An intensive professional development training course on
Certificate in Data Science Best Practices
The Complete Course on Data Science and Big Data Analytics
Why Choose Certificate in Data Science Best Practices Training Course?
Information can exist in many forms and sources. The ability to extract, model and analyse information, can provide significant commercial benefits. Big Data Analytics can assist organisations identify trends and adjust operational procedures to harness the results, to increase revenue and client experience.
This Certificate in Data Science Best Practices training course will provide a practitioner approach to identify requirements for the application of data science, how these can be adopted, technologies available, which analytical models may be appropriate to provide valuable data, and how to make sense of Big Data and Analytics.
This Certificate in Data Science Best Practices 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
What are the Goals?
By the end of This Certificate in Data Science Best Practices 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 is this Training Course for?
This Certificate in Data Science Best Practices training course has been designed for senior executives, technical engineers and those involved in the technology, research and statistical analysis of corporate data.
This Certificate in Data Science Best Practices 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
How will this Training Course be Presented?
This information technology training course will utilize a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. Participants will gain detailed knowledge by active participation in seminars, group discussions and real life case studies. Delivery will be by presentation, group syndicate investigations, training DVD and interactive seminars.
The Course Content
- 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
- 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
- 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
- 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
- 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
Certificate and Accreditation
- AZTech Certificate of Completion for delegates who attend and complete the training course
Do you want to learn more about this course?
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Frequently Asked Questions
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