Duration
13-14 days
Overview
This series of training will equip individuals with an introduction to data engineering for big data and essentials for data exploration and analytics. Big data offers the capability to sieve through huge amount of historical and real-time data from various sources such as system logs, sensor data and even social media data. This is in addition to enterprise relational database systems.
The data engineering component will enable the development of the infrastructure that enables models to be developed. The data engineering program is arranged in a sequence of short courses; covering the fundamentals for establishing a big data infrastructure using Hadoop, the data store on HDFS, accessing un-structured data using PIG and accessing structured data using HIVE. The program also includes administration of the base infrastructure.
The data analytics component will introduce the fundamentals for extracting knowledge from large volumes of data that could be structured or unstructured, with key competencies in the areas of data mining. The data analytics program covers the key concepts, skills and tools necessary to enable participants to be productive in the initial process of the data analytics pipeline. This includes the exploration of the data, social media analytics and an overview of the data mining techniques. To complete the course, participants can opt for various visualization tools such as Microsoft PowerBI, Tableau and Qlik Sense.
This course provides the essentials necessary to appreciate and begin data science projects. The next step upon completing the course and with some experience in real projects would be to take on future courses in statistics to enable the individual to interpret the outcome of the analytics appropriately.
Training Program : Hadoop Essentials (2 days)
Course Content
- Introduction to BIG DATA & Data Engineering
- Hadoop Essentials : Hadoop architecture, Hadoop ecosystem
- Hadoop Distributed File System
- Hadoop MapReduce
- Data Management: SQL and NoSQL
Who Should Attend
System and Network Engineers and Administrators, Database Administrators & IT Managers
Special Note
Will require workstations with at least an Intel i5 (6th Generation or newer) with a minimum of 16 GB of main memory and 30 GB of free hard disk space.
Training Program : ETL Hadoop Essentials (2 days)
Course Content
- Extract, Transform and Load unstructured data with Pig: Developing Pig Latin programs for extracting, loading and transforming data.
- Extract, Transform and Load structured and Hive: Developing using SQL like HiveQL to extract, load and transform data.
- Introduction to Sqoop for structured databases to HDFS.
- Introduction to Flume for streaming data ingestion.
Who Should Attend
System Engineers and Administrators, Database Administrators & Software Developers
Special Note
Will require workstations with at least an Intel i5 (6th Generation or newer) with a minimum of 16 GB of main memory and 30 GB of free hard disk space.
Training Program : Hadoop Administration (2 days)
Course Content
- Installing, configuring and managing a Hadoop cluster.
- Monitoring a Hadoop cluster.
- Administering a Hadoop cluster.
Who Should Attend
System Engineers and Administrators
Special Note
Will require workstations with at least an Intel i5 (6th Generation or newer) with a minimum of 32 GB of main memory and 60 GB of free hard disk space. For this class, the hands-on will be in groups of students and may utilize several workstations.
Training Programme: Exploratory Data Analytics - 2 days (+1 day if participants are not familiar with the programming language)
Course Content
- Introduction to programming tools (R or Python)
- Getting and cleaning data
- Data transformation
- Descriptive analytics
- Basic data visualization.
Who Should Attend :
Anyone who’s involved with:
Data analysts & Customer Insights Executives
Training Programme: Social Media Analytics (2 days)
Course Content
- Mining Social Media Content
- Text Mining: Typical process and basic processing
- Natural Language Processing: An Introduction
- Sentiment Analysis (as a Use Case)
Who Should Attend :
Anyone who’s involved with:
- Digital Campaigns and Social Media Personnel
- Brand and Engagement personnel
- Data analysts
- Customer Insights Executives
Training Programme: Data Mining (3 days)
Course Content
Introduction to Data Mining and feature selection
Association rule mining and outlier analysis
Regression: Linear regression, multi-variate regression
Clustering: k-means, hierarchical clustering
Classification: decision trees, naïve bayes, random forest
Who Should Attend
Data analysts & Customer Insights Executive
Programme scope, delivery arrangements and suitability are confirmed during enquiry.