What will you learn in this Data Science: Statistics and Machine Learning Specialization Course
Statistical Inference: Understand the process of drawing conclusions about populations or scientific truths from data.
Regression Models: Perform regression analysis, least squares, and inference using regression models.
Machine Learning: Build and apply prediction functions, understanding concepts such as training and test sets, overfitting, and error rates
Data Product Development: Develop public data products and create interactive data visualizations.
Capstone Project: Apply the skills learned to build a data product using real-world data.
Program Overview
1. Statistical Inference
⏳ 54 hours
Learn to make informed data analysis decisions using p-values, confidence intervals, and permutation tests
2. Regression Models
⏳ 53 hours
Understand ANOVA and ANCOVA model cases, and investigate analysis of residuals and variability.
3. Practical Machine Learning
⏳ 8 hours
Cover the basic components of building and applying prediction functions with an emphasis on practical applications.
4. Developing Data Products
⏳ 10 hours
Create interactive data visualizations and develop data products that tell a story to a mass audience.
5. Data Science Capstone
⏳ 5 hours
Build a data product using real-world data, demonstrating mastery of the material.
Get certificate
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Job Outlook
Equips learners for roles such as Data Analyst, Data Scientist, and Machine Learning Engineer.
Provides foundational skills applicable in industries like finance, healthcare, marketing, and technology.
Enhances employability by teaching practical skills in data analysis and machine learning.
Specification: Data Science: Statistics and Machine Learning Specialization
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