The Complete Course on Data Science & Big Data Analytics

Course Introduction

Information can come in various forms and from multiple sources. Mastering the ability to extract, model, and analyze this information can offer significant commercial advantages.

Big Data Analytics enables organizations to identify trends, refine operational procedures, and leverage insights to boost revenue and enhance client experiences.

The Complete Course on Data Science & Big Data Analytics provides a practical approach to applying data science techniques.

It covers how to determine the requirements for data science applications, the technologies available, and the analytical models suited to derive valuable insights from Big Data. This training will guide you on making sense of complex data and utilizing analytics effectively.

This training course will feature:

• An Overview of Big Data Analytics
• Adaptation and Approach of Lifecycles and Models
• Methods and Models for Statistical Evaluation
• Advance Methods and Models for Big Data Analytics
• How To Select Appropriate Tools to Achieve the Best from Data Analytics

Training Objectives

By the end of this training 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 from applying best practice in Data Analytics

Who should Attend?

This training course has been designed for senior executives, technical engineers and those involved in the technology, research and statistical analysis of corporate data.

This training course is suitable to a wide range of professionals but will greatly benefit:

• Statistical and Research Analysts
• Key Application Development and data Research Personnel
• Technology Engineers, CTO and CIO
• Strategic Development Directors

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