Description
Data Science in Python: Data Prep & EDA course. This is a hands-on, project-based course designed to help you master the core building blocks of Python for data science. We begin by introducing the fields of data science and machine learning, discuss the difference between supervised and unsupervised learning, and review the data science workflow we will use throughout the course. From there we move on to the data preparation and EDA steps in the workflow. You will learn how to conceptualize a data science project, use pandas to collect data from multiple sources and address common data cleaning issues, and perform exploratory data analysis using techniques such as filtering, clustering, and visualize the data. During the course, you will play the role of a junior data scientist for Maven Music, a streaming service struggling with customer churn. Using the skills you learn throughout the course, you’ll use Python to collect, clean, and explore data to provide insights about their customers. Last but not least, you’ll practice preparing data for machine learning models by joining multiple tables, setting row granularity, and engineering useful fields and attributes. Summary of the course:
- An introduction to data science
- Introduce the field of data science, review essential skills, and introduce each step of the data science workflow
- Scope of a project
- Review the process of scoping a data science project, including brainstorming problems and solutions, selecting techniques, and setting clear goals.
- Data collection
- Read flat files into a Pandas DataFrame in Python and explore common data sources and formats, including Excel spreadsheets and SQL databases.
- Delete data
- Identify and convert data types, find and fix common data problems such as missing values, duplicates, and outliers, and create new columns for analysis.
- Exploratory data analysis
- Explore datasets to discover insights by sorting, filtering, and grouping data, then visualize them using common chart types such as scatter charts and histograms.
- Midterm project
- Test your skills by cleaning, exploring, and visualizing data from a brand new dataset containing Rotten Tomatoes movie ratings.
- Preparing for modeling
- Structure your data ready for machine learning models by creating non-null numeric tables and engineering new features.
- Final course project
- Apply all the skills learned throughout the course by collecting, cleaning, exploring, and preparing multiple datasets for Maven Music.
If you are an aspiring data scientist looking for an introduction to the world of machine learning with Python, this course is for you.
What you will learn in Data Science in Python: Data Prep & EDA course
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Master the basic building blocks of Python for data science before using machine learning algorithms
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Expand data science projects by clearly defining the goals, techniques, and data sources needed for your analysis
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Import and export flat files, Excel workbooks and SQL database tables using Pandas
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Clean up data by converting data types, addressing common data issues, and creating new columns for analysis
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Perform exploratory data analysis (EDA) by sorting, filtering, grouping, and visualizing data to discover patterns and insights.
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Prepare data for machine learning models by joining tables, aggregating rows, and applying feature engineering techniques.
This course is suitable for people who
- Data scientists seek to learn core techniques and best practices for data preparation and exploratory data analysis.
- Python users who want to build the core skills needed before using artificial intelligence and machine learning models
- Data analysts or BI experts are looking to transition into a data science role
- Anyone interested in learning one of the most popular open source programming languages in the world
Data Science in Python: Data Prep & EDA course specifications
- Publisher: Udemy
- teacher: Maven Analytics
- Training level: beginner to advanced
- Training duration: 8 hours and 41 minutes
- Number of courses: 180
Course topics Data Science in Python: Data Prep & EDA on 9/2023
Data Science in Python course prerequisites: Data Prep & EDA
- Jupyter Notebooks (free download, we’ll walk through the installation)
- Familiarity with basic Python and Pandas is recommended, but not required
Course images
Sample video of the course
Installation guide
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Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
2.7 GB
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