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
โข Data Analysts and Business Analysts
โข Beginners in Data Science and Analytics
โข Business Intelligence Professionals
โข ETL and Reporting Professionals
โข Professionals transitioning into data-driven roles
Pre-requisites
โข Basic understanding of data concepts
โข Familiarity with spreadsheets (Excel preferred)
โข Logical thinking and analytical mindset
โข No prior programming experience required
Skillset Achieved
โข KNIME Analytics Platform navigation and workflow design
โข Data ingestion from multiple sources
โข Data cleaning and transformation techniques
โข Visual data pipeline creation (drag-and-drop workflows)
โข Basic statistical analysis and reporting
โข Introduction to data blending and integration
โข 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
โข Overview of KNIME architecture and interface
โข Creating and managing workflows
โข Importing data from files and databases
โข Basic node operations and workflow execution
Data Preprocessing and Transformation
โข Handling missing values and data cleansing
โข Filtering, sorting, and aggregating data
โข Data type conversions and normalization
โข Joining and merging datasets
Data Analysis and Visualization
โข Descriptive statistics using KNIME nodes
โข Creating charts and visual insights
โข Data segmentation and grouping
โข Reporting outputs and exporting results
Introduction to Machine Learning Workflows
โข Overview of ML concepts in KNIME
โข Building simple classification and regression models
โข Model evaluation basics
โข End-to-end workflow automation
Assessment Topics
โข KNIME workflow creation and node usage
โข Data cleaning and transformation techniques
โข Data aggregation and visualization
โข Basic statistical analysis in KNIME
โข Introduction to machine learning workflows
โข End-to-end data pipeline development
Evaluation
โข Hands-on workflow building exercises
โข Daily practical assignments using real datasets
โข Mini project on end-to-end data pipeline creation
โข 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
โThe KNIME training was extremely practical and easy to follow. I can now build complete workflows without writing code.โ
โGreat introduction to KNIME. The workflow-based approach made data analysis very intuitive.โ
โThe hands-on exercises helped me understand data preprocessing and automation very effectively.โ
โA very useful course for beginners in data science. The machine learning introduction was particularly helpful.โ
โExcellent training structure with real-world datasets. I can now confidently use KNIME for reporting and analytics.โ