Data Science Methodology in Action using Dataiku
Gain hands-on experience in building a Data Driven AI engagement using Dataiku
Ratings 3.88 / 5.00
What You Will Learn!
- Students will learn proven data science methodology to deal with big data challenges as we move from BI world to AI world.
- Students will use real case study and will gain hands-on experience in Designing / prototyping a Data science engagement on the chosen case study.
- We divide the data scientists into clickers and coders. Clickers Examples include SPSS Modeler, Excel and Dataiku. This course is primarily for clickers.
- This course uses Dataiku to show all necessary steps and activities needed for data science engagement.
Description
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.
Who Should Attend!
- This course is for anyone interested in becoming a data scientist such as students, business analysts, developers, testing professionals.
- There are several job categories where this course can be used as introductory material, such as data scientists, AI or automation engineer, test engineers, and knowledge engineers.
