Data Science: Statistics and Machine Learning
About this course
Build models, make inferences, and deliver interactive data products. This specialization continues and develops on the material from the Data Science: Foundations using R specialization. It covers statistical inference, regression models, machine learning, and the development of data products. In the Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, learners will have a portfolio demonstrating their mastery of the material. The five courses in this specialization are the very same courses that make up the second half of the Data Science Specialization. This specialization is presented for learners who have already mastered the fundamentals and want to skip right to the more advanced courses.
90/100
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- What the provider tells you
- 39/45
- Who stands behind it
- 35/35
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- 16/20
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What you'll learn
- Conduct statistical inference to draw conclusions from data
- Build and evaluate regression models for prediction and analysis
- Apply machine learning algorithms to real-world datasets
- Develop interactive data products that present analytical findings
- Complete a capstone project using real-world data for a portfolio demonstration
Course objectives
- Master statistical inference techniques for data-driven decision making
- Develop proficiency in building and interpreting regression models
- Gain practical experience applying machine learning methods
- Learn to create data products that deliver insights to stakeholders
- Build a portfolio project demonstrating end-to-end data science skills
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