Data Science in Action using Dataiku
Gain Hands-On Experience in Building AI Solutions with Dataiku
 
👉 Start learning today and gain a competitive edge in AI!
 
Course Overview
Embark on a journey into the world of data science with "Data Science in Action using Dataiku." This self-paced course is designed to harness the power of unstructured data and AI modeling using Dataiku as the primary tool.
Following a modified CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology, this course provides a hands-on, step-by-step guide to building AI solutions. You will explore the entire data science lifecycle — from defining a use case and preparing data to developing, deploying, and monitoring AI models within Dataiku.
This course focuses on the ‘clicker’ approach to data science — utilizing graphical user interface (GUI)-based tools like Dataiku to develop AI solutions without requiring deep coding knowledge. The course features a capstone project where you will design and prototype a real-world data science engagement, ensuring that you gain both theoretical knowledge and practical experience.
Whether you're a business analyst, project manager, or aspiring data scientist, this course will give you the skills and confidence to implement AI-driven solutions using Dataiku’s intuitive platform.
 
Key Learning Objectives
By the end of this course, you will be able to:
✅ Understand the Data Science methodology – Learn the modified CRISP-DM framework and how it applies to AI projects.
✅ Define and describe use cases – Identify business challenges and translate them into data science projects.
✅ Prepare and clean data using Dataiku – Master the process of importing, structuring, and preparing data.
✅ Develop AI models – Build predictive models using clustering, regression, and classification techniques in Dataiku.
✅ Evaluate and refine AI models – Measure model performance and optimize results using evaluation metrics.
✅ Deploy AI models – Understand the process of deploying AI models into production environments.
✅ Monitor and update AI models – Establish continuous monitoring and improvement processes for deployed models.
✅ Differentiate between 'clickers' and 'coders' – Learn the strengths and limitations of GUI-based AI solutions versus coding-based approaches.
 
Who Should Attend
This course is ideal for:
✔️ Business analysts and project managers seeking to integrate AI into business processes.
✔️ Data science beginners looking for a non-coding, hands-on introduction to AI.
✔️ IT professionals and data engineers working on data transformation projects.
✔️ Consultants helping businesses adopt AI-driven strategies.
✔️ ‘Clickers’ using GUI-based AI tools like SPSS Modeler, Excel, and Dataiku.
 
Prerequisites
To enroll in this course, you should have:
Basic understanding of data analysis and business processes.
Familiarity with data science concepts is helpful but not required.
An analytical mindset and a willingness to learn.
 
Expected Outcome
Upon successful completion of the course, you will:
✅ Gain a deep understanding of the CRISP-DM methodology for AI development.
✅ Develop AI models using Dataiku’s intuitive platform.
✅ Build and deploy AI solutions to solve real-world business challenges.
✅ Understand the key differences between ‘clickers’ and ‘coders’ in AI development.
✅ Gain practical experience through a hands-on capstone project.
✅ Master the ability to monitor and refine AI models post-deployment.
✅ Earn a recognized certification in Data Science using Dataiku from the Applied AI Institute (AAII).