This 90-minute guided-project, "Pyspark for Data Science: Customer Churn Prediction," is a comprehensive guided-project that teaches you how to use PySpark to build a machine learning model for predicting customer churn in a Telecommunications company. This guided-project covers a range of essential tasks, including data loading, exploratory data analysis, data preprocessing, feature preparation, model training, evaluation, and deployment, all using Pyspark. We are going to use our machine learning model to identify the factors that contribute to customer churn, providing actionable insights to the company to reduce churn and increase customer retention. Throughout the guided-project, you'll gain hands-on experience with different steps required to create a machine learning model in Pyspark, giving you the tools to deliver an AI-driven solution for customer churn. Prerequisites for this guided-project include basic knowledge of Machine Learning and Decision Trees, as well as familiarity with Python programming concepts such as loops, if statements, and lists.
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What you'll learn
Use AI driven solution to solve a business problem
Build a machine learning model with PySpark
Apply data cleansing activities using PySpark
Skills you'll practice
Details to know
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- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies
About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Set up the project environment (11 min)
Exploratory Data Analysis Part I - Numerical Columns (10 min)
Exploratory Data Analysis Part II - Categorical Columns (10 min)
Preprocess and clean data (7 min)
Demonstrate your understanding of Data Exploration and Preprocessing (5 min)
Prepare the input data for your model Part I - Numerical Features (6 min)
Prepare the input data for your model Part II - Categorical Features (10 min)
Train your decision tree (9 min)
Evaluate your model (11 min)
Deploy your model (6 min)
Challenge Activity: Employee Attrition Prediction (6 min)
Recommended experience
Basic knowledge of Machine Learning and Decision Trees, Python programming language (basic concepts such as: loops, if statements and lists)
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.