Introduction to Data Science Corporate Training
From data curious to data capable.
This instructor-led program introduces data science properly: Python, statistics, data wrangling, visualization, and machine learning basics, practiced in guided labs on real datasets.
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-driven decisions team
The Edstellar DATA SCIENCE Capability Model
Assess
We baseline your team's data science skills before training begins.
Learn
Instructor-led sessions build Introduction to Data Science knowledge step by step.
Practice
Guided hands-on labs lock in each technique with coaching.
Apply
Teams apply Introduction to Data Science to real work before the program ends.
Measure
Skill checks show what improved and what comes next.
Need more than one program?Get a group quote
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Program Overview: What is Introduction to Data Science?
Data science starts with asking better questions of data. This program teaches the full beginner arc: working with data in Python, thinking statistically, visualizing clearly, and building first models.
Led by practicing data scientists, the program moves from Python and statistics to wrangling, visualization, and machine learning basics. Guided labs run in every module on real datasets.
The program closes with a capstone full build: an end-to-end data science project with analysis, model, and business recommendations, reviewed by the instructor.
Teams leave data-capable: cleaning data, analyzing it soundly, visualizing it clearly, and building models that answer real questions.
What's Included in this Workshop for Your Enterprise Teams
- 1
Instructor-Led Delivery
Live Data science sessions with certified trainers
- 2
Hands-On Labs
Guided labs built on real-world use cases
- 3
Tailored Curriculum
Agenda tuned to your stack and team goals
- 4
Assessments & Materials
Pre and post checks plus reference workbooks
- 5
Post-Training Support
Follow-up help as teams apply the skills
- Instructor-led delivery: onsite, live virtual, or hybrid
- Tailored agenda: topics matched to your team's stack and goals
- Guided hands-on labs built around real-world use cases
- Cohort sizes that suit small teams and large groups
- Materials, workbooks, and post-program reference guides
- Post-training support and assessment on request
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
Introduction to Data Science Course Topics and Program Outline
7 modules, 24 instructor-led hours, and 4 guided labs that move Introduction to Data Science from theory to dependable team practice.
Built by Edstellar with data scientists who ship models and analysis into production
Built by data scientists who ship models and analysis into production, shaped around your stack and use cases.
We check where your team stands on Data science today, so the program targets real gaps instead of repeating what they know.
Instructor-led sessions teach data science concepts in order, with demos and Q&A in every module.
guided labs give your team coached repetition on realistic data science scenarios with instructor review.
The capstone full build proves the learning: a data science project, built, reviewed, and ready to take back to work.
From baseline to job-ready in 24 hours.
Delivered as
Cohorts run hybrid, onsite, or live virtual formats, scheduled around your calendar in half-day or full-day blocks.
Frame a data question and hypothesis for a dataset.
learna)Asking good questions
b)Hypothesis framing
c)Project lifecycle
d)Ethics basics
Wrangle a messy dataset with pandas.
learna)Python refresher
b)pandas essentials
c)NumPy basics
d)Reading data files
Analyze a dataset statistically and report findings.
practicea)Descriptive statistics
b)Distributions
c)Sampling
d)Significance basics
Build a visual story from analysis results.
practicea)Chart selection
b)Matplotlib and seaborn
c)Dashboard basics
d)Storytelling with data
Train and evaluate a first model.
practicea)ML concepts
b)Regression
c)Classification
d)Model evaluation
Clean and prepare a real-world dataset.
practicea)Missing data
b)Joining datasets
c)Feature basics
d)Data pipelines intro
Present your project and defend the recommendations.
applya)Project presentation
b)Analysis walkthrough
c)Model review
d)Recommendation defense
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
Your team will wrangle data in Python, think statistically, visualize insights, build first models, and present findings that drive decisions.
Python wrangling
Clean and shape data with pandas.
Statistical thinking
Reason about distributions and samples.
Visualization
Choose charts that show the insight.
ML basics
Train regression and classification models.
Model evaluation
Judge models honestly with metrics.
Data storytelling
Present findings that persuade.
Project workflow
Run data projects end to end.
Teams that Benefit from this Introduction to Data Science Group Training
Built for analysts, engineers, and managers moving into data science. Content adapts to each cohort's data and tools, so every group works on problems that mirror its own.
Analysts leveling up to data science
Analysts add Python, statistics, and modeling to their toolkit, moving from reports to predictions.
Workflow friction
- Stuck in spreadsheets
- No modeling skills
- Reports nobody acts on
How the program helps
- Work in Python
- Build first models
- Drive decisions
Practice use cases
- analytics
- python
- modeling
Engineers adding data skills
Engineers learn the data science workflow, so they can build data features and work with data scientists.
Workflow friction
- No data fluency
- Weak collaboration with DS
- Data features avoided
How the program helps
- Speak data fluently
- Collaborate with scientists
- Ship data features
Practice use cases
- engineering
- fluency
- features
Managers commissioning analysis
Managers learn what data science can and cannot do, so they scope projects well and judge results.
Workflow friction
- Unrealistic expectations
- Poorly scoped projects
- Ignored analysis
How the program helps
- Scope projects well
- Judge results fairly
- Act on findings
Practice use cases
- management
- scoping
- decisions
Groups run with employees at similar levels so exercises match daily work. Mixed cohorts are welcome when goals align.
Prerequisites: Basic programming in any language and comfort with spreadsheets helps. No prior data science is required.
Introduction to Data Science: skill progression
A realistic path from foundation to advanced data science capability, mapped to the modules above. Your team can see exactly which skills each module builds.
Bands show where each skill starts and where this program takes it.
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
Instructor-led delivery in hybrid, onsite, or live virtual formats, with hands-on labs in every session.
Hybrid Training
Split your cohort between the training room and a live virtual feed. Every session is instructor-led, with hands-on labs in each module and the same curriculum for both groups.
- Live instruction in every session
- Onsite workshops for guided labs
- Virtual sessions for distributed teams
- One cohort or split batches
Onsite Training
Your trainer comes to your premises. Sessions stay practical: hands-on labs run in the room with the instructor beside each team.
- Trainer at your premises
- Guided guided labs with the instructor beside each team
- Team collaboration in one room
- Agenda tuned on the spot
Live Virtual Training
Join from anywhere in live instructor-led sessions. Labs run in shared environments so the trainer can see every screen and coach in real time.
- Join from anywhere, live
- Shared lab environments with trainer coaching
- Sessions recorded for review
- Same curriculum, same hours
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
Basic programming helps; a Python refresher is built into the program.
Statistics is taught intuitively with code; no advanced math is required.
Python, pandas, and scikit-learn: the standard open toolkit.
Yes. Classification and regression models on real datasets, honestly evaluated.
An end-to-end project: analysis, model, and business recommendations.
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.
Introduction to data science is the first step in this path. Your team learns what data science is, how projects run and where it adds value. The later steps build Python data science skills, machine learning with scikit-learn and engineering models for production.
Why Choose Edstellar as Your Introduction to Data Science Corporate Training Provider
Edstellar delivers Introduction to Data Science as instructor-led corporate training for enterprise teams: practitioner instructors, hands-on labs, and a curriculum tailored to your goals.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Data science training scoped to your stack and team level, tuned module by module after a discovery call.
Proven Methodology
A Learn-Practice-Apply arc refined across thousands of corporate teams: concepts first, then guided labs until each skill holds.
Practice-Based Learning
Most hours go to doing: guided labs on realistic tasks your team faces on the job, with instructor review after each one.
Expert Trainers
Instructors who work in data science teach from real delivery experience, matched to your cohort and goals.
Global Scale
Same Data science program for every cohort, delivered across time zones by 5,000+ certified trainers.
Measurable Outcomes
Pre- and post-program assessments mapped to your curriculum, so you can see exactly what each cohort learned and what comes next.
Build Data Science Foundations Through Questions, Analysis, and Defensible Recommendations
Edstellar introduces data science as a connected project workflow rather than a collection of tools. Participants frame questions, prepare data with Python, examine statistical evidence, and communicate findings visually before testing a first model. The final project links recommendations to analysis, with feedback on data preparation, evaluation, and the limits of conclusions.
- Step 01
Consult
We assess programming and spreadsheet comfort, analytical responsibilities, and expectations of data science to identify the support needed for Python work and realistic project framing.
- Step 02
Plan
We begin with questions and hypotheses, then connect pandas preparation, statistics, visualization, and introductory modelling before participants complete and explain an applied data science project.
- Step 03
Align
We align practical data science expertise with analysts, engineers, and business participants, confirming Python access and providing a shared language for analysis and model evaluation.
- Step 04
Customize
We adapt sample datasets and business questions to familiar decisions, retaining missing or inconsistent records that require participants to justify preparation and analysis choices.
- Step 05
Execute
Participants clean data with pandas, examine statistical patterns, build visual explanations, and train a first model, receiving feedback on methods, interpretation, and evidence quality.
- Step 06
Evaluate
We assess the final project for a well-framed question, transparent preparation, appropriate analysis and evaluation, and recommendations that acknowledge the dataset's limitations.
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?
Introduction to Data Science 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 Introduction to Data Science Training for Your Team
Tell us your team size, timelines, and goals for Introduction to Data Science training. An advisor will shape the agenda, confirm availability, and share a detailed proposal.