中By completing this course, learners will be able to apply Python programming to analyze datasets, construct compelling visualizations, evaluate statistical measures, and implement machine learning techniques to generate actionable insights. You will develop hands-on skills in Python scripting, create reusable libraries, build functions, and preprocess data for accurate analysis. Learners will also construct charts, scatter plots, histograms, and box plots, evaluate probabilities and hypotheses, and implement regression and optimization models using gradient descent.
Data Science with Python: Analyze & Visualize
您将学到什么
Analyze datasets with Python scripting, functions, and libraries.
Visualize data using charts, scatter plots, histograms, and box plots.
Apply ML techniques like regression and gradient descent models.
您将获得的技能
- Scripting
- Data Science
- Applied Machine Learning
- Statistical Analysis
- Data Cleansing
- Data Visualization Software
- Regression Analysis
- Machine Learning Algorithms
- Box Plots
- Matplotlib
- Programming Principles
- Histogram
- Statistical Methods
- Statistical Inference
- Scatter Plots
- Data Manipulation
- Data Analysis
- Probability & Statistics
- NumPy
- Python Programming
要了解的详细信息
可分享的证书
添加到您的领英档案
最近已更新！
October 2025
作业
14 项作业
授课语言：英语（English）
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积累特定领域的专业知识
本课程是 Python for Data Science: Real Projects & Analytics 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有4个模块
This module introduces learners to the core principles of Python programming and its application in data science. Students will explore the Python environment, understand essential coding structures, and build reusable functions and libraries. By the end of this module, learners will have the programming foundation necessary to analyze, process, and manipulate data effectively.
涵盖的内容
7个视频3个作业1个插件
This module focuses on data visualization methods for effective data storytelling. Learners will develop skills in creating charts, graphs, and scatter plots while exploring the mathematical foundations of vector spaces and matrices. By mastering these visualization tools, students will be able to present data insights clearly and persuasively.
涵盖的内容
6个视频3个作业
This module provides a deep dive into the statistical foundations of data science. Learners will explore measures of central tendency, variability, probability, and hypothesis testing while addressing advanced concepts such as the Central Limit Theorem, Bayesian inference, and p-hacking. These skills prepare students to evaluate datasets critically and draw reliable conclusions.
涵盖的内容
11个视频4个作业
This module introduces learners to regression, optimization, and applied data analysis techniques. Students will implement gradient descent, preprocess datasets, and apply visual tools such as histograms, scatter plots, and box plots to extract insights. The module concludes with practical applications and a summary of the entire learning journey.
涵盖的内容
12个视频4个作业
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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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