MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 20 lectures (1h 53m) | Size: 1.96 GB
Be Scalable To Learn First Step In Networking Automation from zero without any Background in Python

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 9 Lessons (58m) | Size: 111.8 MB
Python 3.10 is out! Volunteers have been working on the new version since May 2020 to bring you a better, faster, and more secure Python. As of October 4, 2021, the first official version is available.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 39m | Size: 484.8 MB
Python and R are common programming languages used when working with data. Each language is powerful in its own way; however, it's important that you select the language that will best help you achieve your end result. In this course, data scientist and coding instructor Lavanya Vijayan helps you make this choice, sharing important considerations for using each language in various circumstances. Lavanya starts by going over the background of both languages, as well as the strengths and disadvantages of each in different scenarios. She then walks through the process of working on a data science project and how you'd handle the data at various stages using Python and R. Lavanya then covers how to analyze data using both languages. She rounds out the course by discussing the use cases that play to each language's strengths. By the end of this training, you'll have the essential information you need to determine whether Python or R is right for you.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 33m | Size: 409.4 MB
Python and javascript are two of the most popular programming languages used by developers, analysts, and data scientists alike. But how do you know which language to use for specific projects or tasks? In this course, longtime instructor and software engineer Julie Nisbet answers this question and provides you with the tools you need to decide between these languages when approaching different projects. Julie starts by exploring the history of each language and how they operate. She then discusses key considerations when picking between each language for a project or task. Julie continues by reviewing key differences between the two programming languages, and closes by exploring various use cases for Python and javascript. Upon completing this course, you'll feel prepared to determine whether Python or javascript is best for you based on the project at hand.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 29m | Size: 350.3 MB
As Python has risen in popularity, there are many tools and repositories that have also become increasingly important. Of the many that are available, Jupyter and PyCharm have emerged as leading tools. In this course, software engineer and instructor Sam Pettus provides you with the baseline knowledge you need to work effectively with both Jupyter and PyCharm, as well as determine which option works best for you. Sam begins by detailing the difference between integrated development environments (IDEs) and open-source web applications, as well as how each of these tools function. Sam then walks through the key differences between each tool when working on a data science project, including topics such as debugging and integrating data. He then goes over the user profiles that most commonly leverage each program, giving you the ability to make a decision between the two depending on the project or task at hand. After watching this course, you'll be familiar with the pros, cons, and use cases for each programming tool.

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 43m | Size: 231.8 MB
You've probably heard about machine learning before, but have you ever wondered what that term really means? How does a machine learn? Have you thought about building a machine learning model, but didn't know where to start? In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python.

Linkedin Learning - Python Tools: Jupyter vs. PyCharm-XQZT
English | Size: 375.13 MB
Category: Tutorial

Manning - Constraint-satisfaction Problems in Python-iLLiTERATE
English | Size: 3.50 GB
Category: Tutorial