course | Data Science and Big Data Analysis
Looking to excel in data science big data analysis? Data Science and Big Data Analysis in Abu Dhabi offers applied tools, case studies, and certification.
DIGTR-510 | Data Science and Big Data Analysis
Course Sector : Digital Transformation and Innovation
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 09/11/2026 | 13/11/2026 | Abu Dhabi | $4,250 | Book now |
| 5 Days | 01/02/2027 | 05/02/2027 | Dubai | $4,250 | Book now |
| 5 Days | 24/05/2027 | 28/05/2027 | Barcelona | $4,950 | Book now |
| 5 Days | 08/08/2027 | 12/08/2027 | Jeddah | $4,250 | Book now |
Course Introduction
Data science and big data analytics have been one of the vital key players in the business world nowadays. Companies are using trend analysis to make critical decisions to improve consumer engagement, corporate performance, and boost revenue. Big data analytics allows companies to analyze data and develop business intelligence solutions.
Methods of utilizing data science
This training course is designed to provide participants with the essential concepts, models, and methods of utilizing data science and big data analytics in order to advance in the business environment. This course will focus on topics such as methods of identifying requirements for the application of data science, how these can be adopted, technologies available, selecting analytical models appropriate to provide valuable data, and how to achieve better business results using Big Data and Analytics.
Course objective
- Gain a comprehensive understanding of the role of big data in the business.
- Recognize when to apply data analytics and the best methods of approach for the application.
- Explore methods and models for statistical evaluation and advance methods and models for big data analytics.
- Select appropriate models and technology for big data.
- Identify and apply best practices in data analytics.
Course audience
- Data Analysts
- Data Engineers
- Business and technology leaders
- Business Unit Managers
- Business Development Consultants
- General Managers and Senior Leaders
Course Outline | Day 01
Big Data Analytics
- Current Practices and Trends in Big Data Analytics
- Business Intelligence v Data Science
- Analytical Architecture for Big Data
- Roles for Big Data within the Technology and Commercial Enterprise
- Key Drivers for Big Data Analytics
Course Outline | Day 02
Data Analytics Models and Lifecycle
- Data Analytics Lifecycle
- Stage 1 - Discovery
- Stage 2 - Preparation of Data
- Stage 3 - Model Planning and Review
- Stage 4 - Model Creation
- Stage 5 - Communication Plan
- Stage 6 - From Planning to Operation
Course Outline | Day 03
Data Analytical Methods and Programs
- Overview of R Framework
- Overview of Big Data Analytics
- Exploratory Data Analysis
- Statistical Methods of Evaluation
- Advanced Methods of Clustering
- Advanced Theory and Methods of Association Rules
- Advanced Theory and Methods of Regression
Course Outline | Day 04
Advanced Theory and Methods Overview
- Advanced Analytical Theory of Classification
- Advanced Analytical Theory of Time Series Analysis
- Advanced Analytical Theory of Textual Analysis
- Technology and Tools for Advanced Data Analytics
- Case Studies
Course Outline | Day 05
Implementing Analytics Within Your Organization
- Expanding analytic capabilities
- Breaking down Big Data Analytics into manageable steps
- Integrating analytics into current business processes
- Reviewing Spark, MLib, and Mahout for machine learning
Technology, Tools, and Achieving Results
- Unstructured Data Analytics
- Advanced Analytical Tools in Database Analytics
- How to integrate Data Analytics
- Current Best Practice Management and Approach for Project Delivery
- Data Visualization Overview
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
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