IBM - Big Data Analytics Professional Program Online Course

IBM - Big Data Analytics Professional Program

All levels
English

Course Description

In the age of information, data is the new oil. The ability to harness, analyze, and derive actionable insights from vast amounts of data is a critical skill in today’s digital economy. The Big Data Analytics Professional Program is designed to equip you with the knowledge and skills needed to thrive in this data-driven world. This IBM - Big Data Analytics Professional Program covers a broad range of topics, from foundational concepts to advanced analytical techniques, ensuring that graduates are well-prepared to tackle real world challenges. -- Eligibility Criteria -- - No previous experience with Big Data required. - Interest in data analysis and data science. - Computer access with internet capability. - Commitment to a 6-month self-paced learning plan. - Understanding of English for course instruction and materials.

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What you’ll learn

Big Data 101 : Understand the fundamentals of big data, including its characteristics and significance.
Hadoop 101 : Learn the basics of Hadoop, its architecture, and its role in big data processing.
NoSQL - MongoDB : Explore NoSQL databases with a focus on MongoDB for handling unstructured data.
Introduction to Big Data, Hadoop & Ecosystem : Get an overview of big data concepts and the Hadoop ecosystem.
Spark Fundamentals I : Master the basics of Apache Spark for large-scale data processing.
Predictive Modeling Fundamentals I : Learn the fundamentals of predictive modeling and its applications.
Simplifying Data Pipelines with Apache Kafka : Understand how to use Apache Kafka for building data pipelines.
Solr 101 : Discover Apache Solr and its capabilities for enterprise search.
Developing Distributed Applications Using ZooKeeper : Learn how to use Apache ZooKeeper for managing distributed applications.

Covering Topics

Learning Mode : Online Self-Paced (Learn Anywhere & Anytime).

Program Duration : 6 Months.

Learning Hours : 60+ (Includes E-Courseware, Videos, Hands-on-Labs, Assignments, Quiz etc by IBM).

Support : Weekly Doubt Clearance Session.

Certification : Official IBM certifications that directly engage with your LinkedIn Profile.

Curriculum

  Course 1 : Big Data 101

Module 1: What is Big Data? 
Module 2: Big Data - Beyond the Hype
Module 3: The Big Data and Data Science
Module 4: BDUse Cases
Module 5: Processing Big Data

  Course 2 : Hadoop 101

Module 1: Introduction to Hadoop 
Module 2: Hadoop Architecture
Module 3: Hadoop Administration
Module 4: Hadoop Components

  Course 3 : NoSQL- MongoDB

Module 1: Overview of NOSQL 
Module 2: Introduction to MongoDB
Module 3: Basic MongoDB Operations
Module 4: Advanced MongoDB Operations

  Course 4 : Introduction to Big Data, Hadoop & Ecosystem4

Module 1: What is Big Data and Data Analytics
Module 2: Overview about HDP
Module 3: Introduction to Apache Ambari
Module 4: Hadoop and the Hadoop Distributed File System (HDFS)
Module 5: MapReduce and YARN
Module 6: Apache Spark
Module 7: Overview on Data File Formats, HBase, Pig, Hive, R and Python
Module 8: ZooKeeper, Slider, and Knox
Module 9: Flume and Sqoop
Module 10: DataPlane Service
Module 11: Stream Computing

  Course 5 : Spark Fundamentals  I

Module 1: Introduction to Spark - Getting started
Module 2: Resilient Distributed Dataset and DataFrames
Module 3: Spark application programming
Module 4: Introduction to Spark libraries
Module 5: Spark configuration, monitoring and tuning

  Course 6 : Predictive Modeling Fundamentals I

Module 1: Introduction to Data Mining
Module 2: The Data Mining Process
Module 3: Modeling Techniques
Module 4: Model Evaluation
Module 5: Deployment on IBM Bluemix

  Course 7 : Simplifying Data Pipelines with Apache Kafka

Module 1: Introduction to Apache Kafka
Module 2: Kafka Command Line
Module 3: Kafka Producer Java API
Module 4: Kafka Consumer Java API
Module 5: Kafka Connect and Spark Streaming

  Course 8 : Solr 101

Module 1: Search Engines
Module 2: Configure and Add Documents to Solr
Module 3: Analyzers and Queries
Module 4: SolrJ and Customization

  Course 9 : Developing Distributed Applications Using ZooKeeper

Module 1: Introduction to ZooKeeper
Module 2: The ZooKeeper Data Model
Module 3: Programming and Advanced Topics