Coursera - Data Science: Statistics and Machine Learning Specialization

[LeeAndro]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 166 Lessons (20h 47m) | Size: 4 GB

Perform regression analysis, least squares and inference using regression models.​

Build and apply prediction functions

Develop public data products

Understand the process of drawing conclusions about populations or scientific truths from data

Machine Learning
Github
R Programming
Regression Analysis
Data Visualization (DataViz)
Statistics
Statistical Inference
Statistical Hypothesis Testing
Model Selection
Generalized Linear Model
Linear Regression
Random Forest

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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.

Each course in this Data Science: Statistics and Machine Learning Specialization includes a hands-on, peer-graded assignment. To earn the Specialization Certificate, you must successfully complete the hands-on, peer-graded assignment in each course, including the final Capstone Project.

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