From Shared Foundations to Advanced Specialist Skills
The NTAI data-centric and AI training programs share a few “core” courses from data science, upon which each specialized program is built. Data analytics, data science, data engineering, and AI share a common data lifecycle, with skills and knowledge shared across that lifecycle. The shared data lifecycle starts by applying the scientific method to data to formulate some clear questions that data can answer. With key questions clearly articulated, the next steps are to capture, clean, and prepare data, explore and analyze those data, and decide how they might best answer the questions at hand. Common follow-on steps to create data models and algorithms, build databases, design and build visualizations. Data feature engineering is often applied, supervised and unsupervised learning tools may be used, and neural networks or deep learning tools may be applied. Once the analytics or AI applications are working acceptably, additional testing and optimization are done. Advanced data scientist or data engineering specialist skills weigh in at this stage to create data pipelines and scale the entire application, and the smart applications are put into production. Advanced analytics and Artificial Intelligence applications are built using these tools and foundations.
Where Do NTAI Graduates Work?
Graduates are prepared for exciting new careers in data-driven analytics, intelligent decision making, and innovation science. NTAI graduates emerge from their training as leaders, drivers, and support specialists in these fields. Our data science and AI specialists work throughout science, engineering, IT, business, marketing, manufacturing, medicine, healthcare, finance, insurance, social science, and elsewhere.