Learn How to Leverage Python modules for Advanced Analytics, How to Codify ML Algorithms for Descriptive Analytics, and How to deploy Python/Jupyter Notebook with Analytics Solutions
Learn the evaluation criteria metrics, levels of analytics, data science methods & solutions, scale-up strategy for successful implementation of ‘Data Science & Analytics’ initiative.
Learn How to Build intelligence for Operation through Soft Sensors, Create Connected Analytics for System-level KPI’s, Practical Workflow & implementation of Digital Twin
Learn How to start creating Value out of manufacturing data by defining the (achievable) problem statement and objectives. How to select right ML methods & workflows, Which techniques to apply and build (practical) solution.
Learn How to Extract Value out of Process Data, Deploy Machine Learning Models, and Achieve Operational Excellence through advanced visualization of your Process Data.
In this e-Meet, our experts will be discussing the problems that are relevant to the industry with the help of case studies. They will also be suggesting the state-of-the-art solutions of Industry-4.0 in order to address these issues sustainably!
In this webinar, we demonstrate with the help of case studies, how the power of Process Simulations and Data Analytics could be harnessed to arrive at the cost effective and profit making solutions. The problems chosen are common and most relevant to the Chemical Process Industry, and the solutions are simple and equally implementable.