English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 8h 06m | 2.60 GB
Python is a great, beginner-friendly programming language because it was originally designed with learners in mind. It is also used by professional developers in a wide range of applications, like web programming, data science, artificial intelligence, and DevOps. It is estimated that there are about 3 million Python programmers in the world, and by some accounts, it is the fastest growing, most widely used language, especially in high-GDP countries. Out of dozens of programming languages, Python is the third most loved language and is the number one language that current and aspiring developers want to learn.
As an instructor who regularly teaches people who are completely new to programming, Arianne has found that students are often looking for more context than is provided in most introductory courses. Specifically, students want to know how various languages fit into the programming landscape, as well as what next steps they should take after the course. Introduction to Python LiveLessons attempts to fill these gaps by providing “extra context” lessons, in addition to teaching fundamental programming concepts, answering questions like, “Why are there so many languages?”, “How is Python different from other languages?”, and “What concepts should I learn next?” Afterwards, the lessons end with a crash-course on data analysis and web development, the two primary uses of Python.
This 6+ hour LiveLesson video helps absolute beginners get started in Python, which is one of the most popular and in-demand languages in use today. Python was created with beginners in mind, but don’t let its simple nature fool you. It is used by professional developers in a wide range of applications, such as web programming, data analysis, machine learning, and DevOps. While most introductory courses focus on the basics of the language, this course goes one step further to explain how Python is used in practice in the fields of data analysis and web development.
Students learn fundamental programming concepts–for example, variables and functions. They are given hands-on, modular problems to solve so they can progress as they go. Finally, students tie it all together and experiment with some real programming in the form of text-based games.
The overall goal of this course is to help absolute beginners learn from scratch, navigate the esoteric world of software development, and then kick-start their programming journey with introductions to two of the more common uses of Python: data analysis and web development.
What You Will Learn
Students will learn how to
- Think like a programmer
- Solve mini practice problems in Python
- Use common libraries like “math” and “random”
- Build three small games to practice their learning
- Use PyCharm, a code editor for Python
- Clean up code so it is easy to understand
Once the basics are down, Arianne will provide
- A brief introduction to data analysis
- A brief introduction to web development
- An overview of classes, external libraries, and virtual environments in Python
Table of Contents
02 Learning objectives
03 1.1 Install Python and PyCharm
04 1.2 Run your first Python code
05 1.3 Get more context – understand what programming is
06 Learning objectives
07 2.1 Learn about types
08 2.2 Work with variables
09 2.3 Debug errors
10 2.4 Use libraries
11 2.5 Get more context – learn about Python
12 2.6 Write your own functions
13 2.7 Manipulate strings
14 2.8 Write a Mad Libs program
15 Learning objectives
16 3.1 Get more context – solve problems like a programmer
17 3.2 Identify true and false statements
18 3.3 Use conditional тАЬifтАЭ statements
19 3.4 Write a number-guessing game
20 Learning objectives
21 4.1 Use a тАЬwhileтАЭ loop
22 4.2 Improve the number guessing game with тАЬwhileтАЭ loops
23 4.3 Create and manipulate lists
24 4.4 Loop over lists with тАЬforтАЭ loops
25 4.5 Write a word-guessing game
26 4.6 Get more context – clean up and test your code
27 Learning objectives
28 5.1 Get more context – discuss how to keep learning
29 5.2 Look at more data structures
30 5.3 Create list comprehensions
31 5.4 Read files
32 5.5 Write more complex functions
33 5.6 Program with classes
34 5.7 Import external libraries
35 5.8 Manage virtual environments
36 Learning objectives
37 6.1 Look at the ecosystem
38 6.2 Set up Anaconda in Jupyter
39 6.3 Import a dataset
40 6.4 Plot the data
41 6.5 Clean some data
42 Learning objectives
43 7.1 Look at the anatomy of a web app
44 7.2 Start a web app with Flask
45 7.3 Learn the basics of HTML and CSS
46 7.4 Fill in website functionality
47 7.5 Understand some JavaScript and JQuery
48 7.6 Get more context – databases and deployment
49 Introduction to Python – Summary
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