PeopleCert Data Science: Data Analyst
Connect the dots. Uncover patterns. Draw insights.
PeopleCert Data Science Analyst is aimed at anyone who wishes to demonstrate a thorough understanding of data science concepts and how these can be applied in a real professional environment.
Extract value from data, apply useful insights
Candidates get guidance on how to use scientific methods, processes, and algorithms to extract insights from structured and unstructured data. Organisations can use data for many reasons, from refining their marketing campaigns and techniques to solving business problems, carrying out predictive modelling, and other analytics applications. The use of data science is constantly increasing in importance across many industries and can lead to a comparative advantage, maximising efficiency and increasing profitability.
With PeopleCert Data Science Analyst, you will learn about:
- The basics of Data Science (recap of the PeopleCert Data Science: Foundation course)
- Key concepts of Programming (with R/Python)
- Key concepts of Data Management and Business Intelligence
- Probability and Statistics and Advanced Statistical topics
- Machine Learning and Artificial Intelligence (AI)
- Data Visualisation Methods
- Data Governance, Data Anonymisation
Why choose PeopleCert Data Science Analyst?
PeopleCert Data Science enables candidates to obtain solid knowledge and understanding of data science concepts and tools, along with real business examples. Holding a PeopleCert Data Science certificate enables you to reach your career goals by demonstrating your ability to solve real business problems, realise opportunities, optimise operations, improve inefficiencies within your company, predict market trends and discover new sources of revenues, using data science tools.
Who is the PeopleCert Data Science Analyst for?
PeopleCert Data Science Analyst is for all those who want to prove their knowledge, understanding and proficiency with data science and Big Data concepts and terms, potential data sources that can be used for solving real business problems and an overall overview of data mining tools.
Example of typical job titles:
- Software Developer
- Data Scientist
- Data Analyst
- Data Engineer
- Business Analyst
- Big Data Developer
- Database Administration
Day 1
8 Contact Hours
| Module | Approximate Time |
| Welcome | 0.5 hour |
| Foundation Overview and Recap | 1.0 hour |
| Introduction to Data Analytics | 1.0 hour |
| Introduction to Programming | 1.0 hour |
| Basic Programming Skills | 1.5 hours |
| Relational Databases | 2.0 hours |
| Big Data Storage | 0.5 hour |
| Recap and QA | 0.5 hour |
Day 2
8 Contact Hours
| Module | Approximate Time |
| Business Intelligence with Power BI | 4.0 hours |
| Time Series Basics with Power BI | 1.0 hour |
| Time Series with Power BI Lab: Getting Started | 0.5 hour |
| Time Series with Power BI Lab: Assignments | 2.0 hours |
| Recap and Q&A | 0.5 hour |
Day 3
8 Contact Hours
| Module | Approximate Time |
| Data Governance | 1.0 hour |
| Anonymize Data | 1.0 hour |
| Introduction to Statistics | 1.5 hours |
| Machine Learning (ML) | 2.5 hours |
| Artificial Intelligence (AI) | 1.0 hour |
| Recap and Q&A | 1.0 hour |