What you will learn
The program offers a comprehensive curriculum covering key areas in data science and artificial intelligence (AI). Participants will gain expertise in data analysis, machine learning, computer vision, natural language processing, and big data technologies. This knowledge empowers them to address data-related challenges, make data-driven decisions, and implement practical solutions in real-world applications
Data Science and Analysis
- This course provides a comprehensive introduction to data science and analysis techniques. Participants will learn the fundamental concepts and methods used in data analysis, data visualization, and statistical modeling. The course focuses on practical experience with realworld data sets and the use of popular data tools and libraries. By the end of this course, participants will be able to address data-related challenges, contribute to data-driven strategies, and effectively communicate complex findings to both technical and non-technical
Applied Machine Learning
- Machine Learning has revolutionized various industries by enabling computers to learn patterns and make predictions or decisions from data. This course on Applied Machine Learning aims to provide participants with a comprehensive understanding of machine learning
algorithms, techniques, and their practical applications. The course will cover both supervised and unsupervised learning, as well as delve into advanced topics such as neural networks and deep learning. Participants will gain hands-on experience by working with popular machine learning libraries and implementing models using Python.
Image Analysis and Computer Vision
- This course is an introduction to the areas of Artificial Intelligence that deal with fundamental issues and techniques of computer vision and image processing. The focus is on the fundamental concepts and methods used in image processing, feature extraction, object detection, and image recognition. The course emphasizes practical implementation, algorithm implementation, and realworld applications of computer vision.
Natural Language Processing and Language Modeling
- This course explores the major challenges of working with written language data, basic techniques used in natural language processing, and basic applications of NLP technology. This course constitutes a thorough introduction to the Large Language Model technology, tracing the historical threads in computational linguistics and language modeling that led to it, and exploring the design patterns that underpin its application in modern AI systems. Through this course, particular interest will be given to NLP case studies by exploring applications such as : Machine translation, Text summarization, Chatbots and Sentiment analysis.
Big Data Systems and Technologies
- This course provides an in-depth overview of Big Data systems and technologies. Participants will learn more about the basic concepts, architectures and technologies used in handling and managing big data. The course focuses on how to apply technologies such as Hadoop,
MongoDB and various NoSQL databases to build simple, robust and efficient systems for handling and analyzing big data. The aim is to guide the participants through the principles of big data systems and how to operate them once they are deployed.