Data Science & AI Foundations
The Data Science & AI Foundations course offers a comprehensive introduction to the key concepts and techniques in data science and artificial intelligence. Students will explore essential topics such as data wrangling, exploratory data analysis, and much more. This foundational course provides the necessary skills to understand and implement basic algorithms and prepares students for more advanced studies in the field.
Statistical Methods for Decision Making
In the Statistical Methods for Decision Making course, students learn how to apply statistical techniques to make informed business decisions. The curriculum covers fundamental concepts such as descriptive statistics, probability theory, and hypothesis testing. Students will gain hands-on experience with regression analysis, enabling them to analyze data effectively and derive actionable insights for strategic decision-making.
Foundations of Generative AI
The Foundations of Generative AI course introduces students to the principles and techniques of generative models, which are pivotal in creating new and synthetic data. Students will explore various generative approaches and this course provides a solid understanding of how models work and their applications in generating realistic data and content.
Business Intelligence with Power BI
Business Intelligence with Power BI equips students with the skills to transform data into insightful visualizations and interactive reports. The course covers key features of Power BI, including data import, transformation, and visualization. Students will learn to create dynamic dashboards that facilitate data-driven decision-making, using best practices to present complex information in a clear and actionable manner.
Deep Learning & Neural Networks
The Deep Learning & Neural Networks course dives into advanced techniques for building and training neural networks. Students will explore the architecture and functioning of various neural networks, including feedforward, convolutional, and recurrent networks. The course emphasizes practical aspects such as model optimization and regularization, preparing students to tackle complex problems and deploy state-of-the-art deep learning solutions.
Python for AI & ML
Python for AI & ML is a critical module that delves into programming skills required for developing AI and machine learning applications. Students will become proficient in using Python libraries such as NumPy, Pandas, and Scikit-Learn to build and train machine-learning models. The course also covers best practices in coding, debugging, and model evaluation, ensuring that students are well-prepared to handle the technical aspects of AI development.