Course Overview
PeopleCert Data Science Analyst is a certification course that teaches you how to apply data science concepts and tools to solve real-world problems and generate value from data. You will learn how to use programming languages such as R or Python, data management and business intelligence techniques, probability and statistics, machine learning and artificial intelligence, data visualisation methods, and data governance and anonymisation principles.
 
By the end of this course, you will be able to:
Extract insights from structured and unstructured data using scientific methods, processes, and algorithms.
Refine your marketing campaigns, techniques, and strategies based on data analysis.
Solve business problems, carry out predictive modelling, and discover new sources of revenue using data science.
Demonstrate your knowledge and proficiency with data science and big data concepts and terms.
Use data science tools and frameworks in a professional environment.
 
This course is aimed at anyone who wishes to obtain advanced skills of Big Data and Data Science and requires candidates to have and demonstrate a thorough knowledge, understanding and application of the Data Science terms, concepts, tools, and principles. The certification can also cater for candidates seeking personal certification.
 
The certification will provide all the required levels of knowledge to its holders and will certify that they have a thorough understanding and application of Big Data and Data Science concepts.

Target Audience
PeopleCert Data Science Analyst is a certification that validates the skills and knowledge of data science professionals who can apply scientific methods, processes, and algorithms to extract insights from structured and unstructured data. The target audience for this certification are:
Software developers who want to learn how to use data science tools and techniques to create applications that leverage data.
Data scientists who want to demonstrate their proficiency in data science concepts and terms, and how to use them in real business cases.
Data analysts who want to enhance their ability to perform data analysis, data mining, and data visualisation using various tools and frameworks.
Data engineers who want to learn how to design, build, and maintain data pipelines and systems that support data science projects.
Business analysts who want to understand how data science can help them solve business problems, optimise operations, and improve decision making.
Big data developers who want to learn how to work with large-scale data sets and use data science techniques to extract value from them.
Database administrators who want to learn how to manage and secure data sources that are used for data science purposes.

Course Prerequisites
For this examination, the candidate must hold the PeopleCert Data Science: Foundation certification, however, there are no training requirements.

To be eligible for the PeopleCert Data Science: Data Analyst level examination a candidate, apart from holding the PeopleCert Data Science: Foundation certification, must be able to demonstrate a thorough knowledge, understanding and application of the Big Data and Data Science principles and it is recommended that the candidate has received Accredited Training by a PeopleCert accredited training partner.
 
Course Objectives
PeopleCert Data Science Analyst is a certification course that aims to teach candidates how to apply data science concepts and tools in real-world scenarios. The course covers the following topics:
Programming: Candidates learn how to use R or Python to manipulate, analyse, and visualise data.
Data Management and Business Intelligence: Candidates learn how to store, retrieve, and query data from various sources, such as relational databases, NoSQL databases, and cloud platforms. They also learn how to use business intelligence tools, such as Power BI, to create dashboards and reports.
Probability and Statistics: Candidates learn how to use descriptive and inferential statistics to summarise and test data. They also learn how to use probability distributions, hypothesis testing, and confidence intervals to make data-driven decisions.
Machine Learning and Artificial Intelligence: Candidates learn how to use supervised and unsupervised learning algorithms to build predictive and clustering models. They also learn how to use artificial intelligence techniques, such as natural language processing and computer vision, to analyse text and images.
Data Visualisation: Candidates learn how to use various libraries and frameworks, such as ggplot, matplotlib, seaborn, and plotly, to create effective and interactive data visualisations. They also learn how to use design principles and storytelling techniques to communicate data insights.
Data Governance and Anonymisation: Candidates learn how to ensure the quality, security, and privacy of data. They also learn how to use data anonymisation methods, such as masking, encryption, and differential privacy, to protect sensitive data.

Course Content
Day 1 - 8 Contact Hours
Welcome and Course Introduction and details
Introduction to Data Science
Data Management
Probability and Statistics
Programming Skills with Python
Review Day 1 and Introduction to Day 2
 
Day 2 - 8 Contact Hours
Introduction to Day 2
Visualization of Data
PowerBI
Business Skills
Review Day 2 and Introduction to Day 3
 
Day 3 - 8 Contact Hours
Machine Learning
Artificial Intelligence
Data Governance
Wrap Up and Review

Course Materials
Our package includes:
PeopleCert Official Training Material (OTM)
Sample exam paper and rationales
Official PeopleCert Data Science Analyst Exam Voucher inclusive of proctor (valid for 12 months)
 
PeopleCert Data Science: Analyst Exam Overview
Material allowed: None (This is a 'closed book' exam.)
Exam duration:  1 hour 15 minutes (75 minutes)
Question types: 40 Multiple Choice Questions (MCQ)/Each question is awarded one (1) mark
Number of marks: 40 marks
Pass mark: 28 out of 40 marks (70% or above)
Level of thinking: Bloom’s levels 1,  2 & 3 (Knowledge, Comprehension, Application)
Certification validity : Three (3) years
“Bloom’s level” describes the type of thinking needed to answer the question.
For Bloom’s level 1 questions, you need to recall information (Knowledge).
For Bloom’s Level 2 questions, you need to show understanding of these concepts (Comprehension).
For Bloom’s level 3 questions, you need to apply your knowledge to a situation (Application).