This course provides an overview of the health insurance industry, covering fundamental concepts such as insurance plans, coverage models, and reimbursement processes. Participants will learn about key stakeholders, regulatory frameworks, and the role of insurers in healthcare. The course also explores risk management, cost-sharing mechanisms, and common terminologies. By the...

Course Overview Designed for beginners, this course introduces Python programming with a focus on healthcare applications. Participants will learn core programming concepts such as variables, loops, functions, and data structures. Real-world healthcare scenarios, including data processing, automation, and simple analytics, will be used to reinforce learning. By the end of...

Course Overview This course covers essential data wrangling techniques to clean, transform, and analyze real-world datasets using Python. Participants will work with libraries such as Pandas and NumPy to handle missing data, reshape datasets, and perform exploratory analysis. Practical exercises will focus on healthcare data, enabling students to extract meaningful...

Course Overview (in progress) This course introduces Power BI as a powerful tool for business intelligence and healthcare analytics. Participants will learn to connect, visualize, and analyze healthcare data using interactive dashboards and reports. Topics include data modeling, DAX calculations, and best practices for storytelling with data. By the end...

Course Overview This course provides a hands-on introduction to machine learning and AI using Python. Participants will learn key concepts such as supervised and unsupervised learning, model evaluation, and feature engineering. The course covers popular libraries like Scikit-Learn and TensorFlow, with practical applications in healthcare and business. By the end...

Course Overview This course covers the principles of Agile project management tailored for AI and data science teams. Participants will explore Agile frameworks such as Scrum and Kanban, along with key roles, ceremonies, and artifacts. The course emphasizes best practices for managing AI projects, ensuring iterative development, collaboration, and adaptability...

Course Overview This course explores the ethical implications of AI and data science in healthcare. Participants will learn about bias in AI models, patient privacy concerns, regulatory compliance, and responsible AI practices. Case studies will highlight real-world ethical dilemmas and solutions. By the end, students will be equipped to navigate...

Course Overview This course provides an introduction to deep learning and its applications using Python. Participants will learn the fundamentals of neural networks, activation functions, and training deep learning models. Using frameworks like TensorFlow and PyTorch, students will implement models for tasks such as image recognition and NLP. By the...

Course Overview (in progress) Introduction to Supervised Machine Learning in Python is a beginner-friendly course designed to help learners understand the fundamentals of supervised learning_. It covers key concepts such as classification and regression, exploring how models are trained using labeled data. The course introduces essential algorithms like linear regression, decision...

Course Overview Get the crucial data analysis and visualization skills you need for any data job. You will learn the fundamentals of Python to prepare, explore, analyze and build data visualizations. By the end, you’ll be able to convey insightful stories and help make data driven decisions. Key Skills Programming...

Course Overview This course introduces the fundamentals of prompt engineering, a critical skill for optimizing interactions with AI models like ChatGPT and other LLMs. Participants will learn techniques to craft effective prompts, structure queries for desired outputs, and fine-tune responses using contextual cues. The course covers best practices, ethical considerations...