Data Science With SAS Training
Data Science with SAS Training participants get the abilities necessary to use SAS (Statistical Analysis System) to evaluate, interpret, and derive insightful information from sizable datasets. Numerous data science topics are covered in the course, such as statistical modeling, machine learning, data manipulation, and data visualization with SAS tools. Participants learn how to use SAS to manage challenging data analysis problems and make data-driven decisions.
- 10+ Courses
- 30+ Projects
- 400 Hours
Data Science With SAS Training is suitable for the following target audiences:
Aspiring Data Scientists: People who want to work in data science and who want to use SAS as their primary tool for modeling and data analysis.
Statisticians and Analysts: These are professionals in statistical analysis or data analysis positions who wish to expand their knowledge of SAS for more complex data science applications.
IT and Software Professionals: IT workers who wish to focus on data science and utilize SAS to make data-based decisions.
Business analysts: In various industries, business analysts want to use SAS to conduct predictive modeling, business intelligence, and sophisticated data analysis.
Researchers and Academics: Researchers and academic professionals require SAS expertise to carry out intricate data analysis, statistical analyses, or research initiatives.
Data Scientist: Data scientists use SAS to address business challenges by analyzing big datasets, creating predictive models, and drawing conclusions.
SAS Data analyst: Managing, cleaning, and analyzing data in industries like healthcare, banking, and retail using SAS technologies.
Statistical Analyst: Using statistical techniques to improve business decision-making processes and extract useful insights.
Business Intelligence Analyst: Producing dashboards and reports with SAS to assist companies in making data-driven choices.
Business Intelligence Analyst: Data engineers are responsible for creating and managing data pipelines and making sure that data flows easily for reporting and analysis.
Industries like healthcare, finance, marketing, government, and technology are actively seeking SAS-skilled data scientists and analysts due to the high need for data science personnel. Both the USA and Canada offer competitive salaries and a growing job market for individuals proficient in SAS, positioning them for career advancement in the dynamic field of data science.
- A look at data science ideas and uses
- Getting to know the SAS environment and interface
- Setting up and using SAS Studio
- The basics of SAS programming and syntax
- Getting to know the data science process
- How to import and export data in SAS
- Making datasets and processing data steps
- Cleaning and changing data
- Dealing with missing values and duplicates
- Using SAS procedures to change data
- SAS descriptive statistics
- Statistics and data profiling
- Making reports and summaries
- The basics of data visualization
- Learning how to spot patterns and trends in data sets
- Getting started with statistical modelling
- Testing hypotheses and ideas about probability
- Using SAS for regression analysis
- Correlation study
- Using statistical methods on real data sets
- Getting to know predictive analytics
- Using SAS Enterprise Miner to make predictive models
- Models for classification and regression
- Clustering and decision trees
- Checking the model and accuracy measures
- Analysis of time series
- SAS’s methods for making predictions
- Ideas about data mining
- Tuning and optimising models
- Business analytics applications
- Getting Started with SAS Machine Learning
- Putting machine learning models into action
- Getting data ready for modelling
- Model validation and metrics for performance
- Real-world examples of machine learning
- SAS-based end-to-end Data Science project
- Analysing data and making predictions
- Case study of a real business
- Help with writing a resume and preparing for an interview
- Presentation of the final project
It’s a class that teaches you how to use SAS for data analysis, predictive modelling, and statistical methods.
This class is suitable for students, data analysts, statisticians, and individuals working in the field of Data Science.
It helps to know some programming, but beginners can also learn SAS, which is designed to be user-friendly and accessible for those without extensive programming experience.
Tools like SAS, SAS Studio, and SAS Enterprise Miner.
Yes, students do hands-on projects with real-world data sets.
The training will cover concepts in data analysis, statistical modelling, predictive analytics, and machine learning.
Data Analyst, SAS Programmer, Statistical Analyst, and Data Scientist.
Yes, SAS is used a lot in fields like healthcare, banking, and drug analytics, particularly for tasks such as data management, statistical analysis, and predictive modelling.
The course is an eight-week training program.
Yes, the class teaches you about Machine Learning and how to use SAS for predictive modelling.
We currently offer online sessions with flexible weekday/weekend batches for 8 weeks. All sessions are recorded. You’ll have access to the recordings, along with support from instructors and peers in our learning portal.
You can register via our website https://mediumblue-spoonbill-560747.hostingersite.com/, or reach out to our support teams via phone, email, or WhatsApp. We’ll help you with batch schedules and payment options.
Email info@checkmateittech.    Call us: +1-347-408-2054
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Job opportunities in USA and Canada
Data Scientist: Data scientists use SAS to address business challenges by analyzing big datasets, creating predictive models, and drawing conclusions.
SAS Data analyst: Managing, cleaning, and analyzing data in industries like healthcare, banking, and retail using SAS technologies.
Statistical Analyst: Using statistical techniques to improve business decision-making processes and extract useful insights.
Business Intelligence Analyst: Producing dashboards and reports with SAS to assist companies in making data-driven choices.
Business Intelligence Analyst: Data engineers are responsible for creating and managing data pipelines and making sure that data flows easily for reporting and analysis.
Industries like healthcare, finance, marketing, government, and technology are actively seeking SAS-skilled data scientists and analysts due to the high need for data science personnel. Both the USA and Canada offer competitive salaries and a growing job market for individuals proficient in SAS, positioning them for career advancement in the dynamic field of data science.
