Dataiku Data Science Studio (DSS) Corporate Training
Instructor-led, hands-on training that builds your team's Dataiku DSS skills from projects and flows to deployed models.
This program takes your team from DSS project fundamentals through visual data preparation, machine learning, and model 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 visual, production-ready data science team
The Edstellar DATA SCIENCE Capability Model
Diagnose analytics gaps
Skill checks map your team's DSS fluency, data preparation habits, and modeling readiness.
Standardize project workflows
Establish shared DSS project structure, naming, and recipe conventions across the team.
Practice in guided labs
Hands-on labs cover flows, visual recipes, ML design, and deployment on real datasets.
Measure model performance
Evaluation metrics, experiment tracking, and checks prove model quality before deployment.
Scale to production flows
Scenarios, APIs, and governance practices carry DSS projects into live operations.
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Program Overview: What is Dataiku Data Science Studio (DSS)?
Dataiku Data Science Studio (DSS) is a practical program for analysts and data scientists who want to ship real data products without writing everything from scratch. Participants learn visual recipes, AutoML, model evaluation, and deployment inside the DSS platform. It is built for analytics teams adopting Dataiku and business users moving from spreadsheets to governed machine learning.
Learning happens inside live DSS projects: participants prepare messy datasets with visual recipes, train models with AutoML, and deploy scoring endpoints for real use. Instructors with production DSS experience review each flow and coach learners on feature engineering and model validation. Collaboration and automation modules show how teams share projects safely with proper governance. A capstone data product ties every skill together in one working deliverable.
Analytics teams stall when every analysis is a one-off: models that never deploy, undocumented prep work, and insights that die in notebooks. Business stakeholders wait weeks for answers they needed yesterday. This program shows teams how to turn ad-hoc analysis into repeatable, governed data products that keep delivering value.
The capstone is an end-to-end DSS data product: a real business dataset prepared, modeled, evaluated, and deployed as a scoring service, with automation and governance configured. Participants demo the working product to reviewers, and return with a reusable blueprint for turning their own backlog of analyses into production assets.
Across 24 instructor-led hours, participants progress from DSS fundamentals to an end-to-end capstone project. Guided labs keep every skill hands-on: building visual flows, preparing messy business data, running ML experiments, and deploying models to production. By the end, your team can design, build, and operate DSS data science projects that deliver measurable business value.
What's Included in this Workshop for Your Enterprise Teams
- 1
DSS foundations
Projects, datasets, and the Flow
- 2
Data preparation
Visual recipes and data quality
- 3
Visual machine learning
Experiments, tuning, and evaluation
- 4
Deployment & automation
Scoring, APIs, and scenarios
- 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, flow 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
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- Hands-On Labs on Live Infrastructure, Led by Industry Experts
Dataiku Data Science Studio (DSS) Course Topics and Program Outline
A 24-hour instructor-led program with 6 modules, 24 practice labs, and a capstone project: DSS foundations, data preparation, visual machine learning, model deployment, automation, and a full end-to-end capstone.
Built by Edstellar with data science practitioners
Built by practitioners who ship Dataiku DSS data products in production, shaped around your stack and use cases.
We benchmark your team's DSS fluency and data maturity, then tune lab intensity and examples to your cohort.
Instructors demo DSS projects, flows, visual recipes, and the Design Lab with live, production-style walkthroughs.
Your team builds flows, prepares data, trains models, and deploys scoring services in guided DSS labs.
A capstone ships an end-to-end DSS data product, from raw data to a deployed model your team presents.
24 hours, 24 guided labs, one deployed DSS data product your team owns
Delivered as
Delivered by certified instructors in live virtual, onsite, or hybrid modes, with every DSS concept reinforced in guided labs.
Create a DSS project, import a business dataset, and publish your first Flow to a shared project folder.
learna)Creating DSS projects and understanding the project workspace
b)Navigating datasets, libraries, notebooks, and the Flow view
c)Connecting common data sources and importing datasets
d)Managing project libraries, plugins, and code environments
e)Sharing projects and collaborating across team roles
Build a multi-step visual Flow that cleans and joins messy sales data into an analysis-ready dataset.
learna)Designing Flows with visual recipes: sync, join, group, and split
b)Applying preparation processors for cleaning and reshaping
c)Managing schemas, storage types, and dataset partitions
d)Exploring data with charts, statistics, and visual profiling
e)Building partitioned flows for repeatable data preparation
Run a visual ML experiment on churn data, tune features and algorithms, and select the best model.
practicea)Setting up visual ML tasks: prediction, clustering, and AutoML
b)Handling features: encoding, imputation, and feature engineering
c)Training algorithms and comparing experiment sessions
d)Tuning hyperparameters with visual search strategies
e)Interpreting partial dependence, variable importance, and subpopulation analysis
Deploy your churn model as a batch scoring Flow and a test API endpoint, then verify predictions.
practicea)Evaluating models with metrics, lift charts, and calibration
b)Comparing models in the model evaluation store
c)Batch scoring new data through Flow recipes
d)Deploying models as real-time API endpoints
e)Monitoring deployed models for drift and performance decay
Automate a daily scoring scenario with checks and alerts, and set up project-level access controls.
applya)Building scenarios to schedule and orchestrate Flow runs
b)Adding metrics, checks, and reporters to automation
c)Collaborating with wikis, discussions, and version control
d)Managing users, groups, and project security
e)Applying model governance, sign-off, and audit practices
Deliver a complete DSS data product from raw data to a deployed model, reviewed by your instructor.
applya)Scoping a business problem and selecting the right datasets
b)Building the full preparation Flow and visual ML experiment
c)Deploying the winning model as batch and real-time scoring
d)Documenting the Flow for handover and governance review
e)Presenting results, metrics, and next steps to stakeholders
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 operate DSS data science flows from raw data to deployed models.
Build DSS project flows
Create and manage projects, datasets, and recipes inside the DSS Flow interface.
Prepare data visually
Clean, join, and reshape datasets with visual recipes and preparation processors.
Train models visually
Run experiments in the visual Design Lab with tuned algorithms and feature handling.
Evaluate and compare models
Score, compare, and select models using metrics, charts, and experiment tracking.
Deploy scoring services
Publish models as batch scoring flows and real-time API endpoints.
Automate flows with scenarios
Schedule and orchestrate flows with scenarios, metrics, and checks.
Govern data products
Apply collaboration, versioning, and model monitoring practices to production flows.
Teams that Benefit from this Dataiku Data Science Studio (DSS) Group Training
This program is built for data, analytics, and business teams that want visual, collaborative data science in Dataiku DSS. Content adapts to each cohort's tools and maturity, so every team practices the workflows it actually owns.
Ship DSS models to production faster
Data scientists learn to prototype, tune, and deploy models in DSS with shared flows and governed experiments.
Workflow friction
- Ad-hoc notebook sprawl
- Slow model handoffs
- Inconsistent modeling methods
How the program helps
- Faster model iteration cycles
- Reusable DSS flow templates
- Governed experiment tracking
Practice use cases
- model prototyping
- feature pipelines
- experiment tracking
- churn prediction
Deliver self-serve analytics without bottlenecks
Analysts learn to automate recurring analysis and build trusted DSS datasets the business can reuse.
Workflow friction
- Spreadsheet-only analysis
- Manual data refreshes
- Siloed analytics requests
How the program helps
- Automated recurring analysis
- Trusted reusable datasets
- Faster insight delivery
Practice use cases
- report automation
- data blending
- dashboard feeds
Build visual pipelines the whole team owns
Engineers learn to design, schedule, and monitor DSS flows that analysts and scientists can extend.
Workflow friction
- Long pipeline dev cycles
- Opaque data pipelines
- Repeated schema rework
How the program helps
- Shared visual pipeline tooling
- Faster delivery of datasets
- Transparent flow lineage
Practice use cases
- pipeline building
- data quality
- flow orchestration
- scheduled refreshes
Get faster, trusted answers from data
Operations teams learn to use DSS outputs, dashboards, and scoring services in their daily decisions.
Workflow friction
- Slow insight cycles
- Data literacy gaps
- Report request backlogs
How the program helps
- Faster answers from data
- Shared analytics language
- Trusted dashboard metrics
Practice use cases
- self-serve insights
- KPI tracking
- demand forecasting
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 Dataiku DSS experience is required. Instructors adapt pacing and examples to the tools and maturity of each cohort.
Analyst to DSS data science practitioner
From first DSS projects to deploying full data science flows, with lab depth tuned to each learner.
A progression that grows with data careers, from DSS 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 DSS 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 DSS labs for everyone
- Shared capstone reviews
- Flexible scheduling windows
Onsite Training
Instructors deliver the full program at your site, with labs tuned to your data and team workflows.
- Dedicated onsite instructors
- Labs on your business data
- Team-focused capstone work
- Minimal travel disruption
Live Virtual Training
Join live virtual sessions with the same guided labs, breakout reviews, and capstone support as onsite.
- Live instructor interaction
- Cloud-based DSS lab environments
- Virtual breakout coaching
- Recorded sessions for review
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.
Learn from industry experts.
Every session is led by a practitioner who has run monitoring for models in production, not a generalist working from slides.
Uddipta
Data Science Trainer in Guwahati
8+ years of Experience
Yogesh
Data Science Trainer in Bhopal
8+ years of Experience
Sudhanshu
Machine Learning Trainer in Bareilly
19+ years of Experience
Prafful
SQL and Python Trainer in Pune
12+ years of Experience
Saurabh
Introduction to Machine Learning Trainer in Indore
7+ years of Experience
Pinak
Data Science Trainer in Bengaluru
8+ years of Experience
Hari
Data Science, AI and AgilePM Trainer in Bengaluru
16+ years of Experience
Trainers are matched to your stack and delivery window at scheduling. We confirm your assigned trainer, with a full profile, before the program is booked.
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 projects, the Flow, and visual recipes, so teams with no DSS background can follow comfortably.
Share your team size, preferred dates, and delivery mode with a training advisor, and we will prepare a tailored quote within one business day.
Yes. A discovery call maps your team's DSS maturity, data workflows, and goals so we tune the labs and capstone to your needs.
Yes. Live virtual delivery includes the same instructor-led sessions, guided labs, and capstone reviews as onsite cohorts.
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.
Dataiku DSS comes second, after your team understands the data science process. Dataiku gives analysts and data scientists one shared place to prepare data and build models. The path then moves to forecasting for business and finally to engineering models for production.
Why Choose Edstellar as Your Dataiku Data Science Studio (DSS) Training Provider
Edstellar pairs deep data science 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
Datasets, flows, and the capstone are tuned to your industry and the analytics questions your team answers daily.
Proven Methodology
We sequence DSS learning from flows to deployed models, so every concept lands in a guided lab before the capstone.
Practice-Based Learning
Your team builds real DSS flows, trains models, and deploys scoring services in instructor-reviewed labs.
Expert Trainers
Instructors are DSS practitioners who ship data science products in production, not just teach the tool.
Global Scale
Live virtual, onsite, or hybrid delivery across time zones, with consistent labs and reviews in every cohort.
Measurable Outcomes
Skill checks before and after the program show exactly how your team's DSS fluency has grown.
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?
Dataiku Data Science Studio (DSS) 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 Dataiku Data Science Studio (DSS) Training for Your Team
Tell us about your team size, timelines, and goals, and we will design a Dataiku DSS training plan that fits your schedule and budget.