Professional Certificate Program in Big Data Technologies

Duration : 3 Months

Certificate Program in Big Data Technologies

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Launch Your Career in
Data Science with IIKMBA

Professional Certificate Program in Big Data Technologies

Evolved and designed by veterans in the Analytics industry, this program prepares students and working professionals to start or improve upon a career in the growing Data and Analytics domain. A perfect blend of technology, Data science and business cases and insights, the program stands out as among the best in the world. Typically, we cover topics / technologies such as R, Hadoop, Spark, Python, Data Mining and Warehousing, statistical analysis. A great feature is the flexibility in the program to assimilate and incorporate technology updates into the modules, on the fly.


Duration : 3 Months

Class : Weekend Classroom

Eligibility Criteria:
Desirable Age: 20 - 35 years :


Graduate with any degree (mentioned below) from a recognized university with minimum of 55% aggregate

Working professionals with work experience and a graduate from a recognized university with minimum 50% aggregate in the below mentioned degrees

BE / BTech / ME / MTech / BCA / MCA
BA / MA - With Economics, Econometrics, Statistics & Mathematics
BSc / MSc - With Mathematics / Statistics as one of the subjects
BCom / MCom - With Mathematics / Statistics as one of the subjects
Any other Graduate with Mathematics/ Statistics as one of the subjects
Programming knowledge is desirable in any of the language for all the above disciplines

Course Fee: INR 50000/-

Modules : Big Data 101, Statistics 101, Hadoop, Access Methods, Big Data with Spark and Python, Python, RDBMS with SQL and DWH

Projects : Live Projects(Optional)


Course Outline

Big Data 101

Big Data Characteristics, Big Data and Business, Big Data Case Studies, Data Relationships and Data Model, Data Grouping, Clustering Algorithms, UPGMA Clustering Algorithm, Single Link Clustering Algorithm, KPIs and Businesses, KPIs and Data Elements, Mapping for business outcomes, Basic and Advanced Query.

Hadoop

Introduction to Big data and Hadoop, Hadoop Architecture, Hadoop Deployment, Hive - Introduction, Metastore, Hive data types, Partitioning and Bucketing, Mapreduce Framework , Hbase Architecture - Run models & Configuration, Hbase Cluster Deployment, Data Model, HBase Shell, Data Loading Techniques

Access Methods

Sqoop - Data import and export through Sqoop to Hive and Hbase, Flume - Introduction , Data streaming demo through Flume, PIG - Introduction, Programming structure in Pig, Running models, Data type. Apache Spark - Ecosystems, Scala programming, spark shell, spark context, RDD, Spark streaming architecture, Zookeeper

Statistics 101

Introduction to Statistics , Introduction to Statistics - II ,Measures of Central Tendency, Spread and Shape -I,Measures of Central Tendency, Spread and Shape - II ,Measures of Central Tendency, Spread and Shape - III ,Measuring Association.

Big Data with Spark and Python

Python: Data Structure, Twitter Analysis and Analytics, Text Analytics, Hadoop. Spark: Machine Learning with Spark Case Studies: Python + Spark Project: Spark.

Python

Understanding Basics of Python, Control Structures and for loop, Playing with while loop | break and continue, Strings and files, List Dictionary and Tuples.

RDBMS with SQL and DWH

Introduction to DBMS / RDBMS, Data Modelling - Entity Relationships Data Modelling - Normalization, Physical Data Model, Getting started with SQL lite, DDL (Creating Tables, Loading Data, Insert, Delete,Update) & DML, Data warehousing, Dimensional modeling.


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