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⇱ Skill Up with Python: Data Science and Machine Learning Recipes | Coursera

Skill Up with Python: Data Science and Machine Learning Recipes

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Skill Up with Python: Data Science and Machine Learning Recipes

Instructor: Pearson

Included with

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Perform Sentiment Analysis on real-world text

  • Work with Image Recognition Tools

  • Scrape Basic Data from Websites

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments

Taught in English

There is 1 module in this course

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.

This module introduces essential Python tools and techniques for data science and machine learning through hands-on projects. Learners will manipulate and visualize data in Jupyter Notebooks, perform sentiment analysis with NLTK, recognize images using OpenCV, and scrape web data with Beautiful Soup. Each lesson builds practical skills for real-world applications, helping students create portfolio-ready projects and prepare for careers in data science and machine learning.

What's included

21 videos5 assignments

21 videos•Total 141 minutes
  • Introduction•3 minutes
  • Learning objectives•1 minute
  • Get started with Jupyter Notebooks•12 minutes
  • Load data into Jupyter•11 minutes
  • Manipulate data with Pandas•10 minutes
  • Visualize data•13 minutes
  • Learning objectives•1 minute
  • Learn about Sentiment Analysis Tools in Python•4 minutes
  • Learn the basics of NLTK•9 minutes
  • Incorporate Sentiment Analysis into an application•12 minutes
  • Analyze with real-world data•15 minutes
  • Learning objectives•1 minute
  • Learn about Image Recognition tools in Python•2 minutes
  • Learn the basics of OpenCV•9 minutes
  • Incorporate image recognition into an application•8 minutes
  • Learning objectives•1 minute
  • Learn about web-scraping tools in Python•5 minutes
  • Learn the basics of the Beautiful Soup Library•7 minutes
  • Format and use scraped data•8 minutes
  • Modify web-scraping logic for other websites•9 minutes
  • Skill Up with Python: Summary•1 minute
5 assignments•Total 150 minutes
  • Manipulate and Visualize Data in Jupyter Quiz•30 minutes
  • Perform Sentiment Analysis Quiz•30 minutes
  • Work with Image Recognition Quiz•30 minutes
  • Scrape Data from the Internet Quiz•30 minutes
  • End of Course Assessment•30 minutes

Instructor

Pearson
268 Courses•65,339 learners

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Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,