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2.5 Hours of Video Instruction
Explore Python's capabilities for Data Science and Machine Learning, the topics of greatest import these days in the tech world.
Python has risen to popularity as one of the most versatile and beginner-friendly programming languages. Its simplicity, readability, and extensive libraries make it a powerful language for a wide variety of different domains. It's widely used in web development, data analysis, scientific computing, artificial intelligence, and automation. Python's versatility and large community support make it an excellent language to kickstart your programming journey. This course offers a hands-on approach to building your Python skills through a series of practical projects from scratch. Hone your expertise in areas such as data analysis, machine learning, web scraping, and more.
Related Learning:
Watch and learn from Shauns other videos:
https://learning.oreilly.com/course/functional-programming-projects/9780138318772/
Skill Level:
Intermediate-Advanced
What You Will Learn:
Each project will include some different aspect of data science/ machine learning with Python that it will be both accessible and engaging while you advance your skill set.
Who Should Take This Course:
Job titles:
Software developer, Data analyst/scientist, Machine Learning Engineer, Web Developer, DevOps Engineer.
Course Requirements:
Prerequisites:
Python experience and app development background
About Pearson Video Training:
Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.
Introduction
Lesson 1: Manipulate and Visualize Data in Jupyter
1.1 Get started with Jupyter Notebooks
1.2 Load data into Jupyter
1.3 Manipulate data with Pandas
1.4 Visualize data
Lesson 2: Perform Sentiment Analysis
2.1 Learn about Sentiment Analysis tools in Python
2.2 Learn the basics of NLTK
2.3 Incorporate Sentiment Analysis into an application
2.4 Analyze with real-world data
Lesson 3: Work with Image Recognition
3.1 Learn about image recognition tools in Python
3.2 Learn the basics of OpenCV
3.3 Incorporate image recognition into an application
Lesson 4: Scrape Data from the Internet
4.1 Learn about web-scraping tools in Python
4.2 Learn the basics of the Beautiful Soup Library
4.3 Format and use scraped data
4.4 Modify web-scraping logic for other websites
Summary