105 Data Science Preparatory Programs

Harness analytics to make more informed investment decisions.

The Seasonal School intends to offer a multi- and inter-disciplinary learning and training experience on the main tools, methodologies, solutions, and present/future challenges that concern the technological, socio-economic, legal, and healthcare issues arising in the so-called Digital Health domain.

Data is everywhere—from e-commerce sales, app downloads to a smartphone, to supply chain management or bioinformatics or connected devices. And that massive increase in the amount and variety of data being collected is translating to an exponential growth in the computer power needed to process that data.

The Certificate in Data Science is intended for students who possess a Bachelor of Science in a Science, Technology, Engineering, or Mathematics (STEM) field, but who lack sufficient background in Data Science to be admitted to the Master of Science in Data Science.

Data Science is continually ranked as one of the most in-demand professions. The need for professionals who can manage and leverage insights from data is clearer than ever before. The curriculum taught in this program is designed to meet the expanding multi-disciplinary needs of data professionals. By covering a wide array of topics, the program addresses the wide variety of skills needed to work on successful data-based projects. Topics covered include data-driven discovery and prediction, data engineering at scale (inspecting, cleaning, transforming, and modeling data), structured and unstructured data, computational statistics, pattern recognition, data mining, data visualization, databases, SQL, Python programming, and machine learning. UC Irvine’s 3-month post-graduate level Accelerated Certificate Program (ACP) in Data Science covers a wide array of topics in data science including data-driven discovery and prediction, data engineering at scale (inspecting, cleaning, transforming, and modeling data), structured and unstructured data, computational statistics, pattern recognition, data mining, data visualization, databases, SQL, Python, and machine learning.

Data science is changing how we understand and study politics, policy, and decision-making. This course introduces students to the fundamental tools of data science, including collecting, modeling, and visualizing data, and how to apply these tools to study political and policy questions.

A hands-on introduction to the methods of principles of data science. Strategies for analyzing and visualizing tabular data, including common patterns and pitfalls. Data acquisition through web scraping and REST APIs. Core principles of machine learning: supervised vs. unsupervised learning, training vs. test error, hyperparameter tuning, and ensemble methods. Introduction to data of different shapes and sizes, including text, image, and geospatial data.

The aim of the Summer School ‘Data Science and AI in Health’ is to introduce young, enthusiastic researchers to the principles of data science and AI in healthcare and clinical research. Participants will be introduced to various aspects of data science, such as setting up and implementing a project. This includes both the collection and cleaning of data and the practical conduct of an initial (machine learning) analysis of the collected data.

In Data Science and Artificial Intelligence in Marketing. Gain cutting-edge skills to revolutionize marketing strategies with data-driven insights and AI innovations. Our comprehensive course covers the dynamic intersection of data science, AI, and marketing, equipping you to elevate customer experiences and drive success in today’s business landscape.

CentraleDigitalLab is a post-graduate program of excellence, specializing in computer science and dedicated to the digital transformation of companies. CentraleDigitalLab and 3IA Côte d'Azur join forces to offer a high-level professional training program in Artificial Intelligence and Data Science.

In DS Inno - Data Science Driven Innovation in Business and Society Seasonal School aims to examine the relationship between innovation management and data science through a multi-level approach. First, this relationship will be explored at the company level through not only theoretical knowledge but especially through firsthand testimonials and site visits to large and small enterprises.

Data governance is about the convergence of data quality, data management, data policies, business process management, and risk management around the handling of data within an organization.

This program is of interest to anyone who wants to use the powerful capabilities of relational databases in conjunction with the new "Big Data" management frameworks for data storage and retrieval, and for data analysis in support of management decision-making. Data architects, data analysts, database administrators, and information technology staff members can all benefit from this program.

The current digital transition of companies is bringing significant changes to information systems (security, data access, cloud computing, Artificial Intelligence) and new uses of IT (BYOD, teleworking, etc.). CESI engineers use their technical and scientific skills in this environment to successfully carry out IT projects that meet these new requirements.

Machine Learning and Natural Language Processing define the current state of the art of Artificial Intelligence. These technologies, which are a form of data mining and data analysis, continuously learn from the provided information.

In today’s world, there is a growing shortage of industrial data communications and industrial IT engineers, technologists and technicians. This is due to new technologies taking centre stage in modern plants, factories and offices. This course provides you with a thorough understanding of modern industrial data communication technologies underpinned by practical, hands-on experience and expertise from our global industry experienced instructors.