Will I get hands-on practice using KNIME?

Yes. The course includes multiple hands-on demonstrations and workflow-building exercises using KNIME for real-world data collection and processing tasks.

What data sources will I learn to work with?

You will work with CSV and Excel files, JSON and XML data, relational databases, APIs, and web-scraped data sources.

What skills will I gain from this course?

You will gain skills in data collection, data cleaning, transformation, exploratory data analysis, and building automated no-code data workflows using KNIME.

Is this course suitable for beginners in data science?

Yes. The course starts with foundational concepts and gradually progresses to more advanced data processing and analysis techniques.

How is my learning evaluated in this course?

Learning is evaluated through practice quizzes, module-level graded assessments, and a final comprehensive course assessment.

How long will it take to complete the course?

The course duration varies by learner, but most participants can complete it within a few weeks with regular study and hands-on practice.

KNIME is a leading open-source no-code analytics platform used globally to build data workflows, clean datasets, and generate insights — without writing code.

How are the hands-on demonstrations structured?

Each concept is taught through step-by-step instructor video demonstrations. You're encouraged to set up KNIME on your own machine, follow along with the instructor, and pause the video whenever you need time to replicate a step or explore the interface.

What will I get if I subscribe to this Specialization?

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.

Is financial aid available?

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.

Build Your First No-Code Data Workflow

Sparen Sie mit 40% Rabatt auf 3 Monate Coursera Plus bei den Fähigkeiten, die Sie zum Strahlen bringen. Jetzt sparen

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

Build Your First No-Code Data Workflow

Dieser Kurs ist Teil von Spezialisierung „No-Code Data Science and Machine Learning“

Dozent: Edureka

Bei enthalten

Mehr erfahren

5 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Anfänger

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

5 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Anfänger

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

Kategorie: Data Presentation
Kategorie: Correlation Analysis
Kategorie: Data Analysis Software
Kategorie: Data Collection
Kategorie: Data Validation
Kategorie: Data Wrangling
Kategorie: Data Science
Kategorie: Data Manipulation
Kategorie: Data Processing
Kategorie: Machine Learning
Kategorie: Data Visualization
Kategorie: Data Analysis
Kategorie: Feature Engineering
Kategorie: Data Cleansing
Kategorie: Data Quality

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Kürzlich aktualisiert!

März 2026

Bewertungen

15 Zuweisungen¹

KI-bewertet siehe Haftungsausschluss

Unterrichtet in Englisch

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Weitere Informationen zu Coursera für Unternehmen

Logos von Petrobras, TATA, Danone, Capgemini, P&G und L'Oreal

Erweitern Sie Ihre Fachkenntnisse

Dieser Kurs ist Teil der Spezialisierung Spezialisierung „No-Code Data Science and Machine Learning“

Wenn Sie sich für diesen Kurs anmelden, werden Sie auch für diese Spezialisierung angemeldet.

Lernen Sie neue Konzepte von Branchenexperten
Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 5 Module

Data science doesn't require code anymore. This course equips you with the practical skills to collect, clean, transform, and explore data using KNIME Analytics Platform — one of the world's most widely used no-code data science tools — so you can start building real workflows from day one.

Throughout this course, you'll explore the full data science lifecycle and discover how no-code platforms are transforming the way analysts, business professionals, and domain experts work with data at scale. Each concept is reinforced through step-by-step video demonstrations that you can follow along on your own KNIME setup — pause, rewind, and practice at your own pace. By the end of this course, you'll be able to: - Navigate the KNIME interface and build end-to-end no-code data workflows from scratch. - Collect and integrate data from CSV, Excel, JSON, XML, databases, APIs, and web scraping sources. - Clean, transform, and validate data using normalization, encoding, aggregation, and feature engineering techniques. - Perform exploratory data analysis using descriptive statistics, visualizations, correlation matrices, and heatmaps in KNIME. This course is designed for a diverse audience: aspiring data analysts, business analysts, operations and marketing professionals, students entering data science, and anyone looking to gain practical data skills without programming knowledge. Prior familiarity with spreadsheet tools like Excel is helpful, though no technical or coding background is required to succeed in this course. Take the first step toward no-code data mastery and build the foundational skills needed to work confidently with real-world data using KNIME.

St rengthen your foundational understanding of data science by exploring its core concepts, lifecycle, and real-world impact across industries. Learn how data-driven solutions are structured, the types of data used in analytics, and how no-code platforms enable faster insights. Gain hands-on exposure to the KNIME interface, workflows and data formats to build a strong base for practical data science without programming.

Das ist alles enthalten

8 Videos4 Lektüren3 Aufgaben

8 VideosInsgesamt 35 Minuten

Course Introduction3 Minuten
What is Data Science?4 Minuten
The Data Science Lifecycle4 Minuten
Case Study- Implementing Data Science at an OTT Giant6 Minuten
Types of Data6 Minuten
Introduction to No-Code Data Science5 Minuten
Traditional vs No-Code Workflow5 Minuten
Hands-On: Installing KNIME and Exploring the Interface3 Minuten

4 LektürenInsgesamt 40 Minuten

Course Outline: No-Code Data Preparation and Analysis with KNIME10 Minuten
Introduction to Data Science10 Minuten
Understanding Data Formats and KNIME10 Minuten
Module Summary: Foundations of Data Science & Introduction to KNIME10 Minuten

3 AufgabenInsgesamt 27 Minuten

Practice Assignment: Introduction to Data Science6 Minuten
Practice Assignment : Understanding Data Formats and KNIME6 Minuten
Graded Assignment: Foundations of Data Science & Introduction to KNIME15 Minuten

Develop practical data acquisition skills by learning how to collect, access, and integrate data from multiple sources and formats. Gain hands-on experience working with structured and semi-structured data, including CSV, Excel, JSON, XML, databases and web-based sources. Learn how to build your first KNIME workflows, connect to databases, and extract data using APIs and web scraping techniques for real-world data collection scenarios.

Das ist alles enthalten

10 Videos3 Lektüren3 Aufgaben

10 VideosInsgesamt 46 Minuten

Data Collection and Cleaning Overview4 Minuten
Data Formats and Storage Structures7 Minuten
Hands-On: Viewing and Exploring Data in KNIME4 Minuten
Hands-On: Reading CSV and Excel Files in KNIME4 Minuten
Hands-On: Creating Your First Workflow5 Minuten
Hands-On: Working with JSON + XML Data in KNIME7 Minuten
Essentails to Databases and SQL Operations4 Minuten
Hands-On: Connecting to Databases (SQLite) in KNIME4 Minuten
Collecting Web Data Through APIs and Web Scrapping4 Minuten
Hands-On: Web Scraping with KNIME5 Minuten

3 LektürenInsgesamt 30 Minuten

Data Acquisition and Working with Different Data Formats10 Minuten
Database and Web Data Collection10 Minuten
Module Summary: Data Collection -Methods, Sources and Techniques10 Minuten

3 AufgabenInsgesamt 27 Minuten

Practice Assignment: Data Acquisition and Working with Different Data Formats6 Minuten
Practice Assignment : Database and Web Data Collection6 Minuten
Graded Assignment: Data Collection : Methods, Sources and Techniques15 Minuten

Enhance your ability to prepare high-quality data by identifying and resolving common data issues such as missing values, duplicates, and inconsistencies. Learn essential data transformation techniques including normalization, standardization, encoding, aggregation, and feature creation. Gain hands-on experience building automated data processing pipelines in KNIME to ensure clean, reliable, and analysis-ready datasets.

Das ist alles enthalten

12 Videos5 Lektüren4 Aufgaben

12 VideosInsgesamt 56 Minuten

Exploring Dimensions of data quality4 Minuten
Hands-On: Identifying Missing Data Patterns and Outliers in KNIME5 Minuten
Hands-On: Handling Missing Values and Removing Duplicates in KNIME5 Minuten
Data Transformation using Normalization4 Minuten
Data Transformation using Standardization4 Minuten
Data Transformation using Encoding4 Minuten
Hands-On: Scaling and Normalization in KNIME7 Minuten
Hands-On: Encoding Categorical Variables in KNIME4 Minuten
Hands-On: Data Aggregation and Grouping in KNIME4 Minuten
Creating New Variables Through Feature Engineering3 Minuten
Hands-On: Feature Creation Techniques in KNIME6 Minuten
Hands-On: Building Automated Data Processing Pipelines6 Minuten

5 LektürenInsgesamt 50 Minuten

Data Quality and Cleaning10 Minuten
Normalization vs. Standardization 10 Minuten
Data Transformation Techniques10 Minuten
Feature Engineering and Pipeline Automation10 Minuten
Module Summary: Data Processing - Cleaning, Transformation and Quality10 Minuten

4 AufgabenInsgesamt 33 Minuten

Practice Assignment: Data Quality and Cleaning6 Minuten
Practice Assignment : Data Transformation Techniques6 Minuten
Practice Assignment : Feature Engineering and Pipeline Automation6 Minuten
Graded Assignment: Data Processing: Cleaning, Transformation and Quality15 Minuten

Strengthen your analytical skills by learning how to explore, summarize, and interpret data effectively. Apply descriptive statistics, distribution analysis, and visualization techniques to uncover patterns, trends, and relationships within datasets. Gain hands-on experience creating charts, correlation matrices, and heatmaps in KNIME to support data-driven insights and informed decision-making.

Das ist alles enthalten

8 Videos3 Lektüren3 Aufgaben

8 VideosInsgesamt 33 Minuten

Exploratory Data Analysis for Better Decision-Making3 Minuten
Summarizing Data Using Descriptive Statistics4 Minuten
Hands-On: Statistical Analysis in KNIME7 Minuten
Hands-On: Understanding Data Distribution and Outliers in KNIME5 Minuten
Data Visualization Principles and Chart Types3 Minuten
Hands-On: Creating Visualizations in KNIME4 Minuten
Understanding Data Relationships3 Minuten
Hands-On: Correlation Matrix and Heatmaps in KNIME3 Minuten

3 LektürenInsgesamt 30 Minuten

Statistical Analysis and Data Distribution10 Minuten
Data Visualization and Correlation Analysis10 Minuten
Module Summary: Exploratory Data Analysis (EDA)10 Minuten

3 AufgabenInsgesamt 27 Minuten

Practice Assignment: Statistical Analysis and Data Distribution6 Minuten
Practice Assignment: Data Visualization and Correlation Analysis6 Minuten
Graded Assignment: Exploratory Data Analysis (EDA)15 Minuten

This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz.

Das ist alles enthalten

1 Video1 Lektüre2 Aufgaben1 Diskussionsthema

1 VideoInsgesamt 3 Minuten

Course Summary3 Minuten

1 LektüreInsgesamt 30 Minuten

Practice Project: Building a No-Code Data Intelligence System for MarketPulse Analytics30 Minuten

2 AufgabenInsgesamt 60 Minuten

Knowledge Check: Getting Started with No-Code Data Science30 Minuten
Strategic Implementation of a No-Code Data Intelligence Pipeline Using KNIME30 Minuten

1 DiskussionsthemaInsgesamt 5 Minuten

Describe Your Learning Journey5 Minuten

Erwerben Sie ein Karrierezertifikat.

Fügen Sie dieses Zeugnis Ihrem LinkedIn-Profil, Lebenslauf oder CV hinzu. Teilen Sie sie in Social Media und in Ihrer Leistungsbeurteilung.

Dozent

Edureka

185 Kurse172.864 Lernende

von

Edureka

Mehr von Data Analysis entdecken

Status: Kostenloser Testzeitraum
LearnQuest
Data Science Foundations with No-Code Tools
Kurs
Status: Kostenloser Testzeitraum
Edureka
No-Code Data Science and Machine Learning
Spezialisierung
Status: Kostenloser Testzeitraum
LearnQuest
Automate Data Analysis and BI with No-Code AI
Kurs
Status: Kostenloser Testzeitraum
LearnQuest
No-Code Machine Learning and Data Science for Everyone
Spezialisierung

Warum entscheiden sich Menschen für Coursera für ihre Karriere?

Felipe M.

Lernender seit 2018

„Es ist eine großartige Erfahrung, in meinem eigenen Tempo zu lernen. Ich kann lernen, wenn ich Zeit und Nerven dazu habe.“

Jennifer J.

Lernender seit 2020

„Bei einem spannenden neuen Projekt konnte ich die neuen Kenntnisse und Kompetenzen aus den Kursen direkt bei der Arbeit anwenden.“

Larry W.

Lernender seit 2021

„Wenn mir Kurse zu Themen fehlen, die meine Universität nicht anbietet, ist Coursera mit die beste Alternative.“

Chaitanya A.

„Man lernt nicht nur, um bei der Arbeit besser zu werden. Es geht noch um viel mehr. Bei Coursera kann ich ohne Grenzen lernen.“

Häufig gestellte Fragen

This course is designed for beginners, aspiring data analysts, business professionals, and non-technical users who want to work with data using a no-code approach.

The course covers data science fundamentals, data collection from files, databases, and web sources, data cleaning, transformation, feature engineering, and exploratory data analysis using KNIME.

No prior programming experience is required. All concepts and workflows are implemented using KNIME’s visual, drag-and-drop interface.

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.

Weitere Fragen

Besuchen Sie die das Hilfe-Center für Kursteilnehmer.

Finanzielle Unterstützung verfügbar,

¹ Einige Aufgaben in diesem Kurs werden mit AI bewertet. Für diese Aufgaben werden Ihre Daten in Übereinstimmung mit Datenschutzhinweis von Courseraverwendet.