Data Science with KNIME Analytics Platform Corporate Training
Instructor-led, hands-on training that builds your team's KNIME Analytics Platform skills from workflows to deployed analytics.
This program takes your team from KNIME workbench fundamentals through data wrangling, machine learning, and automated deployment, with every concept practiced in guided labs.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build a data-ready, model-driven team
The Edstellar DATA SCIENCE Capability Model
Diagnose analytics gaps
Skill checks map your team's KNIME fluency, data wrangling habits, and modeling readiness.
Standardize workflows
Shared conventions for KNIME workflows, naming, and documentation keep every pipeline readable.
Practice in labs
Guided labs move teams from wrangling to machine learning on their own datasets.
Measure progress
Capstone scoring tracks model quality, workflow maturity, and business relevance.
Scale delivery
Automation and data app patterns put working analytics into daily operations.
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Program Overview: What is Data Science with KNIME Analytics Platform?
Data Science with KNIME Analytics Platform is an instructor-led corporate training program for teams that want data science without heavy coding. Over 24 hours, participants learn to build data pipelines, run analytics, and create machine learning models in KNIME's visual, low-code workbench. The team learns by building real workflows: importing and cleaning data, exploring and visualizing it, training models, and automating the full flow.
Each module pairs a concise concept session with guided labs inside KNIME, where teams assemble real workflows node by node. Instructors review every workflow, coaching participants through data wrangling choices, visualization design, and model evaluation before the cohort advances. Practice builds across the program toward the capstone, an end-to-end data science project the team deploys as a data app. Feedback targets the team's own data and business questions.
Code-heavy data science excludes the very people closest to the business problem. This program removes that barrier, giving analysts and domain experts a visual workbench where they can build, test, and deploy real analytics. Teams return with data science capacity spread across the team instead of bottlenecked on two engineers.
The capstone asks each team to deliver an end-to-end data science project in KNIME, from data import and cleaning through analysis and modeling to a deployed, scheduled data app, presented to instructors. The review covers what matters in production: is the workflow readable, does the model hold up, and can it run unattended. Graduates take home a working project, reusable workflow templates, and the confidence to build the next one themselves.
Across 24 instructor-led hours, participants progress from KNIME fundamentals to an end-to-end capstone project. Guided labs keep every skill hands-on: transforming messy business data, exploring patterns, tuning models, and scheduling production workflows. By the end, your team can design, build, and maintain KNIME analytics solutions that answer real business questions.
What's Included in this Workshop for Your Enterprise Teams
- 1
KNIME foundations
Workbench setup and first workflows
- 2
Data wrangling
Cleaning, joining, and reshaping data
- 3
Analytics & ML
Exploration, visualization, and modeling
- 4
Automation & apps
Scheduling and deployed data apps
- 5
Capstone
End-to-end project with presentation
- Instructor-led sessions (live virtual, onsite, or hybrid)
- Guided hands-on labs with real business datasets
- Capstone project with instructor review and feedback
- Course materials, workflow templates, and reference guides
- Pre-training skills assessment for your cohort
- Post-training support resources and lab access
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
- Plan from 2000+ Industry-ready Training Programs
- Hands-On Labs on Live Infrastructure, Led by Industry Experts
Data Science with KNIME Analytics Platform Course Topics and Program Outline
A 24-hour instructor-led program with 6 modules, 24 practice labs, and a capstone project: KNIME foundations, data wrangling, exploratory analytics, machine learning, workflow automation, and a full end-to-end build.
Built by Edstellar with analytics engineers
Built by practitioners who ship KNIME analytics workflows in production, shaped around your stack and use cases.
We benchmark your team's KNIME fluency and data skills, then tune the lab intensity to your cohort's level.
Instructors walk through the KNIME workbench, wrangling patterns, and modeling workflows with live demos.
Your team builds workflows, cleans datasets, trains models, and automates pipelines in guided labs.
A capstone project ships a deployed KNIME data app that answers a live business question for your team.
24 hours, 24 guided labs, one deployed KNIME data app your team owns
Delivered as
Delivered by certified instructors in live virtual, onsite, or hybrid modes, with every concept reinforced in guided KNIME labs.
Install KNIME and build a first workflow that reads a CSV file and produces a basic summary report.
learna)Installing KNIME Analytics Platform and configuring the workbench
b)Understanding nodes, ports, workflows, and the visual programming model
c)Reading data from CSV, Excel, and database sources
d)Basic data inspection with interactive views and statistics nodes
e)Saving, exporting, and sharing workflows and workflow groups
Build a transformation workflow that cleans a messy sales dataset and loads it into a database table.
learna)Filtering, sorting, grouping, and aggregating records
b)Joining, concatenating, and pivoting multiple tables
c)String manipulation, date handling, and missing value treatment
d)Row and column operations with Rule Engine and Column Expressions
e)Writing clean datasets back to files and databases
Perform an exploratory analysis of a customer dataset and publish an interactive dashboard for the team.
practicea)Descriptive statistics and distribution analysis with KNIME views
b)Correlation, cross-tabulation, and outlier detection techniques
c)Building charts with the JavaScript view nodes
d)Creating interactive dashboards and composite views
e)Reporting results with the BIRT reporting integration
Train and tune a churn prediction model, compare learners, and evaluate with a confusion matrix.
practicea)Preparing features: encoding, scaling, and train-test partitioning
b)Training regression and classification models with native learners
c)Model evaluation: scoring, confusion matrices, and ROC analysis
d)Hyperparameter tuning and cross-validation loops
e)Clustering, anomaly detection, and text mining workflows
Parameterize an analytics workflow, wrap it as a data app, and schedule it for nightly execution.
applya)Parameterizing workflows with variables and flow variables
b)Batch execution, scheduling, and error handling patterns
c)Building data apps with widgets and interactive views
d)Managing credentials, environments, and versioned workflow groups
e)Connecting to databases, APIs, and cloud storage sources
Deliver a full KNIME analytics project: workflow, model, data app, and executive presentation.
applya)Scoping the business problem and defining success metrics
b)Designing the end-to-end workflow: ingestion to deployment
c)Wrangling, modeling, and validating on real project data
d)Building the stakeholder dashboard and report pack
e)Presenting results and defending the recommended actions
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
By the end of this program, your team will be able to design, build, and maintain KNIME analytics workflows that move raw data into insight, models, and deployed apps.
Build visual data workflows
Design KNIME pipelines that read, clean, and reshape data without writing code.
Wrangle messy datasets
Join, pivot, and transform business data into analysis-ready tables.
Run exploratory analytics
Detect patterns, outliers, and drivers with statistics and visual views.
Train machine learning models
Build, tune, and evaluate regression, classification, and clustering models.
Automate analytics delivery
Schedule, parameterize, and monitor KNIME workflows in production.
Ship interactive data apps
Wrap workflows as data apps that business users can run and explore.
Present insight to stakeholders
Report findings and recommendations in clear, decision-ready formats.
Teams that Benefit from this Data Science with KNIME Analytics Platform Group Training
This program is built for analytics, data, and business teams that want low-code data science in KNIME. Content adapts to each cohort's tools and maturity, so every team practices the workflows it actually owns.
Deliver self-serve KNIME analytics faster
Analysts learn to automate recurring reports and build reusable KNIME workflows that scale across requests.
Workflow friction
- Manual reporting bottlenecks
- Inconsistent analysis methods
- Excel-only analytics
How the program helps
- Faster turnaround on ad-hoc analysis
- Reusable workflow templates
- Reliable data pipelines
Practice use cases
- report automation
- dashboard building
- ad-hoc analysis
Prototype and deploy models quickly
Data scientists speed up experimentation with KNIME's visual modeling and validation loops.
Workflow friction
- Long prototyping cycles
- Hard-to-reproduce experiments
- Deployment complexity
How the program helps
- Faster model iteration cycles
- Built-in evaluation workflows
- Easy deployment patterns
Practice use cases
- model prototyping
- feature engineering
- model validation
Run analytics without deep coding
Operations teams build their own data apps and automated reports with guided KNIME workflows.
Workflow friction
- Waiting on analyst bandwidth
- Stale operational reports
- Limited technical skills
How the program helps
- Self-serve operational insight
- Less dependency on data teams
- Faster decision cycles
Practice use cases
- ops dashboards
- self-serve reports
- data apps
Extend pipelines into KNIME analytics
BI and data engineering teams integrate KNIME into existing stacks for wrangling, enrichment, and modeling.
Workflow friction
- Brittle manual data prep
- Slow enrichment cycles
- Tool sprawl
How the program helps
- Flexible enrichment layers
- Faster data prep
- Low-code modeling access
Practice use cases
- data enrichment
- pipeline integration
- data prep
Departments above are examples; the program is tailored to the roles and data workflows of your cohort.
Prerequisites: This program suits analysts, data professionals, and business teams who work with data regularly. Comfort with basic data concepts such as tables, rows, and columns helps, but no prior KNIME or coding experience is required. Instructors adapt pacing and examples to the tools and maturity of each cohort.
Analyst to KNIME data science practitioner
From first KNIME workflows to deploying full data science projects, with lab depth tuned to each learner.
A progression that grows with data careers, from KNIME basics to confident, deployed data science practice.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the delivery format that fits your team. Every mode includes instructor-led sessions, guided KNIME labs, and the capstone project.
Hybrid Training
Mix onsite and virtual sessions so distributed teams learn together without losing hands-on lab time.
- Live instruction across locations
- Guided KNIME labs for everyone
- Shared capstone reviews
- Flexible scheduling windows
Onsite Training
The instructor delivers the full program at your office, with labs run against your data and tooling.
- Face-to-face instructor delivery
- Labs on your datasets
- Team whiteboard sessions
- Capstone on real data
Live Virtual Training
Live online sessions with the same guided labs, breakout practice, and capstone feedback as onsite delivery.
- Live instructor interaction
- Cloud-hosted KNIME labs
- Breakout practice groups
- Recorded recap sessions
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
The program runs for 24 instructor-led hours, typically delivered over three to four days with guided labs and a capstone project.
Yes. The first modules start with installation and workflow basics, so teams with no KNIME background can follow comfortably.
No. KNIME's visual workbench is low-code. Familiarity with data concepts helps, but Python or R experience is not required.
Sessions are live and instructor-led, available in virtual, onsite, and hybrid formats, with interactive Q&A throughout.
The program includes 24 guided labs covering wrangling, visualization, machine learning, and workflow automation, plus a capstone project.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
KNIME comes second, after your team understands the data science process. Its visual workflows let people build preparation and modelling steps without heavy coding. That leads to data mining techniques and then to predictive analytics and forecasting for business planning.
Why Choose Edstellar as Your Data Science with KNIME Analytics Platform Training Provider
Edstellar pairs deep KNIME expertise with a delivery model built for enterprise teams: tailored labs, expert instructors, and measurable skill growth.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Labs and capstone datasets are tuned to your industry, tools, and the analytics questions your team answers daily.
Proven Methodology
A repeatable learn, practice, apply arc moves learners from KNIME basics to production-ready analytics workflows.
Practice-Based Learning
Twenty-four guided labs keep every learner building workflows, tuning models, and automating pipelines hands-on.
Expert Trainers
Instructors are practitioners who ship KNIME analytics in production and bring real project lessons to class.
Global Scale
Consistent curriculum and lab quality across cohorts, locations, and time zones for enterprise rollouts.
Measurable Outcomes
Skill checks and capstone scoring show exactly how KNIME fluency and modeling capability grew in your team.
Build KNIME Analytics Through Visual Workflows and Critical Model Evaluation
Edstellar develops low-code data science through KNIME preparation, exploration, modeling, and automation. Participants connect nodes into reusable workflows and examine model results before packaging a data app. The final project review assesses data quality, analytical reasoning, parameterization, and the clarity with which findings are communicated to business users.
- Step 01
Consult
We explore regular data tasks and table familiarity to identify gaps in visual workflow design, transformation, statistical exploration, and model-result interpretation.
- Step 02
Plan
We establish KNIME setup before data wrangling and exploratory analysis, then machine learning, parameterized delivery, and the complete analytics project.
- Step 03
Align
We align KNIME instruction with analysts and business-data teams, providing visual-workflow foundations without requiring coding and matching examples to the cohort's analytical maturity.
- Step 04
Customize
We tailor sample sales and customer datasets to relevant questions while retaining database loading, learner comparison, and scheduled data-app exercises.
- Step 05
Execute
Participants clean data, compare churn learners, and parameterize workflows, receiving feedback on node logic, confusion matrices, dashboard clarity, and automation behavior.
- Step 06
Evaluate
We assess the project for reproducible workflows, appropriate model evaluation, coherent data-app delivery, and an executive explanation grounded in the analytical evidence.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Data Science with KNIME Analytics Platform Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Data Science with KNIME Analytics Platform Training for Your Team
Tell us about your team size, timelines, and goals, and we will design a KNIME training plan that fits your schedule and budget.