Full Data Analytics Programme

Back to services

We are happy to get you started

The complete data analytics pathway — everything in the 6-Week Programme plus SQL for querying databases, Python for advanced analysis and automation, and an introduction to machine learning. By the end you will have a portfolio of real projects and the skills to apply for junior data analyst, BI analyst, and data science roles.

Payment plans available — split into 3 or 6 monthly instalments. Contact us for details.

Program ID

undefined--1112

Price

₦380,000

Duration

24 Weeks

Program Outline

Everything in the 6-Week Programme (Excel, Power BI, data cleaning, dashboards)
SQL — writing queries to extract and analyse data from relational databases
Python for data analysis — pandas, NumPy, matplotlib and seaborn
Data wrangling with Python — merging, reshaping, aggregating datasets
Statistical analysis and hypothesis testing
Machine learning fundamentals — supervised and unsupervised learning
Building predictive models with scikit-learn
End-to-end data projects added to your professional portfolio
Advanced DAX formulas and Power BI enterprise features
Live instructor-led sessions, session recordings, and dedicated tutor support
CPD-certified completion certificate

View Program Modules

Program Modules

1. Weeks 1–6 — Excel, Power BI & Data Cleaning

Full 6-Week Programme content (see above)
Excel: formulas, functions, PivotTables, dashboards
Power BI: reports, dashboards, Power Query and DAX basics
Data cleaning and quality management

2. Weeks 7–10 — SQL for Data Analysis

Relational databases: tables, keys, relationships
SELECT, WHERE, GROUP BY, ORDER BY, HAVING
Joins: INNER, LEFT, RIGHT, FULL OUTER
Subqueries, CTEs and window functions
Analysing real business datasets using SQL

3. Weeks 11–16 — Python for Data Analysis

Python fundamentals: variables, control flow, functions
pandas: reading, exploring and transforming DataFrames
NumPy for numerical computation
Data visualisation: matplotlib and seaborn charts
Automating reports and data pipelines

4. Weeks 17–20 — Machine Learning Fundamentals

What is machine learning and where it is applied
Supervised learning: regression and classification
Unsupervised learning: clustering and dimensionality reduction
Building and evaluating models with scikit-learn
Interpreting model results and communicating findings

5. Weeks 21–24 — Advanced Analytics & Capstone

Advanced Power BI: enterprise features, Row-Level Security, dataflows
Combining SQL, Python and Power BI in a single workflow
Portfolio capstone project: full end-to-end analytics case study
Peer review and tutor feedback session
CPD assessment, certificate submission and career guidance