This course explores the fundamentals of relational databases and how to seamlessly map Python data structures to robust database tables using object-relational mappers (ORMs). You'll gain practical experience in building efficient ETL (Extract, Transform, Load) pipelines, ensuring your data is not only accessible but also reliable and persistent. You'll learn about data … [Read more...] about Data Science Fundamentals Part 1: Unit 3
Data Science
SPSS: Apply & Interpret Logistic Regression Models
This course provides a practical and applied introduction to logistic regression and supervised learning using IBM SPSS Statistics. Designed for learners seeking to build analytical skills in predictive modeling, the course emphasizes both conceptual understanding and tool-based execution. Through step-by-step instruction, learners will identify key components of logistic … [Read more...] about SPSS: Apply & Interpret Logistic Regression Models
Learning Deep Learning: Unit 3
This course covers key deep learning architectures such as BERT and GPT, focusing on their use in applications like chatbots and prompt tuning. You will learn how to build models that combine text and images, and generate text from visual data. The course also addresses multitask learning and computer vision tasks, including object detection and segmentation, using networks … [Read more...] about Learning Deep Learning: Unit 3
Modern Data Strategy for Enterprise Generative AI
The Modern Data Strategy for Enterprise Generative AI program offers a comprehensive journey along three courses—Data Frameworks for Gen AI, Advanced Data Techniques for Enterprise AI Systems, and Data Lineage & Ethical Frameworks for Responsible AI. This specialized program is designed to equip professionals with the right skills and knowledge with respect to modern data … [Read more...] about Modern Data Strategy for Enterprise Generative AI
Data Science Fundamentals Part 1: Unit 1
This course demystifies core data science concepts and techniques through engaging Python lessons and real datasets. You’ll gain practical experience working with the Python ecosystem, including pandas, NumPy, scikit-learn, and more, as you analyze authentic data and build meaningful applications from scratch. From setting up your programming environment to building your first … [Read more...] about Data Science Fundamentals Part 1: Unit 1
