Data Science with R

• Fundamentals of R programming
• Data manipulation with dplyr and tidyr
• Data visualization using ggplot2
• Statistical analysis and hypothesis testing
• Machine learning with R

SAS programming

• SAS function, tables, Schemas
• Data cleaning and analysis with SAS
• Statistical analysis with SAS procedures
• Creation of reports and graphics

Concepts on Big data

• Conceptual understanding of Big Data
• Big Data technologies and ecosystems
• Data processing and storage techniques
• Big Data analytics and applications

Big Data Modelling

• Understanding of Big Data modeling techniques
• Application of predictive analytics in Big Data
• Hands-on experience with Hadoop
• Designing and implementing Big Data solutions

Data Analyst with SQL

• SQL queries and RDBMS foundation
• Data manipulation with SQL
• Joining and aggregating data
• Writing subqueries and CTEs

Hands-On Essentials: Data Warehouse

• Create, edit, and load snoflake Tables
• Create and Use Snowflake resources
• Create and edit COPY statements
• Transform and parse CSV and JSON data