Data Analytics Certification

Participants / Target audience

• Individuals beginning a career in data analytics

• Professionals seeking to add data-analysis skills to their current roles

 

Who should attend

Anyone who needs to interpret data or present insights to inform business decisions—business analysts, marketing analysts, operations staff, junior analysts, and professionals transitioning into data roles.

 

Prerequisites

• Basic computer literacy (comfortable with spreadsheets)

• No prior programming experience required (introductory Python & SQL content included)

 

Learning outcomes - by the end of this course you will be able to:

• Explain core data concepts and the analytics workflow (collect → clean → analyse → visualise).

• Use Excel, introductory SQL and Python (pandas) to query, transform and summarise datasets.

• Clean and prepare real-world data for analysis (missing values, data types, filtering).

• Create clear, persuasive visualisations and dashboards to communicate insights.

• Apply basic statistical techniques (descriptive stats, correlation, simple hypothesis testing) to support decisions.

• Build a small end-to-end analytics project from raw data to visual story.

 

Course outline / modules

1. Introduction to Data Analytics & the Analytics Workflow

2. Data Collection & Storage — sources, formats, and data ethics

3. Data Cleaning & Preparation — handling missing data, data types, transformations

4. Excel for Analysis — pivot tables, formulas, basic automation

5. Introduction to SQL — querying, joins, aggregations for business questions

6. Intro to Python for Data (pandas) — loading data, filtering, grouping, basic transforms

7. Data Visualization Principles — charts, dashboards, storytelling with data (Excel/Power BI or matplotlib/plotly)

8. Basic Statistics for Decision Making — measures of central tendency, dispersion, correlations, simple hypothesis testing

9. Mini Project & Presentation — apply skills to a business dataset and present findings

 

Benefits

• Gain practical, job-ready analytics skills using commonly used tools (Excel, SQL, Python).

• Make better, data-backed business decisions and improve stakeholder reporting.

• Hands-on project experience to demonstrate capability to employers.

• Clear learning path to intermediate data roles (Data Analyst / Business Analyst).

 

Delivery format

• Instructor-led (classroom or live virtual) with lab exercises and guided projects.

• Small-group practical sessions.

• Course materials and example datasets provided.

 

Certification / outcome

• Certificate of Completion on successful course.

• Capstone project certificate / assessment to validate practical skills.

• Guidance and resources for next-step certifications or job-ready portfolio building.