Python Data Science: Data Prep & EDA with Python — 93% Off Coupon

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

⭐ 4.7 out of 5 Rating (11,271 students) Created by Maven Analytics, Alice Zhao Updated: April 22, 2026 🌐 English

Key Takeaways

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Course Title: Python Data Science: Data Prep & EDA with Python

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Provider: Udemy (Listed via CoursesWyn)

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Instructor: Maven Analytics, Alice Zhao

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Coupon Verified On: April 22, 2026

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Difficulty Level: All Levels

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Category: Development

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Subcategory: Data Science

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Duration: 8h 30m of on-demand video

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Language: English

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Access: Lifetime access to all course lectures and updates

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Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements

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Top Learning Outcomes: 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

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Prerequisites: Jupyter Notebooks (free download, we'll walk through the install) · Familiarity with base Python and Pandas is recommended, but not required

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Price: $11.99 with coupon / Regular Udemy price: $169.99. Applying this coupon saves you $158.00 (93% OFF).

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Coupon: Click REDEEM COUPON below to apply discount

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What You'll Learn

The following technical skills represent the core curriculum targets for learners enrolling in this verified program today.

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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Requirements

Please review the following prerequisites to ensure you have the necessary tools and foundational knowledge for this training.

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Jupyter Notebooks (free download, we'll walk through the install)

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Familiarity with base Python and Pandas is recommended, but not required

About This Course

Comprehensive curriculum analysis and educational value proposition from the official provider library hubs.

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

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:

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Meet Your Instructor

Academic background and professional track record of the subject matter expert responsible for this curriculum.

Maven Analytics, Alice Zhao

Verified Architect

A global leader with specialized excellence in Development. Instructors are vetted for curriculum quality, responsiveness, and consistent student success across the Udemy platform.

4.8 / 5.0

Instructor Rating

94% +

Success Rate

Course Comparison

Market-relative value analysis comparing this verified instructor deal against professional subscription and retail averages.

Feature Benchmarks	This Verified Offer	Global Standard
Cost Verification	FREE (100% Validated)	Fixed Subscription Fee
Enrollment Type	Professional Lifetime Access	Limited Time Ownership
Certification Award	Included with Access Code	Required Add-on Fee

Expert Review

Andrew Derek

Lead Course Analyst, CoursesWyn

"After auditing the curriculum depth and verifying the live access protocol, Python Data Science: Data Prep & EDA with Python stands as an essential career asset. For a verified cost of $0, the return-on-learning ratio far exceeds commercial alternatives."

✅ Strategic Advantages

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Official Certificate: Credential generated at no cost.
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Mobile Friendly: Full access via smart TV & mobile.
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Expert Pacing: Modular design for professional schedules.

❌ Considerations

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Technical Depth: Requires focused 10+ hours study.
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Tool Prep: Certain labs require proprietary software setups.

Verification Outcome: Exceptional Academic Value

Course Rating

Collective learner data and performance analytics based on verified alumni feedback loops and technical graduation audits.

4.7

★★★★★

Verified Excellence

5 Stars

88%

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Frequently Asked Questions

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Andrew Derek

Expert Reviewer

Andrew Derek is a lead editor and course analyst at CoursesWyn with over 8 years of experience in online education and digital marketing. He meticulously audits every Udemy coupon and course syllabus to ensure students get the highest quality learning materials at the best possible price.

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