Course Description

Course Objectives

Big Data involves itself with the compilation of unstructured data, while Data Science is all about creating value out of this data. The dual certification course offered by ExcelR trains students in this visible synergy between the macro and micro-segments of Data Analytics. Suited for freshers and professionals, the course equips one to apply the Big Data framework Apache Hadoop to extract useful data and analyze it further as a data scientist. This training is focused on providing knowledge on all the key techniques such as Statistical Analysis, most widely used Regression Analysis, Data Mining Unsupervised learning techniques These techniques will be explained using the best data science tools in the industry - R & Python.

Methodology

Lecture with a blend of theoretical & practical exposure
Hands-on exercise to reiterate the learning
Quizzes to test the understanding
Discussions & final exam to attain certificate

Who should attend

Candidates aspiring to be Big Data Analysts
Analytics Managers / Professionals, Business Analysts, Software Developer
Graduates who are looking to build a career in Big Data Administration and Machine Learning
Employees of organizations, which are planning to shift to Big Data tools
Finally – Students who are aiming to work in the IT Industry

Learning Outcome

Be able to install & setup Hadoop & Spark environment for storing and processing the data
Be able to understand the advantages of distributed batch processing using the Hadoop Distributed File System (HDFS)
Be able to understand the differences in Hadoop 1.x and Hadoop 2.x version and the advantages of latest version
Be able to perform exploratory queries on data batches using Spark, including parallel processing
Be able to understand Spark RDD optimization techniques
Be able to write programs in Big Data domain as per system architecture
Understand about the landscape of the various data generation sources
Learn about the tools & techniques used in the space of analysing both structured & unstructured data
To understand the differences between descriptive analytics & predictive analytics
Perform text mining to generate the sentiment analysis of customers
To understand the data-driven machine learning approaches in taking critical business decisions
To understand on how to build prediction models for day to day applicability
To understand on how to perform forecasting to take proactive business decisions
Learn about representing data in most representable format using data visualization concepts