This intensive training focuses on visual workflow development, data preprocessing, transformation, analysis, and basic machine learning using a no-code/low-code approach.
Overview
KNIME Training is a practical, hands-on program designed to help learners build end-to-end data analytics workflows using the KNIME Analytics Platform. This intensive training focuses on visual workflow development, data preprocessing, transformation, analysis, and basic machine learning using a no-code/low-code approach. Participants will gain the ability to design scalable data pipelines, automate analytics tasks, and integrate multiple data sources for business intelligence and data science applications across industries
Learning Outcomes
Participants will gain strong practical skills in visual data analytics using KNIME, including workflow creation, data preprocessing, analysis, and basic machine learning. They will be able to automate analytics processes and integrate multiple data sources for business insights.
Duration & Delivery Mode
14 hours
Target Audience
• Data Analysts and Business Analysts
• Beginners in Data Science and Analytics
• Business Intelligence Professionals
• ETL and Reporting Professionals
• Professionals transitioning into data-driven roles
Pre-requisites
• Basic understanding of data concepts
• Familiarity with spreadsheets (Excel preferred)
• Logical thinking and analytical mindset
• No prior programming experience required
Skillset Achieved
• KNIME Analytics Platform navigation and workflow design
• Data ingestion from multiple sources
• Data cleaning and transformation techniques
• Visual data pipeline creation (drag-and-drop workflows)
• Basic statistical analysis and reporting
• Introduction to data blending and integration
• Foundational machine learning workflow development
Course Outcome
Upon completion of this training, participants will be able to design and execute complete data analytics workflows using KNIME. They will be capable of performing data preparation, analysis, and basic predictive modeling without coding, enabling efficient data-driven decision-making in business environments.
Course Outline
Introduction to KNIME Analytics Platform
• Overview of KNIME architecture and interface
• Creating and managing workflows
• Importing data from files and databases
• Basic node operations and workflow execution
Data Preprocessing and Transformation
• Handling missing values and data cleansing
• Filtering, sorting, and aggregating data
• Data type conversions and normalization
• Joining and merging datasets
Data Analysis and Visualization
• Descriptive statistics using KNIME nodes
• Creating charts and visual insights
• Data segmentation and grouping
• Reporting outputs and exporting results
Introduction to Machine Learning Workflows
• Overview of ML concepts in KNIME
• Building simple classification and regression models
• Model evaluation basics
• End-to-end workflow automation
Assessment Topics
• KNIME workflow creation and node usage
• Data cleaning and transformation techniques
• Data aggregation and visualization
• Basic statistical analysis in KNIME
• Introduction to machine learning workflows
• End-to-end data pipeline development
Evaluation
• Hands-on workflow building exercises
• Daily practical assignments using real datasets
• Mini project on end-to-end data pipeline creation
• Trainer-led evaluation of workflow design and outputs
Course Materials
Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.
Certification
Participants who successfully complete the training will receive an AcadNXT Certification in KNIME Training, validating their expertise in KNIME workflow development, data preprocessing, analytics automation, visualization, and basic machine learning using the KNIME platform.
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What Our Students Say
“The KNIME training was extremely practical and easy to follow. I can now build complete workflows without writing code.”
“Great introduction to KNIME. The workflow-based approach made data analysis very intuitive.”
“The hands-on exercises helped me understand data preprocessing and automation very effectively.”
“A very useful course for beginners in data science. The machine learning introduction was particularly helpful.”
“Excellent training structure with real-world datasets. I can now confidently use KNIME for reporting and analytics.”