When it comes to using data, there are two main camps, traditional statistics and machine learning, and the two camps complement each other. Statistics remains highly relevant, irrespective of the size of data. Its role remains what it has always been, but it is even more important now. There is a need to transition from traditional statistical modeling to the machine learning world. This course introduces the statistical background necessary for machine learning. Knowledge of statistics relevant to machine learning will prepare you to become a data scientist. The course prepares you for future instruction on machine learning (including its underlying methodology that has statistical foundations) and enables you to develop a deeper understanding of machine learning models.
This course is aimed at anyone in the field of data science who does not yet have a deep understanding of statistical and machine learning concepts or wants to enhance their knowledge, which might include business analysts, data analysts, marketing analysts, marketing managers, data scientists, data engineers, financial analysts, data miners, statisticians, mathematicians, and others who work in allied areas.
In this module, you learn how to explain the relevance of statistics in big data and machine learning and relate statistical and data science terminology.
涵盖的内容
19个视频8篇阅读材料8个作业1个应用程序项目
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19个视频•总计52分钟
Welcome to the Course•2分钟
Overview•1分钟
Data and Digital Economies•5分钟
Big Data Produced Smart Applications•8分钟
Knowing Statistics (1)•0分钟
Knowing Statistics (2)•1分钟
Relevance of Statistics in Big Data•3分钟
Transitioning to the Machine Learning World•1分钟
Analyzing Data•1分钟
Statistical Modeling: The Two Cultures•2分钟
Modeling Approaches•4分钟
Why Is Statistics Important to Machine Learning?•2分钟
Journey from Statistics to Machine Learning•2分钟
Basic Terminology•5分钟
Variable Type and Level of Measurement•7分钟
Modeling Vocabulary•6分钟
Introduction to SAS Viya•1分钟
SAS Viya Servers•1分钟
Introduction to SAS Studio and SAS Studio Flows•3分钟
8篇阅读材料•总计80分钟
Data Dictionary•10分钟
Using SAS Viya for Learners with This Course (Required)•10分钟
What Is Big Data?•10分钟
Demo: Automated Machine Learning in SAS Studio•10分钟
More about the Relevance of Statistics in Big Data•10分钟
More about the Journey from Statistics to Machine Learning•10分钟
More about SAS Viya•10分钟
Lesson Summary•10分钟
8个作业•总计240分钟
Question: Big Data•30分钟
Question: Computer Vision•30分钟
Question: Modeling Cultures•30分钟
Question: Basic Terminology (1)•30分钟
Question: Basic Terminology (2)•30分钟
Question: Measurement Scales•30分钟
Question: Modeling Vocabulary•30分钟
Question: SAS Viya•30分钟
1个应用程序项目•总计60分钟
Access SAS Viya for Learners•60分钟
Fundamental Statistical Concepts
第 2 单元•小时 后完成
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In this module, you learn about fundamental statistical concepts.
涵盖的内容
36个视频9篇阅读材料17个作业
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36个视频•总计70分钟
Overview•1分钟
Populations and Samples•2分钟
Process of Statistical Analysis•2分钟
Sampling•1分钟
Sampling Methods•3分钟
Event-Based Sampling•7分钟
Analysis Data•2分钟
Analysis Goals•1分钟
Describing Your Data•2分钟
Measures of Central Tendency•1分钟
Measures of Position•1分钟
Measures of Dispersion•4分钟
Visualizing Distributions•0分钟
Histograms•1分钟
Normal (Gaussian) Distribution•2分钟
Usefulness of Normal Distribution in Machine Learning•1分钟
Plots beyond Histograms•2分钟
Measures of Shape: Skewness•3分钟
Measures of Shape: Kurtosis•5分钟
Usefulness of Distribution Analysis in Machine Learning•1分钟
Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
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What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.