With explosive growth in unstructured data, we have ample opportunities to design, develop and deploy AI models. While there are many courses which teach you Data Science, you need a step-by-step guide on how to select a problem, explore data, develop and deploy models and improve the model using user feedback and learning. This course provides you a methodology for AI model development and deployment and uses a case studies to give you skills and confidence.
This course covers many AI challenges and modifies CRISP-DM to deal with big data. We will introduce this methodology as modified by Authors to deal with AI and big data. Our modifications have been tried on a number of real-life large-scale projects. We will point case studies to get you an appreciation for how they get applied.
After completing this course, you will be able to
• Articulate data science process and methodology
• Understand how to analyze data sources and conduct feature engineering
• Understand how to build and integrate Data and AI driven modeling techniques
• Explore how users and experts will be engaged for model measurement and monitoring
- Understand the controls and governance aspects