Data Analysis using SAS Progarmming
Earn certification, gain practical skills, and advance your career with job placement assistance and networking opportunities. Join our vibrant learning community and stay ahead in the world of data-driven decision making
Description
This comprehensive course is designed to equip participants with the essential skills and knowledge required to excel in the field of Data Analysis and programming. From foundational concepts to advanced techniques, participants will learn how to leverage various tools and programming languages to analyze data, derive insights, and make informed decisions.
Throughout the course, participants will delve into the fundamentals of Data Analysis, gaining hands-on experience with industry-leading tools and programming languages such as Python, SQL, and Tableau. From data manipulation and visualization to machine learning and big data analysis, this course covers a wide array of topics to equip participants with the skills and knowledge needed to excel in the rapidly evolving field of Data Analysis.
Whether you're a beginner looking to break into the field or a seasoned professional aiming to upskill, Jagan will help you achieve your goals and unlock your full potential in the world of Data Analysis and programming.
What you'll learn
Master essential Data Analysis techniques for informed decision-making.
Gain proficiency in Python programming for data manipulation and analysis.
Understand SQL fundamentals for database querying and management.
Build & test a full website design.
Create impactful visualizations using Tableau for data-driven storytelling.
Explore advanced statistical analysis and hypothesis testing methods.
Develop machine learning models for predictive analytics and pattern recognition.
Dive into big data technologies like Hadoop for scalable data processing.
Apply data cleaning and preprocessing techniques to ensure data quality.
Utilize clustering and classification algorithms for data segmentation and categorization.
Learn data visualization best practices to effectively communicate insights.
Prepare for a rewarding career in Data Analysis, business intelligence, or data science.
Requirements
- No prior programming experience required, but a willingness to learn programming concepts is beneficial.
- Basic understanding of mathematics and statistics concepts.
- Commitment to continuous learning and self-improvement in the field of Data Analysis and programming.
Course Content
Learn from industry experts with years of practical experience in data analysis, programming, and visualization.
- Day 1-3 Reading raw data, Basic SAS programming, Datatypes, Accessing data drom different sources ,Libraries, Statements, Types of input statement and modifiers
- Day 4- 5 Data Step Processing
- day 5 - 6 Data Manipulation
- Day 7 Combining SAS DataSet Concatenation, Interleaving, Merging
- Day 7 - 11 By Group Processing
- Day 12-15 Functions - Numeric Functions, Character Functions, Date and Time Functions, Nesting SAS Functions Day 15 - 20 - By Group Processing Functions - Numeric Functions, Character Functions, Date and Time Functions, Nesting SAS Functions Conditional Statements Do Loop Where Conditions Arrays
-
Procedures sort, means, summary
Procedures print, Freq, Transpose
Procedures Datasets, Printto, Summary
Procedures Tabulate, Report, Format
Import and export procedures, ODS
Proc SQL
Macro Programming
Advanced SAS Programming Techniques
User defined functions, Proc Format
Combining data Horizontally, Accessing observations
Data Step hash and hilter objects
Data Step Arrays
Revision and Sharing Dumps and Materials
-
Analytics overview
Descriptive statistics
Descriptive statistics
Population and sampling - Difference between population and sample,Sampling Techniques
Central limit theorem
Normality distribution
Explorate data analysis
Explorate data analysis
Data Visualization
Missing value treatment and outliers removal
Hypothesis testing
TTEST - ONE sample
Ttest - Two Sample
Anova-1
Anova-2
Proc corr
Regression
Regression - Model Buidling
Regression - Model evaluation
Logistic regression
Logistic regression - Predictive Modelling
Logistic Regression - Model Buidling
Logistic regression - Model evaluation
Instructor
Jagananathan
Data Analytica & SAS Expert Trainer
Jagan's passion for teaching and commitment to student success make him a standout instructor at JS Analytics. His ability to simplify complex concepts, coupled with his patient demeanor and hands-on teaching style, ensures that students feel supported every step of the way. Whether you're a beginner looking to break into the field or a seasoned professional aiming to upskill, Jagan will help you achieve your goals and unlock your full potential in the world of Data Analysis and programming.
Over the years, he expanded his expertise to include programming languages such as SAS and Python, mastering the art of data manipulation and machine learning algorithms.
Agalya 7 Days ago
The best Data Nalytics Course
"As someone with a background in programming, I was eager to learn Python for data analysis. I enrolled in JS Analytics' Data Analysis using Python course, and it was everything I hoped for and more. The instructors were experts in their field, and the course content was comprehensive yet easy to follow. The hands-on projects were particularly enjoyable and allowed me to apply what I learned in real-world scenarios. I can't recommend this course enough to fellow Python enthusiasts!"
Shakivel 3 Days ago
The best Data analysis Course
"JS Analytics' Advanced Excel course was exactly what I needed to take my Excel skills to the next level. The course covered advanced formulas, functions, and data analysis techniques that have proven invaluable in my day-to-day work. The instructors were patient and provided personalized feedback, and the course materials were well-structured. Whether you're a beginner or an experienced Excel user, this course is sure to enhance your skills and productivity."