Build the confidence to tackle any data project with zero coding. This course introduces modern no-code platforms, guiding learners in acquiring, cleaning, and visualizing data from diverse sources. Master the principles of robust data science practice, from data integrity checks to exploratory analysis. By the end, learners will know how to design models mapped directly to solving pressing business problems, all within easy-to-use tools that bridge technical and non-technical roles. Each module builds job-ready skills for regional and global data needs, with applications relevant to India, the USA, and Spanish-speaking markets.
Data Science Foundations with No-Code Tools
Data Science Foundations with No-Code Tools
包含在 中
您将学到什么
Learn to acquire, clean, and visualize business data using intuitive no-code tools—turning raw information into clear, actionable insights fast.
您将获得的技能
- Dashboard
- Data Literacy
- Data Governance
- No-Code Development
- Data Analysis
- Data Collection
- Data Science
- Data Processing
- Data Presentation
- Data Storytelling
- Data Integrity
- Data Integration
- Data Ethics
- Applied Machine Learning
- Data Transformation
- Data Cleansing
- Data Modeling
- Exploratory Data Analysis
- Predictive Modeling
- Data Capture
要了解的详细信息
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 No-Code Machine Learning and Data Science for Everyone 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3个模块
Welcome to Module 1: Data Acquisition and Preparation. In today’s fast-paced business world, confidently acquiring, cleaning, and preparing data is the foundation for all impactful analytics and machine learning. This module empowers you to pull data from a diverse range of sources with ease, automate error-prone cleaning routines, and ensure your data practices comply with local privacy laws—without writing a single line of code. You’ll build market-relevant skills for overcoming real workplace challenges, giving you the confidence and capability to drive results from day one in any data-driven environment.
涵盖的内容
9个视频1篇阅读材料3个作业
Welcome to Module 2: Exploratory Data Analysis & Visualization Techniques. In this module, you’ll master the art of transforming raw data into powerful, actionable insights using no-code platforms. You’ll discover how to quickly create interactive dashboards, identify key patterns and outliers, and deliver automated reports that drive business decisions. Learn how to present data stories that anyone in your organization can understand—empowering you to influence stakeholders and demonstrate value, regardless of technical background. These essential skills will position you as a trusted data communicator in today’s data-driven world.
涵盖的内容
7个视频1篇阅读材料3个作业
Welcome to Module 3: Model Design Fundamentals for Business Applications. This module gives you the tools to confidently turn business challenges into practical machine learning solutions—even if you have limited technical experience. You’ll learn how to select and configure no-code models tailored to real-world problems in your sector, leverage automation to highlight the most valuable predictors, and ensure your inputs are ready for robust analysis. By mastering these steps, you’ll boost efficiency and transparency across analytics projects and lay a solid foundation for effective model training, testing, and deployment in any industry setting.
涵盖的内容
8个视频2篇阅读材料2个作业
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。
位教师
提供方
从 Machine Learning 浏览更多内容
状态：免费试用
状态：免费试用
状态：预览University of California San Diego
状态：免费试用
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常见问题
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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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