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Python for Data Science Project

Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

This mini-course is intended for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python.

This course is part of the IBM Data Science Professional Certificate and the IBM Data Analytics Professional Certificate.

What you'll learn

Demonstrate your Python skills for solving Data Science challenges.
Scrape data from web pages using the Beautiful Soup library.
Extract and display data using Python libraries such as Pandas, Numpy and yfinance.
Create a dashboard that shows key performance indicators from a specific data set.

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What's inside

Learning objectives

Demonstrate your python skills for solving data science challenges.
Scrape data from web pages using the beautiful soup library.

Extract and display data using python libraries such as pandas, numpy and yfinance.
Create a dashboard that shows key performance indicators from a specific data set.

Demonstrate your python skills for solving data science challenges.
Scrape data from web pages using the beautiful soup library.
Extract and display data using python libraries such as pandas, numpy and yfinance.
Create a dashboard that shows key performance indicators from a specific data set.

Syllabus

Module 1 - Intro to Web Scraping (optional)

Module 2 - Final Project: Analyzing Stock Performance and Building a Dashboard

Peer assignment

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops Python skills for Data Science, a field in demand in industry

Teaches data scraping using the Beautiful Soup library, a valuable skill for extracting data from the web

Introduces Python libraries such as Pandas, Numpy, and yfinance for data analysis and visualization

Provides a hands-on project to create a dashboard from a specific data set, reinforcing learning and practical application

Requires learners to have foundational Python skills, which may be a barrier for absolute beginners

Intended for learners with an interest in Data Science and Python programming

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python for Data Science Project with these activities:

Python Resources Compilation

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Create a curated list of useful Python resources, including online courses, tutorials, documentation, and community forums.

Browse courses on Python

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Gather resources from various sources such as the official Python website, Stack Overflow, and online learning platforms.
Organize the resources into relevant categories, e.g., beginner-friendly tutorials, advanced concepts.
Share your compilation with other learners or as a reference for your own learning journey.

Python Basics Refresher

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Brush up on Python basics, such as data types, variables, and control flow, to enhance your understanding of the course material.

Browse courses on Python

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Review online tutorials or documentation on Python fundamentals.
Practice writing simple Python programs to reinforce your understanding.

Python for Data Analysis, 2nd Edition by Wes McKinney

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Review this book to advance your understanding of Python programming and data analysis techniques.

View Python for Data Analysis: Data Wrangling with... on Amazon

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Four other activities

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Data Cleaning Exercises

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Complete these exercises to become more proficient in data cleaning and get more familiar with your dataset.

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Import your data into a Python environment.
Explore your data and identify missing values, outliers, and inconsistencies.
Clean and transform your data using Python libraries such as NumPy and Pandas.
Check the quality of your cleaned data and make any necessary adjustments.

Study Group Discussions

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Join a study group on a regular basis to discuss course topics, share knowledge, and work through problems together.

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Find or create a study group with fellow learners of this course.
Set regular meeting times and prepare topics for discussion.
Actively participate in discussions and ask questions.
Share resources and collaborate on assignments.

Analyzing a Real-World Dataset

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Work on a project to gain hands-on experience with Python libraries and data analysis techniques by applying them to a real-world dataset.

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Choose a dataset of interest.
Clean and preprocess the data.
Exploratory Data Analysis: Summarize and visualize your data to gain insights.
Model Building: Train a simple model to make predictions or solve a business problem.
Evaluate your results and improve your model.

Stock Market Dashboard

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Create an interactive stock market dashboard using the skills you learned in this course to monitor stock performance and make informed decisions.

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Gather stock data using web scraping or an API.
Clean and process the data to calculate key performance indicators (KPIs) such as stock prices, moving averages, and volatility.
Visualize the data using Python libraries like Matplotlib or Plotly to create interactive charts and graphs.
Deploy your dashboard online or share it with others.

Career center

Learners who complete Python for Data Science Project will develop knowledge and skills that may be useful to these careers:

Web Developer

Web Developers use their skills to build and design websites and web applications. This course may be useful for aspiring Web Developers because it teaches how to scrape data from web pages using Python. Data scraping is a critical skill for Web Developers.

See salaries and explore the career path for Web Developer

Data Visualization Specialist

Data Visualization Specialists use their skills to create visual representations of data. This course may be useful for aspiring Data Visualization Specialists because it teaches how to use Python to create dashboards. Dashboards are a common data visualization tool.

See salaries and explore the career path for Data Visualization Specialist

Data Scientist

Data Scientists use their skills to research and analyze data to solve complex business problems. This course may be useful for aspiring Data Scientists because it teaches how to use Python in web scraping, data extraction, and dashboard creation. Data Scientists regularly use these techniques in the course of their work.

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Operations Research Analyst

Operations Research Analysts use their skills to analyze data to improve efficiency and productivity. This course may be useful for aspiring Operations Research Analysts because it teaches the fundamentals of data analysis using Python.

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Statistician

Statisticians use their skills to analyze data to understand patterns and trends. This course may be useful for aspiring Statisticians because it teaches the fundamentals of data analysis using Python.

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Financial Analyst

Financial Analysts use their skills to analyze data to make investment decisions. This course may be useful for aspiring Financial Analysts because it teaches the fundamentals of data analysis using Python. Data analysis skills are crucial for Financial Analysts.

See salaries and explore the career path for Financial Analyst

Machine Learning Engineer

Machine Learning Engineers use their skills to build and maintain machine learning models. This course may be helpful for aspiring Machine Learning Engineers because it teaches the fundamentals of data analysis using Python. Data analysis skills are crucial for Machine Learning Engineers.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

Quantitative Analysts use their skills to analyze data to make investment decisions. This course may be useful for aspiring Quantitative Analysts because it teaches the fundamentals of data analysis using Python. Data analysis skills are crucial for Quantitative Analysts.

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Market Researcher

Market Researchers use their skills to collect and analyze data to understand consumer behavior. This course may be useful for aspiring Market Researchers because it teaches the fundamentals of data analysis using Python.

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Data Analyst

Data Analysts use data to identify trends and patterns that can help organizations make better decisions. This course may be useful for aspiring Data Analysts because it teaches the fundamentals of data analysis using Python.

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Business Analyst

Business Analysts use their skills to analyze data to help businesses make better decisions. This course may be useful for aspiring Business Analysts because it teaches the fundamentals of data analysis using Python. Data analysis skills are crucial for Business Analysts.

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Data Engineer

Data Engineers design, develop, and maintain data pipelines and infrastructure. This course may be useful for aspiring Data Engineers because it teaches how to use Python in data extraction and dashboard creation. Data Engineers need to be able to use Python to perform these tasks.

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Software Engineer

Software Engineers design, develop, and maintain software applications. Those interested in becoming Software Engineers may find the Python skills taught in this course helpful. Python is one of the most popular programming languages used in software development.

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Product Manager

Product Managers use their skills to manage the development and launch of new products. This course may be useful for aspiring Product Managers because it teaches how to use data to make better decisions. Product Managers rely heavily on data analysis.

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Consultant

Consultants use their skills to help businesses solve problems and improve performance. This course may be useful for aspiring Consultants because it helps build a foundation in data analysis and dashboard creation. These skills are valuable for Consultants.

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Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python for Data Science Project.

Machine Learning Con Pytorch Y Scikit Lean

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Provides a comprehensive overview of machine learning using Python. It covers topics such as supervised learning, unsupervised learning, and deep learning. It valuable reference for anyone looking to use Python for machine learning.

Python for Data Science Project

What you'll learn

What's inside

Learning objectives

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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