The Complete Course on Data Science & Big Data Analytics

Introduction

The Data Science & Big Data Analytics Training Course provides professionals with a practical and structured approach to understanding how data can be transformed into strategic insight. As organizations gather enormous volumes of information from multiple sources, the ability to extract, model, and interpret this data becomes a key competitive advantage. Big Data Analytics helps businesses uncover patterns, predict behavior, and optimize processes, ultimately improving decision-making, operational efficiency, and customer experience. This course gives participants a clear and hands-on understanding of how data science principles and analytical models can be applied within real organizational environments. It explains how to identify analytics requirements, determine which technologies and tools are suitable, and evaluate which modelling approaches deliver the most meaningful results. Through practical examples and structured methodologies, participants explore how to interpret complex datasets and apply Big Data Analytics to achieve measurable outcomes. Throughout the Data Science & Big Data Analytics Course, learners develop the competence needed to choose appropriate analytical methods, assess their relevance to business needs, and translate findings into actionable insights. The training also helps participants understand how modern technologies support large-scale data processing and how advanced analytical models can generate more accurate predictions. By the end of the course, professionals will have the confidence to integrate data science practices into their organization, enabling stronger decision-making and more effective use of Big Data.

Objectives

By completing this Data Science & Big Data Analytics Training Course, participants will develop a solid understanding of how data science and analytics support organizational performance. The course equips learners with the knowledge to determine when Big Data techniques should be applied, how to select the right analytical models, and how to interpret results in a meaningful way. Participants also benefit from case studies and use-case scenarios that demonstrate real-world applications of data analytics.

By the end of this Data Science & Big Data Analytics Course, participants will be able to:

• Understand the role of Big Data for their organization
• Appreciate when to apply Data Analytics and the best methods of approach
• Consider how to choose appropriate models and technology for Big Data
• Learn from case study examples and use-case scenarios
• Successfully achieve results by applying best practice in Data Analytics

Training Methodology

The Data Science & Big Data Analytics Training Course is delivered using a combination of presentations, group discussions, and hands-on case studies to reinforce key concepts. Participants engage in interactive seminars, collaborative exercises, and investigations that demonstrate how data science tools and techniques can be applied in real-life scenarios. The training experience is further enhanced through multimedia resources that support active learning.

• Interactive presentations
• Group discussions and syndicate activities
• Real-life case studies
• Training DVDs and multimedia materials
• Practical data analytics exercises

Who Should Attend?

This Data Science & Big Data Analytics Training Course is designed for professionals responsible for interpreting corporate data, implementing analytics, or driving technology-based performance improvements. It is particularly valuable for senior executives, technical engineers, and specialists involved in research, statistics, or technology development. The course also supports those seeking to expand their understanding of how data science can strengthen strategy, innovation, and organisational capability.

• This training course will greatly benefit:
• Statistical and research analysts
• Key application development and data research personnel
• Technology engineers, CTOs, and CIOs
• Strategic development directors

Course Outline

Day One: 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

• Case Study and Summary

Day Two:  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

• Case Study and Summary

Day Three: Data Analytical Methods and Programs Overview

• 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

• Case Study and Summary

Day Four:  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

• Use Case and Assessment

• Case Study and Summary

Day Five:  Technology, Tools and Achieving Results

• Unstructured Data Analytics

• Advanced Analytical Tools in Database Analytics

• How integrate Data Analytics

• Current Best Practice Management and Approach for Project Delivery

• Data Visualization Overview

• Summary ad Case Study