Complete & Practical SAS, Statistics & Data Analysis Course

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Обучение платное
Сертификация бесплатная
16.5 часов курса
О курсе

You should take this course! 

• If you need a complete and comprehensive package that covers SAS programming, intuitive statistics interpretation, data analysis, and predictive modeling, and

• If you would like to learn by doing various practical use cases fitting in the positions in different business portfolios, and

• Whether you are a job seeker or beginner intending to start a data science career

Then this around 18 hours course is right for you!

This complete SAS course includes more than 150 lectures and contains 11 real world case studies/projects in different applied areas such as banking and marketing. After this intensive training, you will be equipped with a powerful tool for the most sexy data analytics career path!

This complete SAS training covers 108 lectures and 11 real case studies in different applied areas. After this training, you will be equipped with a powerful tool for data analytics career path!
What are you going to learn from this course
This tutorial describes what are you going to take away from this complete training for job seekers and beginners
SAS environment and basic concepts
You will learn the basic SAS environment to start with. Learn library and first SAS program
Introduce SAS environment
We will learn key windows under SAS environment
SAS library
Learn concepts about SAS library 
Try SAS codes
Learn SAS environment, library and data creating by running SAS program 
Home work and data installation
This is a guide to let you know how to set up homework. A zipped file (resource) is provided in this session
SAS Cloud Version
Introduction to SAS Studio Installation on University Edition
Show how to install and run SAS Studio onUniversity Edition
Get started SAS programming
In this lecture we learn, what are major operations in SAS; how to create data sets; data types and formats; SAS data mechanism and naming rules
Create data sets from external files
Learn how to create SAS data sets from external files such as .TXT and .CSV. 
SAS program - create data sets
In this lecture, we will learn how a SAS program is running and generate physical data sets.
  • Basic computer operational skills.
  • Basic math skills.
  • Data intuition
Что Вы изучите?
  • Be equipped with a powerful tool for the most sexy data analytics career path!
  • Read and write various types of raw data with different formats and options
  • Create and modify various professional and statistical reports
  • Be aware of statistical analysis and concepts such as non parametric test, interaction, correlation..
  • Master the most complete SAS graphics tool such GTL and statistical plots
  • Learn comprehensive SAS Macro programming knowledge -- variables and user defined functions
  • Perform many real world case studies -- retail banks, credit bureau, marketing firms and clinical trials
  • Apply powerful data manipulation -- SQL, subsetting, slicing, filtering, transformation, ranking, sorting..
  • Understand data management and data piping
  • Use SAS ODS -- help deliver many useful objects such as charts, tables between different systems
  • Hundreds of SAS sample codes to explain arrays, functions and business cases
Shenggang Li
Shenggang Li
Senior Data Scientist

Having successfully led the development of cutting-edge risk models using Big data at multiple major financial institutions and excelled in the advanced analytics field for the past 15 years, I am very enthusiastic at transferring  knowledge and skills to the job seekers and new comers in the field of data analytics and application to business.

I hold a PhD in Statistics and operational research. I am also a passionate educator, teaching as a principal instructor of a Toronto-based college, including advanced SAS data mining, Python & R for data science and machine learning and Big data analytics foundation and projects and  for over 10 years. As a result, I have helped many of my students land their dream jobs in advanced analytics.

I am also a Big data experts in machine learning, predictive modelling and retail/marketing analytics in Canada. My work includes but not limited to: implementation of Big data analysis for credit bureau, model vetting and validation for banking capital market, and customers attrition and life stage/life style segmentation for retail banks as well as big market firms. I also worked closely with senior executives and Big data architects in the field of health science to provide strategic advice. 

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