Data Science Using Python Syllabus
- Introduction to R
- Data Structures in R
- Working with Data
- Different Functions in R
- Working with Text and Date
- Descriptive Statistics in R
- Inferential Statistics in R
- Cleaning the Data
- Creating Data Visualization
- Creating Statistical Models
- Supervised Learning
- Unsupervised Learning
- Recommender System
- Machine Learning Algorithm
- Deploying to Production
- Big Data and Hadoop Introduction
- Understand Hadoop Cluster Architecture
- Map Reduce Concepts
- Advanced Map Reduce Concepts
- Hadoop 2.0 and YARN
- Introduction to PIG
- Working with Pig
- HIVE
- HBASE
- SQOOP
- Flume and Oozie
- Apache Spark
- Introduction to Scala
- Spark Core Architecture
- Spark Internals
- Spark Streaming
- Getting Acquainted with Power BI
- Creating Datasets from Data Models and Data files
- Demo: Getting Started with Power BI
- Using Quick Insights to Explore a Dataset
- Demo: Using Quick Insights
- Viewing Reports
- Exploring Dashboards
- Using Power BI desktop
- Modelling Data for Analysis
- Enhancing the Data Model
- Introduction to SQL
- Datatypes and Commands
- Operators/Alias Name
- Views
- Stored Procedure
- Trigger/Cursor
- Functions
- Pivot/Unpivot
- Database Backup
- Database Restore
- Generate Script
- Select * into
Tools Covered
