Week 2 | Module 2A | Introduction to Python I

Instructor: Moussa Doumbia, Ph.D. This introductory course will be your guide to learning how to set up the working environment and use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms. In this module, you will be introduced to Python programming skills and the related libraries for accessing from multiple sources. […]

Week 3 | Module 2B | Introduction to Python II

Instructor: Moussa Doumbia, Ph.D. The module builds upon Introduction to Python I. Topics we include: Web scraping with python Use matplotlib and seaborn for data visualizations Use plotly for interactive visualizations

Week 3 | Module 2B | Introduction to Python II

Instructor: Moussa Doumbia, Ph.D. The module builds upon Introduction to Python I. Topics we include: Web scraping with python Use matplotlib and seaborn for data visualizations Use plotly for interactive visualizations

Week 4 | Module 3A | Experimentation in Data Science (A/B Testing and Statistical Analyses) I

Instructor: Roland Doku, Ph.D. This topic covers the principles and applications of A/B testing, a foundational technique for making data-driven decisions in healthcare, business and various other industries. The session will focus on hypothesis testing, including the formulation of null and alternate hypotheses, and how they apply to experimental design. Attendees will learn about statistical […]

Week 4 | Module 3A | Experimentation in Data Science (A/B Testing and Statistical Analyses) I

Instructor: Roland Doku, Ph.D. This topic covers the principles and applications of A/B testing, a foundational technique for making data-driven decisions in healthcare, business and various other industries. The session will focus on hypothesis testing, including the formulation of null and alternate hypotheses, and how they apply to experimental design. Attendees will learn about statistical […]

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