Data Analytics Professional Programme

About this course

Data Analytics Professional Programme

From Complete Beginner to Career-Ready Data Analyst

20 Weeks | Live Online Classes | 30+ Practical Projects | Professional Portfolio Building | Certification Preparation

Don't Just Learn Data Analytics. Build the Evidence That You Can Do It.

Imagine completing your training with more than technical knowledge and a certificate. Imagine having a professional portfolio of projects demonstrating your ability to analyse data, solve business problems, create interactive dashboards and communicate meaningful insights.

That is the experience we are building at Inferaq Academy.

Our 20-week Data Analytics Professional Programme is designed to take complete beginners through a structured, practical learning journey towards becoming confident, career-ready Data Analytics professionals.

You will learn industry-relevant analytical tools, complete practical projects, develop a professional GitHub portfolio, prepare for recognised certifications and gain the confidence to demonstrate your capabilities to prospective employers.

No previous programming or technical experience is required.

Your Professional Portfolio Starts from Day One

At Inferaq Academy, portfolio development is not an optional activity reserved for the final weeks of training. It is an integral part of your learning journey from the very beginning.

Through our signature Design by Success framework, you will progressively build a professional portfolio that demonstrates your development, practical abilities and analytical problem-solving skills.

You will learn how to:

• Create and professionally organise your GitHub portfolio.
• Document your analytical projects using professional README files.
• Publish selected Excel, SQL, Python, Power BI and Tableau projects.
• Present business problems, methodologies, analytical findings and recommendations.
• Develop a comprehensive end-to-end Data Analytics capstone project.
• Showcase your portfolio through your LinkedIn profile and professional CV.
• Explain and defend your project decisions during technical interviews.

Every major stage of your learning journey contributes towards developing evidence of your practical capabilities.

Our goal is simple: when an employer asks what you can do, you should have projects to demonstrate your answer.

What You Will Master

Throughout the programme, you will develop practical competencies in:

Microsoft Excel: Data cleaning, advanced formulas, PivotTables, Power Query, data analysis and dashboard development.

SQL: Database querying, joins, aggregation, data extraction and business reporting.

Python: Programming fundamentals, Pandas, NumPy, exploratory data analysis and data visualisation.

Microsoft Power BI: Data transformation, data modelling, DAX, interactive dashboards and business intelligence reporting.

Tableau: Interactive visualisations, dashboard design and data storytelling.

R Studio: Statistical analysis, data exploration and analytical programming.

Business Analytics: KPI development, business problem-solving, analytical reporting and evidence-based decision-making.

Data Engineering Fundamentals: ETL processes, data pipelines, data warehousing and introductory cloud analytics.

AI-Assisted Analytics: Using modern AI tools responsibly to improve analytical productivity while validating generated results.

30+ Practical Projects Across Multiple Industries

Learning becomes meaningful when you apply it.

Throughout the programme, you will work on practical exercises and projects inspired by real-world business challenges across industries such as healthcare, retail, finance, marketing, human resources and business operations.

You will learn to investigate business questions, prepare datasets, identify patterns, create visualisations and present actionable recommendations.

Selected projects will progressively become part of your professional portfolio.

Design by Success: Our Signature Learning Framework

We believe professional development should be intentional, measurable and practical.

Our learning approach follows four connected principles:

LEARN IT: Develop a clear understanding of analytical concepts through beginner-friendly, instructor-led teaching.

PRACTISE IT: Reinforce your knowledge through guided exercises, assignments, practical laboratories and personalised support.

BUILD IT: Apply your knowledge to practical projects and progressively develop your professional portfolio.

PROVE IT: Demonstrate your capabilities through documented projects, assessments, presentations and a comprehensive final capstone.

You will not simply learn how analytical tools work. You will learn how to use them independently to solve meaningful business problems.

Professional Certification and Career Preparation

The programme includes preparation activities supporting relevant industry certification pathways, including Python Institute PCEP, Microsoft Power BI Data Analyst Associate (PL-300) and Google Data Analytics.

You will also receive structured guidance on professional portfolio presentation, CV development, LinkedIn optimisation, technical interviews and communicating analytical projects to prospective employers.

External certification examinations and awards are administered separately by their respective awarding organisations.

Learn with Expert Guidance and Continuous Support

Your learning experience includes live online classes, guided practical laboratories, recorded learning resources, structured assignments, project feedback, personalised coaching and access to a collaborative student community.

Our objective is to help you develop confidence progressively, regardless of your starting point.

What You Can Become

Develop foundational and practical competencies relevant to career pathways such as:

• Data Analyst
• Business Analyst
• Business Intelligence Analyst
• Reporting Analyst
• Dashboard Developer
• Data Support Officer
• Junior Analytics Professional

Your Journey Starts Here

You do not need to be a programmer, mathematician or technology professional to begin.

You need curiosity, commitment and a willingness to learn.

By the end of your journey, you will have developed practical analytical skills, completed numerous projects and built a professional portfolio demonstrating your progress and capabilities.

20 Weeks. 30+ Practical Projects. Your Professional Portfolio. Your Next Chapter.

Join Inferaq Academy and begin transforming your potential into demonstrable professional skills.

INFERAQ ACADEMY

We Take You From Zero to a Professional.

Who this course is for

• Complete beginners with no coding experience
• Career changer moving into tech
• Business owners and entrepreneurs
• Students and Recent Graduates

What you will learn

• Analyse Real-World Data
• Build Interactive Dashboards
• Complete 30+ Practical Projects
• Build Your Professional Portfolio
• Prepare for Your Analytics Career

Tools you will use

• Excel
• Python
• SQL
• Tableau
• R Studio
• Power BI

Career paths

• Data Analyst
• Business Analyst
• Business Intelligence Analyst
• Dashboard Developer
• Data Support Officer
• Junior Analytics Professional
• Reporting Analyst

Curriculum

Introduction to Data Analytics & Professional Portfolio Setup

Begin your journey into Data Analytics by understanding the role of data in modern organisations, the responsibilities of a Data Analyst, the analytics lifecycle and the different career opportunities available. Learn about datasets, data types, business questions and the essential tools used throughout the programme. Set up your learning environment, create your GitHub account and establish your professional project portfolio from Day One, following Inferaq Academy's Design by Success framework.

Microsoft Excel for Data Analytics

Develop practical Excel skills, progressing from spreadsheet fundamentals to advanced business data analysis. Learn data cleaning, sorting, filtering, formulas, functions, conditional formatting, lookup functions, Excel Tables, PivotTables, PivotCharts and interactive dashboards. Apply your knowledge to realistic business datasets, including sales, revenue and performance analysis. Complete practical assignments and publish your first documented analytical projects in your professional portfolio.

Power Query & Advanced Excel Analytics

Master data preparation and transformation using Power Query. Learn to import datasets from multiple sources, remove duplicates, handle missing values, transform columns, merge and append queries, automate repeatable cleaning tasks and prepare structured data for analysis. Apply advanced Excel techniques to investigate business performance, identify trends and create professional reports. Develop a complete Excel and Power Query portfolio project demonstrating your ability to transform raw business data into meaningful insights.

SQL & Database Analytics

Learn how relational databases store and organise information and develop the SQL skills required to retrieve, manipulate and analyse business data. Progress through SELECT statements, filtering, sorting, aggregation, grouping, joins, subqueries and common table expressions. Apply SQL to realistic business questions involving customers, products, transactions and organisational performance. Complete a database analytics project and document your SQL queries, analytical methods and findings in your professional GitHub portfolio.

Python Programming Fundamentals

Build a strong foundation in Python programming, starting from zero. Learn variables, data types, operators, conditional statements, loops, strings, lists, tuples, dictionaries, functions, modules and exception handling. Develop practical problem-solving skills using Jupyter Notebook and Google Colab. Complete progressively challenging programming exercises and mini-projects while preparing for the Python Institute PCEP certification examination. Publish selected Python projects in your GitHub portfolio.

Python for Data Analysis & Visualisation

Apply Python to real-world data analysis using Pandas, NumPy, Matplotlib and Seaborn. Learn to import datasets, inspect data structures, handle missing values, remove duplicates, transform data, perform exploratory data analysis and create meaningful visualisations. Investigate business questions, identify patterns and communicate analytical findings through well-documented Jupyter Notebooks. Complete practical Python analytics projects using datasets from different industries and showcase selected work in your professional portfolio.

Microsoft Power BI & Business Intelligence

Learn to transform business data into professional, interactive reports and dashboards using Microsoft Power BI. Develop practical skills in Power Query, data modelling, relationships, DAX calculations, KPI development, visualisation and dashboard design. Explore how organisations use Business Intelligence to monitor performance and support strategic decisions. Complete an end-to-end Power BI project, from importing and preparing raw data to developing and presenting an interactive business dashboard. Prepare for the Microsoft PL-300 certification pathway.

Business Analytics, Data Engineering & AI-Assisted Analytics

Explore how Data Analytics supports business strategy, operational performance and evidence-based decision-making. Learn to translate business requirements into analytical questions, define KPIs and communicate actionable recommendations. Develop foundational knowledge of data engineering, ETL processes, data pipelines, data warehousing and cloud analytics. Discover how AI-powered tools can support data cleaning, coding, analysis and reporting while learning to critically evaluate and validate AI-generated outputs. Apply these concepts through practical business analytics exercises.

Professional Portfolio Development & Career Preparation

Transform your completed analytical projects into a professionally presented portfolio that demonstrates your technical capabilities and problem-solving experience. Organise and refine your GitHub repositories, develop professional README documentation, showcase selected Excel, SQL, Python, Power BI and Tableau projects, and communicate your analytical findings effectively. Receive guidance on CV development, LinkedIn optimisation, project presentation, certification preparation and technical interviews. Learn to demonstrate your practical abilities confidently to prospective employers and recruiters.

Final Capstone Project & Professional Showcase

Bring together the knowledge and practical skills developed throughout the programme by completing a comprehensive end-to-end Data Analytics capstone project. Select a realistic business problem, define analytical objectives, prepare and clean datasets, conduct exploratory analysis, develop meaningful visualisations and communicate evidence-based recommendations. Document your methodology, tools, findings and conclusions in a professional project report and GitHub repository. Present your completed project, demonstrate your analytical capabilities and finalise your professional portfolio as evidence of your learning journey.

Requirements

No prior experience required

Access to a laptop and the internet

Fees

Next cohort: Cohort 2, starting 6 November 2026.

• Nigeria: NGN 30,000,000
• United Kingdom: £400.00
• International: US$500.00

Pay in full or in instalments. Your fee is based on the country where you live.