In the era where industry 4.0 is the fusion of the real world with the virtual world, the digital revolution is marked by technology that takes advantage of Big Data and Artificial Intelligence (AI) to nurture automatic learning systems. In biological research and genomics, biological data, computational and data-driven platforms, and tools have gained relevance in handling the massive amount of data. The future of research and development will be governed by data to generate hindsight, insights, and foresight for better decision and process improvement.
This comprehensive webinar will delve into today’s best tools and techniques that massive data science utilize to efficiently and effectively understand outcomes from their datasets, and, capture, transform and shape their data stores with mathematical and statistical functionality from Machine Learning’s pipeline. The key of data science is simple, which is pattern with data.
We will provide an overview of the data science process: data acquisition, data preprocessing, data analysis, data modeling, validation, visualization, deployment of the model, and maintenance. These processes lead to better demystifying interconnections between AI and Machine Learning (ML), as it involves machine mimicking “intelligence human behaviors”, not only on its underlying technology but rather its different applications such as disease prediction in healthcare and crop improvement in agriculture. Join us on this journey to start exploring data science for your research!