Coursera - Data Science: Statistics and Machine Learning Specialization - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Coursera - Data Science: Statistics and Machine Learning Specialization (/Thread-Coursera-Data-Science-Statistics-and-Machine-Learning-Specialization--421432) |
Coursera - Data Science: Statistics and Machine Learning Specialization - BaDshaH - 05-27-2024 Last updated 5/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 166 Lessons ( 20h 47m ) | Size: 4 GB What you'll learn Perform regression analysis, least squares and inference using regression models. Build and apply prediction functions Develop public data products Skills you'll gain Github Machine Learning Data Visualization R Programming Regression Analysis 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. Applied Learning Project 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. Homepage |