This course is part of multiple programs.
Instructors: Azim Hirjani
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
266,196 already enrolled
Included with 
(4,598 reviews)
Recommended experience
Intermediate level
You should have completed the prerequisite courses needed or have proficient knowledge in working with Python and Data.
(4,598 reviews)
Recommended experience
Intermediate level
You should have completed the prerequisite courses needed or have proficient knowledge in working with Python and Data.
Play the role of a Data Scientist / Data Analyst working on a real project.
Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.
Apply Python fundamentals, Python data structures, and working with data in Python.
Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.
Add to your LinkedIn profile
2 quizzes
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course primarily involves completing a project in which you will assume the role of a Data Scientist or a Data Analyst and be provided with a real-world data set and a real-world inspired scenario to identify patterns and trends.
You will perform specific data science and data analytics tasks such as extracting data, web scraping, visualizing data and creating a dashboard. This project will showcase your proficiency with Python and using libraries such as Pandas and Beautiful Soup within a Jupyter Notebook. Upon completion you will have an impressive project to add to your job portfolio. PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much instructional content. It is intended for you to apply prior Python knowledge.
In this module, you will demonstrate your skills in Python - the language of choice for Data Science and Data Analysis. You will apply Python fundamentals, Python data structures, and work with data in Python. By working on a real project, you will model a Data Scientist or Data Analyst's role, and build a dashboard using Python and popular Python libraries using Jupyter notebook.
2 videos8 readings2 quizzes1 peer review5 app items5 plugins
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
At IBM, we know how rapidly tech evolves and recognize the crucial need for businesses and professionals to build job-ready, hands-on skills quickly. As a market-leading tech innovator, we’re committed to helping you thrive in this dynamic landscape. Through IBM Skills Network, our expertly designed training programs in AI, software development, cybersecurity, data science, business management, and more, provide the essential skills you need to secure your first job, advance your career, or drive business success. Whether you’re upskilling yourself or your team, our courses, Specializations, and Professional Certificates build the technical expertise that ensures you, and your organization, excel in a competitive world.
Course
Fractal Analytics
Course
University of Michigan
Course
4,598 reviews
71.64%
16.78%
5.76%
2.45%
3.34%
Showing 3 of 4598
Reviewed on Dec 31, 2022
Material Covered was very good and meaningful in developing knowledge and skills. Unfortunately a significant amount of time was required accessing the tools to complete the work.
Reviewed on Nov 30, 2021
It is the most applicable course on python anyone could participate in. I am glad I came across this amazing course. Kudos to the producers and thanks to every one on them.
Reviewed on Oct 6, 2021
Best course so far, under the IBM Data Science professional certificate program. It is heavy on the practical side, which is a good thing as it gives the person a more hands-on experience.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Financial aid available,
Learn on your own time from top universities and businesses.
Already on Coursera?
I accept Coursera's Terms of Use and Privacy Notice. Having trouble logging in? Learner help center
This site is protected by reCAPTCHA Enterprise and the Google Privacy Policy and Terms of Service apply.
