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Coursera - Data Analysis and Interpretation Specialization
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Coursera - Data Analysis and Interpretation Specialization
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 126 Lessons (13h 20m) | Size: 5.5 GB



Learn Data Science Fundamentals. Drive real world impact with a four-course introduction to data science


SKILLS YOU WILL GAIN
Statistics
Data Analysis
Machine Learning
Regression Analysis
SAS Language
Python Programming
Data Management
Chi-Squared (Chi-2) Distribution
Statistical Hypothesis Testing
Analysis Of Variance (ANOVA)
Logistic Regression
Exploratory Data Analysis
About this Specialization
4,049 recent views
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.


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