DSBDA – Data Science and Big Data Analytics v2

Module 1 – Introduction to Big Data analytics

• Big Data and its characteristics Lesson
• Business value from Big Data
• Data scientist

Module 2 – Data Analytics Lifecycle

• Data analytics lifecycle overview
• Discovery phase
• Data preparation phase
• Model planning phase
• Model building phase
• Communicate results phase
• Operationalize phase

Module 3 – Basic data analytics methods using R

• Introduction to the R programming language
• Analyzing and exploring data
• Statistics for model building and evaluation

Module 4– Advanced analytics theory and methods

• Introduction to advanced analytics—theory and methods
• K-means clustering
• Association rules
• Linear regression
• Logistic regression
• Text analysis
• Naïve Bayes
• Decision trees
• Time series analysis

Module 5 – Advanced analytics—technology and tools

• Introduction to advanced analytics—technology and tools
• Hadoop ecosystem
• In-database analytics SQL essentials
• Advanced SQL and MADlib

Module 6 – Putting it all together

• Preparing to operationalize
• Preparing project presentations
• Data visualization techniques