Transform your data science capabilities with the "Probability Theory and Regression for Predictive Analytics" course. This program is designed to provide essential mathematical and statistical skills necessary for predictive modeling and data analysis. Dive into probability concepts, including conditional probability, Bayes’ Theorem, and various probability distributions. Further, apply regression techniques to enhance your ability to predict and interpret data trends.


您将学到什么
Calculate conditional probabilities and apply Bayes' Theorem for data inference.
Understand and apply various probability distributions for statistical analysis.
Perform ordinary least squares regression to fit linear models to data.
Analyze datasets using advanced regression techniques in Python.
您将获得的技能
- Probability & Statistics
- Machine Learning
- Bayesian Statistics
- Statistical Methods
- Data Science
- Regression Analysis
- Statistical Inference
- Probability
- Data Analysis
- Applied Mathematics
- Statistical Machine Learning
- Python Programming
- Algorithms
- Statistical Modeling
- Predictive Analytics
- Feature Engineering
- Statistical Analysis
- Probability Distribution
要了解的详细信息

添加到您的领英档案
August 2025
4 项作业
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- 获得可共享的职业证书

该课程共有2个模块
This module will introduce basic concepts from probability theory.
涵盖的内容
14个视频1篇阅读材料2个作业1个编程作业1个插件
This module covers essential concepts in regression analysis, from basics like covariance and correlation to advanced topics such as multicollinearity, interaction effects, Lasso regression, and logistic regression. It provides tools for interpreting, diagnosing, and improving regression models.
涵盖的内容
9个视频1篇阅读材料2个作业1个编程作业
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
攻读学位
课程 是 University of Pittsburgh提供的以下学位课程的一部分。如果您被录取并注册,您已完成的课程可计入您的学位学习,您的学习进度也可随之转移。
位教师

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常见问题
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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提供助学金,