Complete & Practical SAS, Statistics & Data Analysis Course
A complete guide and use cases study for job seekers and beginners -- start career in SAS, Statistics and Data science
Ratings 4.10 / 5.00
What You Will Learn!
- 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
Description
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!
Who Should Attend!
- Beginners or job seekers interested in learning SAS Programming, statistical and data analysis in industry fields.
- People who wish to enter data science/analytics field.
