This hands-on course teaches learners how to prepare, analyze, and visually interpret data using Python’s Seaborn library, with a focus on census datasets. Beginning with foundational setup—such as installing Anaconda, configuring Jupyter Notebook, and loading libraries—the course progresses into exploratory data analysis and practical visualization techniques. Learners will … [Read more...] about Seaborn Setup: Tools, Data Prep & EDA for Visualization
Data Science
Foundations of No-Code AI for Real-World Applications
Unlock the essentials of AI development without programming. Learn to use no-code platforms to build, configure, and launch AI applications that solve real business problems in diverse sectors. Explore fundamental machine learning principles, ethical data practices, and methods for creating user-centric interfaces. Designed for ambitious learners in India, the USA, and … [Read more...] about Foundations of No-Code AI for Real-World Applications
Introduction to Transformer Models for NLP: Unit 2
This course covers the fundamentals and advanced applications of BERT and GPT models. You will learn how BERT processes text, including tokenization and vectorization, and practice fine-tuning BERT for tasks such as sequence classification, token classification, and question answering. The course also explains how GPT generates text, adapts to different writing styles, and can … [Read more...] about Introduction to Transformer Models for NLP: Unit 2
Excel: Apply & Evaluate Unsupervised Clustering
This hands-on course empowers learners to apply, analyze, and evaluate unsupervised learning techniques—specifically clustering—using Microsoft Excel. Designed for learners with basic Excel knowledge, the course walks through the entire data clustering pipeline: from preparing and structuring datasets to building and refining logic-based cluster assignments. Learners begin by … [Read more...] about Excel: Apply & Evaluate Unsupervised Clustering
Seaborn Python: Visualize & Analyze Data Distributions
This intermediate-level course is designed to help learners analyze, visualize, and interpret data distributions using the powerful Seaborn library in Python. Building upon foundational knowledge of data visualization, the course takes a hands-on approach to explore univariate and bivariate distributions, apply linear and polynomial regression models, and demonstrate advanced … [Read more...] about Seaborn Python: Visualize & Analyze Data Distributions
