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