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By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python. Determining whether a player’s career will flourish or not became a science based on the player’s stats. Throughout the project, you will be able to analyze players’ stats and build your own binary classification model using Scikit-learn to predict if the NBA rookie will last for 5 years in the league if provided with some stats such as Games played, assists, steals and turnovers …. etc.
Read more
By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python. Determining whether a player’s career will flourish or not became a science based on the player’s stats. Throughout the project, you will be able to analyze players’ stats and build your own binary classification model using Scikit-learn to predict if the NBA rookie will last for 5 years in the league if provided with some stats such as Games played, assists, steals and turnovers …. etc.
Read more
By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python. Determining whether a player’s career will flourish or not became a science based on the player’s stats. Throughout the project, you will be able to analyze players’ stats and build your own binary classification model using Scikit-learn to predict if the NBA rookie will last for 5 years in the league if provided with some stats such as Games played, assists, steals and turnovers …. etc.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/hh9fvf/predict
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Syllabus
Project Overview
By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python. Determining whether a player’s career will flourish or not became a science based on the player’s stats. Throughout the project, you will be able to analyze players’ stats and build your own binary classification model using Scikit-learn to predict if the NBA rookie will last for 5 years in the league if provided with some stats such as Games played, assists, steals and turnovers …. etc.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Learns to use NumPy and Pandas libraries
Guides learners through hands-on projects
Covers topics that may be of interest to those interested in Python, programming, and data analysis
Helps students assess the longevity of NBA rookies based on their statistics
Students who have a curiosity for NBA may find this course interesting
This course may be of use to those interested in exploring data analysis for sports
Save this course
Save Predict Career Longevity for NBA Rookies using Scikit-learn to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Predict Career Longevity for NBA Rookies using Scikit-learn with these
activities:
Review statistics
Show steps
Find a refresher on statistics to prime your brain for applying data analysis in this course.
Browse courses on
Statistics
Show steps
-
Review the concept of probability distributions.
-
Take practice problems on hypothesis testing.
-
Look up regression models.
Follow a tutorial for building a binary classification model
Show steps
Build a solid foundation for this course by following a tutorial that will help you build your own model.
Browse courses on
scikit-learn
Show steps
-
Watch a video or read an article on binary classification.
-
Find a tutorial that walks you through Scikit-learn.
-
Build a model using the tutorial's dataset.
Help other learners in the course
Show steps
Reinforce your knowledge by explaining concepts to other learners in the course.
Browse courses on
Mentoring
Show steps
-
Join online forums and discussion boards.
-
Answer questions and provide support to other learners.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group to discuss NBA career longevity
Show steps
Connect with other learners to collaborate on the project and exchange ideas that might improve your understanding.
Browse courses on
Networking
Show steps
-
Find a study group that is working on similar topics.
-
Meet with the group regularly to discuss the course material and work on the project together.
Solve practice problems on career longevity prediction
Show steps
Sharpen your analytical skills by solving problems that prepare you for this project.
Browse courses on
NBA
Show steps
-
Find practice problems related to career longevity prediction.
-
Solve the problems using the methods you learned in the course.
Create a dashboard that visualizes player career longevity
Show steps
Solidify your understanding of data analysis by creating a visualization that summarizes player career longevity.
Browse courses on
Data Visualization
Show steps
-
Gather data on NBA player career longevity.
-
Choose a data visualization tool.
-
Create a dashboard that visualizes the data.
Contribute to an open-source project that predicts player career longevity
Show steps
Hone your skills in a real-world setting by contributing to a project that aligns with the course material.
Browse courses on
Open Source
Show steps
-
Find an open-source project that predicts player career longevity.
-
熟悉项目代码库。
-
Make a contribution to the project.
Review statistics
Show steps
Find a refresher on statistics to prime your brain for applying data analysis in this course.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review the concept of probability distributions.
- Take practice problems on hypothesis testing.
- Look up regression models.
Follow a tutorial for building a binary classification model
Show steps
Build a solid foundation for this course by following a tutorial that will help you build your own model.
Browse courses on
scikit-learn
Show steps
Show steps
Show steps
- Watch a video or read an article on binary classification.
- Find a tutorial that walks you through Scikit-learn.
- Build a model using the tutorial's dataset.
Help other learners in the course
Show steps
Reinforce your knowledge by explaining concepts to other learners in the course.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Join online forums and discussion boards.
- Answer questions and provide support to other learners.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group to discuss NBA career longevity
Show steps
Connect with other learners to collaborate on the project and exchange ideas that might improve your understanding.
Browse courses on
Networking
Show steps
Show steps
Show steps
- Find a study group that is working on similar topics.
- Meet with the group regularly to discuss the course material and work on the project together.
Solve practice problems on career longevity prediction
Show steps
Sharpen your analytical skills by solving problems that prepare you for this project.
Browse courses on
NBA
Show steps
Show steps
Show steps
- Find practice problems related to career longevity prediction.
- Solve the problems using the methods you learned in the course.
Create a dashboard that visualizes player career longevity
Show steps
Solidify your understanding of data analysis by creating a visualization that summarizes player career longevity.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather data on NBA player career longevity.
- Choose a data visualization tool.
- Create a dashboard that visualizes the data.
Contribute to an open-source project that predicts player career longevity
Show steps
Hone your skills in a real-world setting by contributing to a project that aligns with the course material.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find an open-source project that predicts player career longevity.
- 熟悉项目代码库。
- Make a contribution to the project.
Career center
Learners who complete Predict Career Longevity for NBA Rookies using Scikit-learn will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data scientists use their skills in data analysis, machine learning, and statistics to solve business problems. This course will help you build a foundation in data science, which is essential for this role. You will learn about different data science techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers design and implement machine learning models. This course will help you build a foundation in machine learning, which is essential for this role. You will learn about different machine learning algorithms, how to train and evaluate models, and how to deploy models to production. This course will also help you develop the programming skills needed to implement machine learning models.
Sports Analyst
Sports Analyst
Sports analysts use their skills in data analysis, statistics, and sports knowledge to analyze sports data. This course will help you build a foundation in sports analytics, which is essential for this role. You will learn about different sports analytics techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use their skills in mathematics, statistics, and computer programming to solve business problems. This course will help you build a foundation in operations research, which is essential for this role. You will learn about different operations research techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Statistician
Statistician
Statisticians use their skills in mathematics, statistics, and computer programming to collect, analyze, and interpret data. This course will help you build a foundation in statistics, which is essential for this role. You will learn about different statistical methods, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use their skills in mathematics, statistics, and computer programming to develop financial models. This course will help you build a foundation in quantitative finance, which is essential for this role. You will learn about different financial models, how to build and evaluate them, and how to use them to make investment decisions.
Data Analyst
Data Analyst
Data analysts use their skills in data mining, statistics, and predictive modeling to extract meaningful insights from data. This course will help you build a foundation in data analysis, which is essential for this role. You will learn how to clean and prepare data, perform exploratory data analysis, and build predictive models. This course will also help you develop the communication skills needed to present your findings to stakeholders.
Financial Analyst
Financial Analyst
Financial analysts use their skills in mathematics, statistics, and finance to analyze financial data. This course will help you build a foundation in financial analysis, which is essential for this role. You will learn about different financial analysis techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Data Engineer
Data Engineer
Data engineers use their skills in computer programming, data management, and cloud computing to build and manage data pipelines. This course will help you build a foundation in data engineering, which is essential for this role. You will learn about different data engineering techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Business Analyst
Business Analyst
Business analysts use their skills in data analysis, statistics, and business knowledge to improve business processes. This course will help you build a foundation in business analysis, which is essential for this role. You will learn about different business analysis techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Actuary
Actuary
Actuaries use their skills in mathematics, statistics, and finance to assess risk and develop insurance products. This course will help you build a foundation in actuarial science, which is essential for this role. You will learn about different actuarial techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Risk Manager
Risk Manager
Risk managers use their skills in mathematics, statistics, and finance to identify and manage risk. This course will help you build a foundation in risk management, which is essential for this role. You will learn about different risk management techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Biostatistician
Biostatistician
Biostatisticians use their skills in statistics, mathematics, and biology to design and analyze clinical trials. This course will help you build a foundation in biostatistics, which is essential for this role. You will learn about different statistical methods, how to apply them to clinical trials, and how to interpret the results.
Market Research Analyst
Market Research Analyst
Market research analysts use their skills in data analysis, statistics, and marketing knowledge to understand consumer behavior. This course will help you build a foundation in market research, which is essential for this role. You will learn about different market research techniques, how to apply them to real-world problems, and how to communicate your findings to stakeholders.
Software Engineer
Software Engineer
Software engineers use their skills in computer programming to design, develop, and maintain software applications. This course may be useful for this role, as it will help you build a foundation in machine learning, which is increasingly being used in software development. You will learn about different machine learning algorithms, how to train and evaluate models, and how to deploy models to production.
For more career information including salaries, visit:
OpenCourser.com/course/hh9fvf/predict
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Predict Career Longevity for NBA Rookies using Scikit-learn .
Provides an overview of machine learning techniques and their applications in sports analytics. It covers a wide range of topics, from data preprocessing to model evaluation. This book valuable resource for anyone interested in using machine learning to analyze sports data, including NBA player career longevity.
Provides an insight into the mind of one of the greatest basketball players of all time. It covers a wide range of topics, from his training regimen to his mental approach to the game. This book valuable resource for anyone interested in learning more about the Mamba Mentality.
Save
Uses data analysis to examine the relationship between player salaries and team performance in the NBA. It provides a unique perspective on the economics of the NBA and the value of different players.
Save
Provides a set of rules and tools for analyzing basketball performance. It covers a wide range of topics, from player evaluation to team strategy. This book valuable resource for anyone interested in using data analysis to improve their basketball knowledge.
Provides an annual analysis of the NBA season. It covers a wide range of topics, from player projections to team rankings. This book valuable resource for anyone interested in keeping up with the latest developments in the NBA.
Comprehensive history of basketball, from its origins to the present day. It provides a wealth of information about players, teams, and strategies. This book valuable resource for anyone interested in learning more about the history of basketball.
Provides a guide to watching basketball intelligently. It covers a wide range of topics, from player evaluation to team strategy. This book valuable resource for anyone interested in learning more about the game of basketball.
Provides a comprehensive history of the National Basketball Association (NBA). It covers the league's origins, its major events, and its most famous players. This book valuable resource for anyone interested in learning more about the history of the NBA.
Save
Provides a guide to thinking about basketball intelligently. It covers a wide range of topics, from player evaluation to team strategy. This book valuable resource for anyone interested in learning more about the game of basketball.
Save
Provides a personal account of the game of basketball. It covers a wide range of topics, from the history of the game to the lives of its players. This book valuable resource for anyone interested in learning more about the human side of basketball.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hh9fvf/predict
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Effort
1 hour
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Mohanad Ayman Affify
Language
English
Good to know
Learns to use NumPy and Pandas libraries
Guides learners through hands-on projects
Covers topics that may be of interest to those interested in Python, programming, and data analysis
Helps students assess the longevity of NBA rookies based on their statistics
Students who have a curiosity for NBA may find this course interesting
This course may be of use to those interested in exploring data analysis for sports
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