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).