Python Data Science: Data Prep & EDA with Python
Why take this course?
🚀 Course Headline:
🎓 Master Data Science in Python: Data Preparation & Exploratory Data Analysis (EDA)
Welcome to the World of Data Science!
This is not just another online course; it's a hands-on, project-based learning journey designed to help you master the core building blocks of Python for data science. 🐍📊
What You'll Learn:
In this comprehensive course, we'll cover everything from the fundamentals of data science and machine learning to advanced techniques in data preparation and exploratory data analysis using Python and Pandas.
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Intro to Data Science: We'll kick things off by diving into the field of data science, essential skills, and each phase of the data science workflow. 🧠
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Scoping a Project: Learn how to properly scope your data science projects, brainstorm problems and solutions, and set clear goals for success. 🎯
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Gathering Data: From Excel spreadsheets to SQL databases, we'll show you how to read flat files into a Pandas DataFrame and handle various data sources and formats. 📚
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Cleaning Data: Identify and fix common data issues such as missing values, duplicates, and outliers, and learn to create new columns for analysis. 🛠️
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Exploratory Data Analysis (EDA): Discover hidden insights in your datasets by sorting, filtering, grouping, and visualizing data with scatterplots, histograms, and more. 📈
Your Mission:
Throughout the course, you'll step into the shoes of a Jr. Data Scientist for Maven Music, a streaming service facing challenges with customer churn. Your mission? Use Python to gather, clean, and explore their data to uncover actionable insights. 🎵🔍
Mid-Course & Final Projects:
To solidify your learning, you'll embark on two exciting projects:
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MID-COURSE PROJECT: Put your skills to the test with a brand-new dataset containing Rotten Tomatoes movie ratings. 🎥✨
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FINAL COURSE PROJECT: Gather, clean, explore, and prepare multiple datasets for Maven Music, showcasing all you've learned throughout the course. 🌟📊
What You Get with LIFETIME Access:
Jump into this interactive learning experience with immediate access to:
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8.5 hours of high-quality video lessons. 🎥
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16 homework assignments to reinforce your knowledge.
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7 quizzes to test your understanding.
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2 projects to apply what you've learned (1 mid-course, 1 final).
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A comprehensive ebook (190+ pages) on Data Science in Python: Data Prep & EDA. 📚
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Downloadable project files & solutions. 💾
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Access to an expert support and Q&A forum. 🗣️
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A 30-day Udemy satisfaction guarantee. ✅
Who is this for?
If you're an aspiring data scientist eager to get an introduction to the world of machine learning with Python, this is your course. 🚀
Whether you're a complete beginner or looking to sharpen your skills, this course offers something for everyone. 🕸️👩💻
-Alice Zhao🌟 (Python Expert & Data Science Instructor, Maven Analytics)
Happy learning, and we can't wait to see you inside the course! 🎉 Join today and embark on a transformative journey into the heart of data science with Python.
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Comidoc Review
Our Verdict
Python Data Science: Data Prep & EDA with Python is a standout Udemy course that empowers learners to understand and apply essential data preparation and exploratory data analysis (EDA) techniques using Python. The course's well-structured design, high-quality resources, and engaging teaching style distinguish it from typical college courses, ensuring an efficient and effective learning experience. While certain users might appreciate a more thorough exploration of specific topics or advanced mathematical concepts, the course remains focused on providing user level knowledge and domain expertise that data professionals require in real-life applications.
What We Liked
- Comprehensive coverage of data preparation and exploratory data analysis (EDA) techniques using Python
- Well-structured and easy-to-follow course with PowerPoint slides, demo python notebooks, and assignments for self-study
- Incorporates domain knowledge, mathematical processes, and data science project life cycle into the curriculum
- Effective teaching ability that surpasses typical college courses in quality
Potential Drawbacks
- Minor issue: some content may seem repetitive if you already have a basic understanding of Python or Pandas
- A few users mentioned that the instructor's knowledge on select topics could be more in-depth
- The course does not cover advanced mathematics and coding concepts, focusing instead on user level knowledge