Python Project for Data Science

Python Project for Data Science

This course is part of multiple programs.

Instructors: Azim Hirjani

334,275 already enrolled

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2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

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.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

2 assignments

Taught in English

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This course is available as part of

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Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

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’ll get started with the course and build foundational skills in data collection using Python. You’ll explore the basics of web scraping, learn how to work with HTML content, and practice extracting data both through Python libraries and web scraping techniques. You will then apply your skills in a guided practice project focused on extracting stock data from various sources.

What's included

2 videos6 readings2 assignments3 app items

2 videosTotal 10 minutes

HTML for Webscraping5 minutes
Webscraping5 minutes

6 readingsTotal 41 minutes

Course Introduction5 minutes
Web Scraping: A Key Tool in Data Science8 minutes
Web Scraping Tables using Pandas8 minutes
Stock shares 5 minutes
The yfinance Python library5 minutes
Optional: Gamestop stock vs Tesla10 minutes

2 assignmentsTotal 35 minutes

Extracting Stock Data Using a Python Library20 minutes
Extracting Stock Data Using a Web Scraping15 minutes

3 app itemsTotal 165 minutes

Intro to Web Scraping Using BeautifulSoup60 minutes
Extracting Stock Data Using a Python Library60 minutes
Extracting Stock Data Using Web Scraping45 minutes

This module focuses on acquiring and interpreting stock market information. Learners will practice extracting key stock data from datasets and visualizing it using graphs. By the end of the module, they will understand how to analyze stock trends and make data-driven decisions based on visual insights.

What's included

4 readings1 peer review2 app items

4 readingsTotal 11 minutes

Project Overview5 minutes
Final Submission Guidelines and Deliverables2 minutes
Congratulations & Next Steps2 minutes
Thanks from the Course Team2 minutes

1 peer reviewTotal 60 minutes

Option 2: Peer Graded - Final Project Submission and Evaluation60 minutes

2 app itemsTotal 120 minutes

Option 1: AI Graded - Final Project: Submission and Evaluation60 minutes
Hands-on Lab: Analyzing Historical Stock/Revenue Data and Building a Dashboard60 minutes

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Instructors

Azim Hirjani

IBM

1 Course334,275 learners

Offered by

IBM

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