Big Data Bootcamp
|Course Name||Big Data Bootcamp|
To inquire more about our courses, you may call our Program Sales Officers at 830.20.50 or email us at email@example.com
Big Data has seen a huge leap forward in 2014 regarding how it has been represented and used across companies. The adoption rates have grown and the importance of Big Data as a business function has increased, but what are we going to see in 2015 and moving forward?
The Big Data Bootcamp aims to give a holistic understanding of Big Data fundaments, security, and platforms. The course will explain why Big Data should be processed in a platform that can handle the 4Vs of data: Variety, Velocity, Veracity, and Volume by using a family of components.
This course also aims to give the participants understanding, knowledge, and fluency in data collection, cleaning, investigation, management, exploration, prediction, and communication. This course serves to help the participants familiarize with data science process and surrounding best practices.
After the course, you will:
1. Define, understand, and describe Big Data and its role in the corporate world;
2. Select hardware and software to implement it;
3. Understand and discuss the various frameworks required;
4. Define and describe IT Security for Big Data solutions;
5. Identify certain forms of attacks to Big Data systems such as SQL Injection and Cross Site Scripting, etc.;
6. Understand why a Big Data Platform is required to bring separate silos of data and analytics together; and
7. Draft and estimate a Bill of Materials required to run a Big Data Platform.
8. Be able to identify big data problems, make assessments, suggest and implement suitable big data solutions.
|Who should attend||
Engineers, developers, architects, network specialists, managers, executives, students, professional services, data analysts, BI developers, performance engineers, data warehouse professionals, sales, pre sales officers, technical marketing, project mangers, teaching staff, and delivery managers.
I. Fundamentals of Big Data
A. Introduction of big data fundamentals
B. Concept of the 4Vs
C. Big data use-case examples
II. Big Data Hardware and software
A. The evolution of hardware and what it means to big data
B. Three important computing requirements for big data platforms
C. Introduction to the cloud infrastructure
D. Bill of materials
E. The Evolution of Software and its impact on big data
A. Services management and overview
B. Information Technology Infrastructure Library (ITIL)
C. IT Service Management (ITSM) body of knowledge
IV. IT Security
A. IT security
B. Types of Attacks
C. HW SW Hardening
A. Capabilities of a Complex Event Processor (CEP)
B. High Speed Mediation and Service Broker
C. Natural Language Processing
D. Image Recognition Analytics
E. Big data appliances
F. Streaming and structured data
G. Current key players
H. Draft a BOM without commercials
VI. Data Science Best Practices
A. Introduction to Data Science
B. The Data Science Process - sequence of activities
to carry out a successful data science project
C. Installing Various Sensors for Data Collection
D. Reports and Visualization
VII. Business Intelligence and Advanced Analytics
A. Experimental Statistics and Modeling
B. Data Mining and Forecast Management
C. Introduction to Machine Learning and Artificial Intelligence
D. Deep Thinking and Learning
E. Related Software and Tools
VIII. Data Science and Governance
A. Industry-Specific Applications
B. Solution-Based Applications
C. Validation - Final Exam via Google Forms or Survey Monkey
|Mr. Chino Antonio S. Rodriguez||
is a Product Consultant at Danateq Philippines, Inc. Prior to this, he was the Manager of the Computing Services Group, Information Technology Resource Management Office, of the Ateneo de Manila University.
|Mr. Mario R. Domingo||
is the Founder of lloopp, a deep-learning solutions company headquartered in Singapore. He is responsible for helping client companies transform their businesses by focusing on their customers using deep-learning in enterprise architecture. He is also the Program Director for the Diploma in Applied Project Management at the Ateneo Center for Continuing Education.