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Python Data Science: Data Prep & EDA with Python (Udemy.com)

Learn Python + Pandas for data cleaning, profiling & EDA, and prep data for machine learning & data science with Python

Created by: Maven Analytics

Last updated August 2026

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What you will learn

  • Master the core building blocks of Python for data science BEFORE applying machine learning algorithms
  • Scope data science projects by clearly defining the goals, techniques, and data sources needed for your analysis
  • Import and export flat files, Excel workbooks, and SQL database tables using Pandas
  • Clean data by converting data types, handling common data issues, and creating new columns for analysis
  • Perform exploratory data analysis (EDA) by sorting, filtering, grouping, and visualizing data to discover patterns and insights
  • Prepare data for machine learning models by joining tables, aggregating rows, and applying feature engineering techniques

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Course Description

This is a hands-on, project-based course designed to help you master the core building blocks of Python for data science and machine learning.


We'll start by introducing the fields of data science and machine learning, discussing the difference between supervised and unsupervised learning, and reviewing the Python data science workflow we'll be using throughout the course.


From there we'll do a deep dive into the data prep & EDA steps of the workflow. You'll learn how to scope a data science project, use Python and Pandas to gather data from multiple sources and handle common data cleaning issues, and perform exploratory data analysis (EDA) using techniques like filtering, grouping, and visualizing data.


Throughout the course, you'll play the role of a Jr. Data Scientist for Maven Music, a streaming service that’s been struggling with customer churn. Using the skills you learn throughout the course, you'll use Python to gather, clean, and explore the data to provide insights about their customers.


Last but not least, you'll practice preparing data for data science and machine learning models by joining multiple tables, adjusting row granularity, and engineering useful fields and features.


COURSE OUTLINE:


  • Intro to Data Science & Machine Learning

    • Introduce the field of data science, review essential skills, and introduce each phase of the data science workflow


  • Scoping a Project

    • Review the process of scoping a data science project, including brainstorming problems and solutions, choosing techniques, and setting clear goals


  • Gathering Data

    • Read flat files into a Pandas DataFrame in Python, and review common data sources & formats, including Excel spreadsheets and SQL databases


  • Cleaning Data

    • Identify and convert data types, find and fix common data quality issues like missing values, duplicates, and outliers, and create new columns for analysis


  • Exploratory Data Analysis (EDA)

    • Explore datasets to discover insights by sorting, filtering, and grouping data, then visualize it using common chart types like scatterplots & histograms


  • MID-COURSE PROJECT

    • Put your skills to the test by cleaning, exploring, and visualizing data from a brand-new data set containing Rotten Tomatoes movie ratings


  • Preparing for Modeling

    • Structure your data so that it’s ready for machine learning models by creating a numeric, non-null table and engineering new features


  • FINAL COURSE PROJECT

    • Apply all the skills learned throughout the course by gathering, cleaning, exploring, and preparing multiple data sets for Maven Music


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Ready to dive in? Join today and get immediate, LIFETIME access to the following:


  • 8.5 hours of high-quality video

  • 16 homework assignments

  • 7 quizzes

  • 2 projects (1 mid-course, 1 final)

  • Data Science in Python: Data Prep & EDA ebook (190+ pages)

  • Downloadable project files & solutions

  • Expert support and Q&A forum

  • 30-day Udemy satisfaction guarantee


If you're an aspiring data scientist or business intelligence professional looking for an introduction to the world of machine learning and data science with Python and Pandas, this is the course for you.


Happy learning!

-Alice Zhao (Python Expert & Data Science Instructor, Maven Analytics)


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Looking for our full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses!


See why our courses are among the TOP-RATED on Udemy:


"Some of the BEST courses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen!" Russ C.


"This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier!" Tatsiana M.


"Maven Analytics should become the new standard for all courses taught on Udemy!" Jonah M.

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Instructor Details

Maven Analytics

Maven Analytics is an award-winning platform where individuals and teams build new skills, showcase work, and connect with experts around the world.

We've helped more than 2,000,000 learners around the world build job-ready data & AI skills, master tools like Excel, SQL, Power BI, Tableau and Python, and build the foundation for successful careers.

Start learning for free!

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Reviews

4.7

2,093 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Soham Chakraborty on 6/28/2026

Exceptionally good course , for those who are venturing into the field of Data Science and Analytics. Hats Off to the Tutor. I really loved that , every section has practical demo.

By Abel Aleu Chol Garang on 3/6/2026

You have unveil the mask of not knowing how to approach data science project, I have learnt that preparation is where you can get it right or wrong. From now, you have set me on the right path to approach a project before executing any solution.

By Geraldo Tchipenda on 2/26/2026

I am extremely satisfied with this courses. Overall, this training has significantly enhanced my technical skills and positively contributed to my professional growth. I highly recommend these courses to anyone looking to build strong foundations in data analysis and data preparation for machine learning. Thank you

By Amit Karande on 2/21/2026

Course delivery is excellent. However, Course content is bit dated and needs refresh. for e.g. (1) get_dummies now returns boolean instead of int. (2) pd.to_datetime needs format to be speficied found a few similar gaps.

By Juan Camilo Garcia Lopez on 1/26/2026

This course has exactly what I was looking for. Most courses give the methods to handle different situations when you are working with data, but they don't specify the right way and the order to apply all these techniques to any data science project.

By Alfred TAN on 12/27/2025

Alice Zhao is easily a Top 10 instructor for Data Science on Udemy. Her course materials and code files has clarity, depth and structure. I depend on these materials as first priority to work on the Google Advanced Analytics careers certificate projects.

By Camilo Narvaez on 12/17/2025

The course was excellent, one of the best. The only shortcoming was that in some cases, particularly in the final modules, the data shown in the videos did not match the datasets provided, which made it a bit confusing to follow at times. Aside from that, it was excellent very comprehensive and extremely clear.

By Al-baraa Hegaz on 12/16/2025

You were really simple and clear in explaining and I enjoyed every moment of the cource and thanks a lot for leaving the slides to get back to it when needed that helps a lot thank you again for your clear English .

By Ogechukwu Iloanusi on 12/16/2025

Instructor is indeed an expert in the field. Excellent lectures delivery and presentations!! Precise and straight to the point. Every single second of the videos in this course is valuable!! I am happy I found this course!

By Daniel Sellers on 11/24/2025

Alice makes crystal clear the difference between supervised and unsupervised learning. The EDA section is done extremely well and is full of simple, easy understand, well thought out examples.

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Overall Score : 94 / 100