Dataiku Training provides practical experience in using Dataiku Data Science Studio (DSS) to prepare data, build machine learning models, automate workflows, and deploy AI solutions. The course covers collaborative analytics, visual and code-based development, model evaluation, and project governance, enabling teams to develop and manage end-to-end data science projects in enterprise environments.
Prerequisites:
Technical Prerequisites
- Basic understanding of statistics and machine learning concepts
- Familiarity with Python, R, or SQL
- Understanding of data preparation and data analysis principles
- Experience with data processing or big data tools such as Apache Hadoop or Spark
System Requirements
- 64-bit CPU and operating system
- Hardware virtualization enabled in BIOS
- VirtualBox or VMware Player installed
- Minimum 8 GB RAM
Recommended Background
- Degree or experience in a STEM field (for advanced modules)
What Will You Learn:
- Dataiku DSS interface and core concepts
- Project and Flow management
- Team collaboration tools and shared dashboards
- Data connectivity with SQL, cloud, Hadoop, and Spark
- Data preparation and transformation using visual recipes
- Exploratory data analysis and visualization
- Machine learning fundamentals
- Model creation, evaluation, and tuning
- Time series forecasting and image classification
- Custom coding with Python, R, and SQL
- Automation of data pipelines and workflows
- Model deployment and production scoring
- Model performance monitoring and governance
- End-to-end data science project development
Who Should Do This Training
- Data Scientists and Analysts
- Data Engineers and Managers
- Business and Project Analysts
- CRM and Marketing Professionals
- IT and Software Engineers
- Students and Researchers in Computer Science, Business, or Data Science
- Career Switchers seeking roles in Analytics or AI
