AI Intro, a primer on AI, is geared for the executive/ senior management team. It enables business leaders and decision makers to explore and grow functional understanding of artificial intelligence.
AI delivery is designed to demystify the delivery process and is designed for the Middle Management, who are responsible for the Data and AI/ ML delivery. This session entails introduction to various tools and tricks including AI Canvas and Data to Insights Engagement framework.
AI Ultimate is the hands-on AI/ ML training that has been designed for the single contributors like Business and Data Analysts, Engineers, Citizen Data Scientists & Software Developers. It gives them a deeper understanding of AI solutions.
AI Strategy lays out the strategic plan as it pertains to artificial intelligence and aligns it with the long and short term corporate goals and initiatives. It is a customised results-driven plan that leverages the latest advancement in AI/ Machine learning.
AI Value computes expected financial benefit from Artificial Intelligence for organisation of any shape and size, and stage of AI maturity. AI Value calculates total AI value - increase in revenue and reduction in cost - before spending or taking up any AI projects.
AI Roadmap articulates the AI transformation journey for the company based on the AI Strategy and Value assessment. Depending on the company’s objectives, the roadmap strikes the balance between high value AI applications and low hanging AI solutions.
AI Model is where the proof of concept (POC) and production ready AI models are created. This step includes data collection, cleaning, annotation and pre-processing, model training and validation, and finally deployment in production, once the desired accuracy is achieved.
AI Apps enable the consumption of AI models and transformation of desktop and mobile apps into intelligent software capable of predicting the future and helping in making better decisions. With this, you get your AI embedded applications.
AI Ops is a set of practices that monitors, retrains and manages the deployed model in production environment and integrates into business workflow. AI Ops detects digital-service issues earlier and resolves before business operations and customers are impacted.