Course Overview


Embark on a journey into the world of Data Science with our "Data Science in Action using Dataiku" course, designed to harness the power of unstructured data and AI modeling. This course is perfect for those who want a practical, hands-on experience in the field, following a modified CRISP-DM methodology with Dataiku as the primary tool.

Course Overview

  • Categorization of Data Scientists: Learn the distinction between 'clickers' and 'coders' in data science, focusing on the 'clicker' approach using tools like Dataiku.
  • Capstone Project: Apply your learning in a comprehensive capstone project, offering a real-world experience in designing and prototyping a Data Science engagement.
  • Comprehensive Methodology: The course begins with setting up your Dataiku environment and reviewing our unique data science methodology.
  • Seven-Step Data Science Methodology: Dive deep into each step of the process, from describing your use case to continuous model monitoring and evaluation, all within Dataiku. These steps include:
  • Use Case Description: Understand and articulate your selected data science use case.
  • Data Description: Explore data sources and datasets using Dataiku.
  • Dataset Preparation: Get hands-on experience in preparing datasets within Dataiku.
  • Model Development: Apply AI modeling techniques like clustering and regression in Dataiku.
  • Model Evaluation: Learn how to measure and evaluate your AI model results.
  • Model Deployment: Understand the process of deploying your AI models.
  • Model Monitoring: Master continuous monitoring and evaluation of your models in production.

This course is tailored for those seeking an introductory 'clicker' experience in data science. Whether you're a business analyst, project manager, or someone interested in coding or advanced machine learning, this course offers a foundational understanding of data science methodologies and practical applications using Dataiku. Download datasets, follow step-by-step instructions, complete assignments, and submit your final notebook to fully engage in this immersive learning experience. Join us to transform your data science skills and apply them in everyday scenarios.

Expected Outcome

  • Understanding Data Science Methodology: Students will learn a proven data science methodology, crucial for navigating the transition from a Business Intelligence (BI) to an Artificial Intelligence (AI) focused approach in dealing with big data challenges.
  • Hands-On Case Study Experience: Through a real case study, students will gain practical experience in designing and prototyping a data science project. This hands-on approach ensures a deeper understanding of the process and its application.
  • Focus on 'Clickers': The course categorizes data scientists into two groups: 'clickers' and 'coders'. 'Clickers' typically use tools like SPSS Modeler, Excel, and Dataiku, which are more GUI-oriented. This course is tailored primarily for 'clickers', providing them with the skills to utilize these tools effectively in data science engagements.
  • Dataiku as a Teaching Tool: Utilizing Dataiku, the course demonstrates all the essential steps and activities required in a data science engagement. Dataiku serves as the primary platform for illustrating the practical aspects of data science work, making the learning process more comprehensive and applicable.

Example Curriculum

  Introduction
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  Dataiku - Sandbox
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  Data Science Methodology
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  Step 1: Define Project
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  Step 2: Describe Data
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  Step 3: Prepare Data
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  Step 4: Develop Model
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  Step 5: Evaluate Model
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  Step 6: Deploy Model
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  Step 7: Optimize Model
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  Summary
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