Python Project for Data Science

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Python Project for Data Science

This course is part of multiple programs.

Instructors: Azim Hirjani +1 more

321,318 already enrolled

Included with

2 modules

Gain insight into a topic and learn the fundamentals.

4,863 reviews

Intermediate level

Recommended experience

Flexible schedule

7 hours to complete

Learn at your own pace

91%

Most learners liked this course

2 modules

Gain insight into a topic and learn the fundamentals.

4,863 reviews

Intermediate level

Recommended experience

Flexible schedule

7 hours to complete

Learn at your own pace

91%

Most learners liked this course

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

Category: Data Presentation
Category: Data Wrangling
Category: Data Visualization
Category: Web Scraping
Category: Graphing
Category: Data Science
Category: Analytical Skills
Category: Data Collection
Category: Data Analysis
Category: Data Visualization Software

Tools you'll learn

Category: Python Programming
Category: Pandas (Python Package)
Category: Dashboard
Category: Jupyter

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

2 assignments

Taught in English

Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

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 videos4 readings2 assignments3 app items3 plugins

2 videos Total 10 minutes

HTML for Webscraping 5 minutes
Webscraping 5 minutes

4 readings Total 15 minutes

Course Introduction 5 minutes
Pre-requsite Web Scraping 0 minutes
Stock shares 5 minutes
Optional: Gamestop stock vs Tesla 5 minutes

2 assignments Total 30 minutes

Extracting Stock Data Using a Python Library 15 minutes
Extracting Stock Data Using a Web Scraping 15 minutes

3 app items Total 165 minutes

Intro to Web Scraping Using BeautifulSoup 60 minutes
Extracting Stock Data Using a Python Library 60 minutes
Extracting Stock Data Using Web Scraping 45 minutes

3 plugins Total 13 minutes

Reading: Web Scraping - A Key Tool in Data Science 5 minutes
Reading: Web Scraping Tables using Pandas 5 minutes
Reading: yfinance Library 3 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

3 readings1 peer review2 app items1 plugin

3 readings Total 9 minutes

Project Overview 5 minutes
Congratulations & Next Steps 2 minutes
Thanks from the Course Team 2 minutes

1 peer review Total 60 minutes

Option 2: Peer Graded - Final Project Submission and Evaluation 60 minutes

2 app items Total 120 minutes

Hands-on Lab: Analyzing Historical Stock/Revenue Data and Building a Dashboard 60 minutes
Option 1: AI Graded - Final Project: Submission and Evaluation 60 minutes

1 plugin Total 2 minutes

Reading: Final Submission Guidelines and Deliverables 2 minutes

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Instructors

Instructor ratings

(1,235 ratings)

Azim Hirjani

IBM

1 Course 321,318 learners

Offered by

IBM

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Showing 3 of 4863

Reviewed on Dec 30, 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 Feb 3, 2022

The peer-review is a headache.

Reviewed on Sep 13, 2022

It was a great and informative course. I just hope further editions on this course can be a bit more detailed escpecially in explaining terms in the labs. Thank you for a well -put-together course.

Frequently asked questions

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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.