
    Lists
    1 Quiz
  25. Lists - practical
    1 Quiz
  26. Tuples
    1 Quiz
  27. Tuples - practical
    1 Quiz
  28. Dictionaries
    1 Quiz
  29. Dictionaries - practical
    1 Quiz
  30. Control Flow
    Conditionals
    1 Quiz
  31. Conditionals - practical
    1 Quiz
  32. Loops
    1 Quiz
  33. Loops: "for" - practical
    1 Quiz
  34. Loops: "while" - practical
    1 Quiz
  35. Tools
    1 Quiz
  36. Tools - practical
    1 Quiz
  37. Functions
    Why do we use functions?
    1 Quiz
  38. User-defined Functions
    1 Quiz
  39. Naming Conventions
    1 Quiz
  40. Pre-defined functions - practical
    1 Quiz
  41. User-defined Functions - practical: 3 basic examples
    1 Quiz
  42. User-defined Functions - practical: Moments of Inertia
  43. User-defined Functions - practical: Total Drag Force
  44. User-defined Functions - practical: Reynolds Number
  45. User-defined Functions - practical: Buoyant Force
  46. User-defined Functions - practical: Total Resistance
  47. User-defined Functions - practical: Skin Friction Coefficient
  48. User-defined Functions - practical: Hull Speed
  49. Basic File Handling
    Introduction to Basic File Handling
    1 Quiz
  50. Basic File Handling - practical
    1 Quiz
  51. Classes
    What is a Class?
    1 Quiz
  52. Why do we use Classes?
    1 Quiz
  53. Anatomy of a Class
    1 Quiz
  54. Naming Conventions
    1 Quiz
  55. Class Objects
    1 Quiz
  56. Instance Objects
    1 Quiz
  57. Instance Methods
    1 Quiz
  58. Class Recap
  59. Classes - practical: General
    1 Quiz
  60. Classes - practical: Dataset without Classes
  61. Classes - practical: Dataset with Classes
    1 Quiz
  62. Packages and Modules
    Modules: what are they and how do you create and import them?
    1 Quiz
  63. How do we share the data and code?
    1 Quiz
  64. Accessing Google Drive from Google Colab
    1 Quiz
  65. Modules - practical
    1 Quiz
  66. Packages: what are they and how do you create and import them?
    1 Quiz
  67. Packages - practical: General
    1 Quiz
  68. Packages - practical: Naval Engineering job
  69. Python Standard Library
    1 Quiz
  70. Python Standard Library - practical
    1 Quiz
  71. Popular Packages
    1 Quiz
  72. Popular Packages - practical: Numpy, Matplotlib
    1 Quiz
  73. Popular Packages - practical: SciPy, SymPy, Pytorch
    1 Quiz
  74. Final Assignment - Capstone Project
    Final Assignment (mandatory)
  75. Exercise 1
  76. Exercise 2
  77. Exercise 3
  78. Exercises 4 and 5
  79. Course Materials
    Course Materials
  80. Course Survey
    Course Evaluation Survey
    1 Quiz
  81. Summary
    Wrap-up

Congratulations!

You have successfully completed our Introduction to Python course, and we are incredibly proud of your progress!

We started with the basics, introducing you to Python and the Google Colab platform.

You learned essential concepts like variables, bugs, dynamic typing, and basic syntax.

You explored data types, operators, and data structures such as lists, tuples, and dictionaries.

You mastered control flow with conditionals and loops, making your code efficient and dynamic.

You also learned how to create and use predefined and user-defined functions to organize and reuse your code.

You learned to read from and write files, a crucial skill for managing data in real-world applications.

You dove into object-oriented programming, defining classes, and working with attributes and methods.

You understood the power of modules and packages, learning to create, import, and utilize them effectively.

We introduced you to popular Python libraries like NumPy, Pandas, Scipy, and Pytorch, expanding your toolkit for data analysis and machine learning.

Finally, you successfully managed and analyzed an extensive dataset of 10,000 parametrized hull geometries. You learned how to clean the dataset, analyze it, and extract valuable insights.

So what’s next?

Your new knowledge opens up a world of possibilities.

You could pursue a career in data science, automate tasks you have been doing manually, or even explore the fascinating world of machine learning, which is revolutionizing industries worldwide.

Our suggestion is to choose a project that excites you so you can put some time into what you have learned. There are countless resources, including databases such as Kaggle and codes from others on GitHub and GitLab. Set achievable goals, and you will enjoy a steady stream of victories to keep you motivated.

Now, more than ever, we have infinite programming resources, forums about programming, and large language models such as ChatGPT at our fingertips. The path to coding has never been so open to everyone. With just the basics, you can utilize these resources to reach unthinkable goals.

Understanding these fundamental concepts is all you need to start your project and understand code from others. Mastering these basics truly opens up a new world of possibilities.

Remember, this is just the beginning; keep practicing, experimenting, and, most importantly, keep coding.

The future is bright, and your journey with Python has only just begun.