Edureka

No-Code Data Science and Machine Learning 专项课程

Edureka

No-Code Data Science and Machine Learning 专项课程

Learn No-Code Data Science and Machine Learning.

Master data workflows, ML modeling, and AutoML deployment.

Edureka

位教师:Edureka

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深入学习学科知识
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推荐体验

8 周 完成
在 5 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
中级 等级

推荐体验

8 周 完成
在 5 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Build end-to-end no-code data workflows to collect, clean, transform, and analyze data using KNIME Analytics Platform.

  • Apply visual machine learning techniques to build, evaluate, and tune regression and classification models using Orange Data Mining.

  • Train and deploy AutoML models for structured data, image, and NLP tasks using Google Vertex AI without writing code.

  • Integrate ML predictions into business tools and monitor deployed models to maintain performance in real-world cloud environments.

要了解的详细信息

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授课语言:英语(English)
最近已更新!

March 2026

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

  • 向大学和行业专家学习热门技能
  • 借助实践项目精通一门科目或一个工具
  • 培养对关键概念的深入理解
  • 通过 Edureka 获得职业证书

专业化 - 3门课程系列

Build Your First No-Code Data Workflow

Build Your First No-Code Data Workflow

第 1 门课程, 小时

您将学到什么

  • Navigate the KNIME interface and build end-to-end no-code data workflows to collect data from files, databases, APIs, and web sources

  • Collect and integrate data from multiple sources including files, databases, APIs, and web sources by building structured no-code workflows in KNIME.

  • Identify, analyze, and resolve data quality issues using appropriate cleaning and transformation techniques in KNIME workflows.

  • Apply statistical summaries and visualizations to evaluate data patterns, relationships, and insights for informed decision-making.

您将获得的技能

类别:Data Quality
类别:Data Collection
类别:Data Science
类别:Data Analysis
类别:Feature Engineering
类别:Data Visualization
类别:Data Validation
类别:Data Processing
类别:Machine Learning
类别:Data Cleansing
类别:Data Analysis Software
类别:Business Analytics
Applied Machine Learning Without Coding

Applied Machine Learning Without Coding

第 2 门课程, 小时

您将学到什么

  • Explain fundamental machine learning concepts, mathematical foundations, and the role of no-code tools in building analytical workflows.

  • Apply Orange Data Mining to build regression and classification models using visual, no-code workflows.

  • Analyze model performance using appropriate evaluation metrics to compare, select, and improve machine learning models.

  • Evaluate and optimize machine learning solutions by tuning parameters and designing end-to-end predictive workflows for real-world data.

您将获得的技能

类别:Model Evaluation
类别:Applied Machine Learning
类别:Regression Analysis
类别:Classification Algorithms
类别:Data Processing
类别:Machine Learning
类别:Logistic Regression
类别:Feature Engineering
类别:Random Forest Algorithm
类别:Data Manipulation
类别:Data Preprocessing
类别:Data Visualization
类别:Supervised Learning
类别:Data Science
类别:Data Analysis
类别:Exploratory Data Analysis
类别:Predictive Modeling
类别:Predictive Analytics
类别:Statistical Modeling
类别:Machine Learning Algorithms
AutoML: Build ML Models without Code

AutoML: Build ML Models without Code

第 3 门课程, 小时

您将学到什么

  • Set up Google Cloud Platform and Vertex AI to configure, upload datasets, and manage AutoML workflows for structured, image, and text data.

  • Train AutoML classification and regression models on structured data and interpret automated feature engineering and evaluation results

  • Build AutoML Vision and NLP models for image classification, object detection, and text sentiment analysis without writing any code

  • Deploy models for online predictions, connect outputs to Google Sheets and BigQuery, and monitor performance via the cloud console

您将获得的技能

类别:Model Deployment
类别:Image Analysis
类别:Model Evaluation
类别:Text Mining
类别:Google Cloud Platform
类别:Natural Language Processing
类别:Feature Engineering
类别:Applied Machine Learning
类别:Cloud Deployment
类别:Data Science
类别:Artificial Intelligence and Machine Learning (AI/ML)
类别:Machine Learning
类别:Google Sheets
类别:No-Code Development
类别:Predictive Modeling
类别:Computer Vision
类别:Machine Learning Software

获得职业证书

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位教师

Edureka
Edureka
175 门课程156,958 名学生

提供方

Edureka

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