Diploma in ADVANCED DATA ANALYTICS
Program Objective
The Diploma in Advanced Data Analytics will develop the knowledge, skills and behaviours you need to be an effective data analyst. By completing this program, you will cover the key technical skills in Data Preparation, Data Analysis and Data Visualization as well as nontechnical data skills. Our program combines these requirements with a focus on understanding, analysis and application of fundamental data-focused tools, techniques, and theories. The program leads you through a series modules to efficiently meet all these requirements.
This program is designed to develop advanced, job-ready competencies in data analysis, preparing learners for technical roles such as Data Analyst, Data Technician, or Junior Data Scientist. Students will learn to collect, clean, process, and analyze data using modern tools and languages like Python, SQL, Excel, Power BI, and Tableau. Emphasis is placed on analytical thinking, automation, ethics, and the ability to translate complex datasets into actionable insights for business decision-making.
By the end of the program, students will be capable of working autonomously on data projects, supporting data-driven strategies, and contributing to performance optimization across organizations.
Program Structure
Duration: 12 Months
Terms 1–3 (9 months): Classroom-based instruction (12 modules)
Term 4 (3 months): Final project & Internship Placement
Level: NVQ Level 4 / EQF Level 5
TERM 1: Analytical Foundations & Technical Skills
Module 1: Introduction to Advanced Data Analysis
This module provides a strategic overview of the data analyst’s role and responsibilities, introducing core concepts such as the data lifecycle, data-driven decision-making, and governance. Learners explore the ethics of data, including privacy, consent, and bias.
Module 2: Advanced Excel & Spreadsheet Techniques
Learners strengthen their spreadsheet skills for complex business analysis. Emphasis is placed on using Excel to simulate business scenarios and present insights effectively.
Module 3: Statistical Thinking for Analysts
This module builds quantitative reasoning. Learners apply statistical methods to analyze relationships, measure variability, and draw conclusions from real-world datasets.
Module 4: Data Cleaning & Preparation
This module focuses on transforming raw data into a reliable dataset ready for analysis. Learners work with real-world “dirty” datasets to develop best practices in data wrangling and validation.
TERM 2: Tools, Applications & Domain Knowledge
Module 5: SQL for Data Analysis & Reporting
Learners gain the ability to retrieve and manipulate data using SQL. The module progresses from basic queries to advanced data processing, including nested queries and window functions.
Module 6: Data Visualization & Storytelling
This module teaches how to create compelling visuals that support insight generation and effective decision-making. Focus is placed on choosing appropriate visual formats and crafting clear narratives.
Module 7: Python for Applied Data Analysis
Python is used to automate and scale analysis workflows. This module introduces students to programming concepts and libraries used by data professionals.
Module 8: Business Contexts for Data Use
Learners explore how data drives decision-making across functions like sales, HR, marketing, and logistics. They analyse domain-specific datasets to understand how metrics align with strategy.
TERM 3: Strategy, Decision-Making & Career Readiness
Module 9: Predictive Analytics & Forecasting
This module introduces predictive modeling and trend analysis, preparing students to go beyond describing data toward forecasting future outcomes.
Module 10: Data-Driven Decision Making
Students learn how to use data to influence organizational decisions. The module emphasizes A/B testing, scenario analysis, and risk assessment.
Module 11: Project Management for Data Analysts
This module provides tools for managing small to medium-sized data projects. It emphasizes communication, documentation, and agile practices.
Module 12: Professional Development & Industry Preparation
Students prepare for employment or freelance work by developing their professional identity and showcasing their capabilities.
TERM 4: Internship & Final Thesis
Supervised Internship
Students gain hands-on experience in a real-world setting, contributing to data projects in roles such as junior analyst, research assistant, or reporting coordinator.
Final Project / Thesis
Learners complete a capstone project focused on a business problem or public interest issue using a real dataset. The final deliverable includes a written report and visual presentation.
Learning Outcomes
Upon successful completion of the Diploma in Advanced Data Analytics, learners will be able to:
Independently manage and execute data projects using modern tools and techniques.
They will demonstrate the ability to clean, structure, and analyse data using Excel, SQL, and Python,
apply statistical and machine learning models to generate insights.
Learners will be proficient in creating interactive dashboards with tools such as Power BI or Tableau, and capable of communicating complex findings to both technical and non-technical stakeholders.
Graduates will also show awareness of data ethics, governance, and security, and be prepared to contribute effectively in real-world business environments across sectors.
What does the Advanced Diploma in Data Analytics cover?
Find clear answers to your questions about the program’s structure, duration, and career benefits to help you decide with confidence.
How long is the Diploma in Advanced Data Analytics program?
The program runs for 12 months, combining classroom learning and an internship to ensure practical experience.
What skills will I gain from this diploma?
It builds upon foundational skills, focusing on machine learning, predictive modeling, experimental design, advanced statistical techniques, and big data technologies.
Is there an internship included in the course?
Yes, an internship is part of the curriculum to provide real-world administrative experience.
Who should enroll in this diploma program?
Anyone aiming to excel as a Advanced Data Analytics across various industries will benefit greatly.
Enroll Today to Advance Your Career
Discover how our diploma can elevate your skills and open new professional opportunities.