Professional Programme · Get job-ready as a junior data scientist

Data Science

The route to a junior data scientist role. Build the analyst's foundations (statistics, SQL and Python), then learn to build, test and explain machine learning models on realistic Nigerian business data, and to use them responsibly. Data science jobs ask for more than models: they ask for clean data, honest evaluation and results a business can act on, which is what this track teaches.

What you'll be able to do

Statistics: distributions, confidence intervals and tests
Data wrangling in SQL and pandas
Regression and classification with scikit-learn
Cross-validation, tuning and honest evaluation
Cost-based decisions, explanation and fairness
Communicating models to non-technical decision-makers

CloudTech Data Scientist

Complete every required course and the capstone project to earn the free programme badge, then claim your official Professional Certificate.

Start with Statistics for Data Analysis

What you'll learn, module by module

Work through the modules in order. Open one to see exactly what it covers.

1Module 1FoundationThe statistics and Python every data scientist relies on.
Professional courseLevel 2 · Practical Skills
Statistics for Data Analysis
Distributions, sampling, confidence intervals and tests: the language of uncertainty.
About 8 hours
You'll learn
- Statistics for Analysts
- Averages: Mean, Median and Mode
- Spread: Range, IQR and Standard Deviation
- Distributions and Outliers
- Rates, Percentages and Weighted Averages
- Correlation
- Sampling and the Normal Distribution
- Confidence Intervals
- Comparing Groups
- Regression and Trends
- Final Project
Professional courseLevel 2 · Practical Skills
Python for Data Analytics
pandas for loading, cleaning, reshaping and exploring data.
About 9 hours
You'll learn
- Python and Colab for Analysts
- Lists, Dictionaries, Loops and Functions
- DataFrames: Load and Explore
- Filtering and Sorting
- Calculated Columns and Dates
- Cleaning Messy Data
- groupby and Aggregation
- Merging Tables
- Pivot Tables and Trends
- Charts with pandas and matplotlib
- From Question to Insight
- Final Project
Professional courseLevel 2 · Practical Skills
SQL for Data Analysis
Get your own data out of databases.
About 10 hours
You'll learn
- Introduction to Databases
- Relational Databases and SQL Tools
- SELECT
- WHERE
- ORDER BY
- LIMIT
- Aggregate Functions
- GROUP BY
- HAVING
- JOINs
- CASE Statements
- Subqueries
- CTEs
- Window Functions
- Business Analysis with SQL
- Final Project
2Module 2CoreBuild and evaluate models properly.
Professional courseLevel 3 · Professional
Machine Learning Fundamentals
Regression and classification with scikit-learn, from baselines to cost-based thresholds and model cards.
About 9 hours
You'll learn
- What Machine Learning Is
- Preparing Data for a Model
- Train, Test and Baselines
- Linear Regression
- Trees, Forests and Overfitting
- Cross-validation and Tuning
- Classification and Logistic Regression
- Evaluating Classifiers and Choosing Thresholds
- Explaining Models and Responsible ML
- From Model to Decision
- Final Project
Professional courseLevel 3 · Professional· Optional
Advanced SQL
Window functions, cohorts and data quality checks for building features.
About 6 hours
You'll learn
- Readable SQL and NULL Traps
- Date Logic
- Data Quality Checks
- Window Functions in Depth
- Top N per Group and Deduplication
- Cohorts and Retention
- Pivots and Period Comparisons
- Advanced Joins
- Query Performance
- Business Analysis Patterns
- Final Project
Professional courseLevel 3 · Professional
Feature Engineering and Model Evaluation
Point-in-time features, time-based validation, calibration, lift and drift, on a mobile wallet's churn.
About 7 hours
You'll learn
- Features and Point-in-Time Thinking
- Features from Events
- Leakage Across Time
- Gradient Boosting and Model Comparison
- Calibration
- Lift and Targeting
- Drift and Retraining
- Final Project
3Module 3SpecialistGo further into the methods data science teams use.
Professional courseLevel 3 · Professional
Time Series Forecasting
Forecast demand with seasonality, events and honest backtests, and turn it into orders.
About 7 hours
You'll learn
- Forecasting for Decisions
- Trend, Seasonality and Events
- Baselines and Honest Testing
- Regression with Calendar Features
- Promotions, Events and Structural Breaks
- Backtesting over Time
- Uncertainty and Ordering
- Forecasting Many Series
- Final Project
Professional courseLevel 3 · Professional
Experimentation and A/B Testing
Design tests, size samples, catch broken splits and read results without fooling yourself.
About 7 hours
You'll learn
- Why Experiment
- Designing a Test
- Running a Test Properly
- Analysing Conversion Tests
- Analysing Continuous Metrics
- Segments, Multiple Tests and Novelty
- Guardrails and Decisions
- When You Can't Randomise
- Final Project
4Module 4ProjectsPortfolio work that shows you can take a model from data to decision.
Portfolio projectLevel 4 · Career Projects
Employee Analytics
Who leaves, when, and why: a natural first prediction problem.
Portfolio projectLevel 4 · Career Projects
Sales Performance Analysis
Explore drivers of revenue before modelling them.
CapstoneLevel 4 · Career Projects
Data Scientist Capstone: From Model to Decision
From a vague request to a trial-tested calling policy, with fairness checks and a monitoring plan.
About 12 hours
You'll learn
- The Problem and the Plan
- Audit the Data
- Point-in-Time Features
- Validate over Time
- Calibration and Capacity
- The Trial and Who to Call
- Fairness and Explanation
- Monitoring and the Final Presentation
5Module 5CareerTurn your skills into applications that get interviews.
Short courseLevel 1 · Foundations
Career Essentials
An ATS-friendly CV and a LinkedIn profile recruiters can find.
1 hr 30 min
You'll learn
- Build a CV with AI
- A Professional LinkedIn Profile
- Quick Excel Analysis
Short courseLevel 1 · Foundations· Optional
Build Your Student Portfolio
One link that shows your notebooks and model cards.
1 hr 25 min
You'll learn
- Plan Your Portfolio
- Show Your Work
- Build Your Portfolio Page
- Share Your Work on LinkedIn

Courses marked "In preparation" join the programme when they're ready. If you've already earned the programme badge by then, you keep it.

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Data Science

What you'll be able to do

Statistics: distributions, confidence intervals and tests
Data wrangling in SQL and pandas
Regression and classification with scikit-learn
Cross-validation, tuning and honest evaluation
Cost-based decisions, explanation and fairness
Communicating models to non-technical decision-makers

CloudTech Data Scientist

Complete every required course and the capstone project to earn the free programme badge, then claim your official Professional Certificate.

Start with Statistics for Data Analysis

What you'll learn, module by module

Work through the modules in order. Open one to see exactly what it covers.

1Module 1FoundationThe statistics and Python every data scientist relies on.

Professional courseLevel 2 · Practical Skills

Statistics for Data Analysis

Distributions, sampling, confidence intervals and tests: the language of uncertainty.

About 8 hours

You'll learn

Statistics for Analysts
Averages: Mean, Median and Mode
Spread: Range, IQR and Standard Deviation
Distributions and Outliers
Rates, Percentages and Weighted Averages
Correlation
Sampling and the Normal Distribution
Confidence Intervals
Comparing Groups
Regression and Trends
Final Project

Professional courseLevel 2 · Practical Skills

Python for Data Analytics

pandas for loading, cleaning, reshaping and exploring data.

About 9 hours

You'll learn

Python and Colab for Analysts
Lists, Dictionaries, Loops and Functions
DataFrames: Load and Explore
Filtering and Sorting
Calculated Columns and Dates
Cleaning Messy Data
groupby and Aggregation
Merging Tables
Pivot Tables and Trends
Charts with pandas and matplotlib
From Question to Insight
Final Project

Professional courseLevel 2 · Practical Skills

SQL for Data Analysis

Get your own data out of databases.

About 10 hours

You'll learn

Introduction to Databases
Relational Databases and SQL Tools
SELECT
WHERE
ORDER BY
LIMIT
Aggregate Functions
GROUP BY
HAVING
JOINs
CASE Statements
Subqueries
CTEs
Window Functions
Business Analysis with SQL
Final Project

2Module 2CoreBuild and evaluate models properly.

Professional courseLevel 3 · Professional

Machine Learning Fundamentals

Regression and classification with scikit-learn, from baselines to cost-based thresholds and model cards.

About 9 hours

You'll learn

What Machine Learning Is
Preparing Data for a Model
Train, Test and Baselines
Linear Regression
Trees, Forests and Overfitting
Cross-validation and Tuning
Classification and Logistic Regression
Evaluating Classifiers and Choosing Thresholds
Explaining Models and Responsible ML
From Model to Decision
Final Project

Professional courseLevel 3 · Professional· Optional

Advanced SQL

Window functions, cohorts and data quality checks for building features.

About 6 hours

You'll learn

Readable SQL and NULL Traps
Date Logic
Data Quality Checks
Window Functions in Depth
Top N per Group and Deduplication
Cohorts and Retention
Pivots and Period Comparisons
Advanced Joins
Query Performance
Business Analysis Patterns
Final Project

Professional courseLevel 3 · Professional

Feature Engineering and Model Evaluation

Point-in-time features, time-based validation, calibration, lift and drift, on a mobile wallet's churn.

About 7 hours

You'll learn

Features and Point-in-Time Thinking
Features from Events
Leakage Across Time
Gradient Boosting and Model Comparison
Calibration
Lift and Targeting
Drift and Retraining
Final Project

3Module 3SpecialistGo further into the methods data science teams use.

Professional courseLevel 3 · Professional

Time Series Forecasting

Forecast demand with seasonality, events and honest backtests, and turn it into orders.

About 7 hours

You'll learn

Forecasting for Decisions
Trend, Seasonality and Events
Baselines and Honest Testing
Regression with Calendar Features
Promotions, Events and Structural Breaks
Backtesting over Time
Uncertainty and Ordering
Forecasting Many Series
Final Project

Professional courseLevel 3 · Professional

Experimentation and A/B Testing

Design tests, size samples, catch broken splits and read results without fooling yourself.

About 7 hours

You'll learn

Why Experiment
Designing a Test
Running a Test Properly
Analysing Conversion Tests
Analysing Continuous Metrics
Segments, Multiple Tests and Novelty
Guardrails and Decisions
When You Can't Randomise
Final Project

4Module 4ProjectsPortfolio work that shows you can take a model from data to decision.

Portfolio projectLevel 4 · Career Projects

Employee Analytics

Who leaves, when, and why: a natural first prediction problem.

Portfolio projectLevel 4 · Career Projects

Sales Performance Analysis

Explore drivers of revenue before modelling them.

CapstoneLevel 4 · Career Projects

Data Scientist Capstone: From Model to Decision

From a vague request to a trial-tested calling policy, with fairness checks and a monitoring plan.

About 12 hours

You'll learn

The Problem and the Plan
Audit the Data
Point-in-Time Features
Validate over Time
Calibration and Capacity
The Trial and Who to Call
Fairness and Explanation
Monitoring and the Final Presentation

5Module 5CareerTurn your skills into applications that get interviews.

Short courseLevel 1 · Foundations

Career Essentials

An ATS-friendly CV and a LinkedIn profile recruiters can find.

1 hr 30 min

You'll learn

Build a CV with AI
A Professional LinkedIn Profile
Quick Excel Analysis

Short courseLevel 1 · Foundations· Optional

Build Your Student Portfolio

One link that shows your notebooks and model cards.

1 hr 25 min

You'll learn

Plan Your Portfolio
Show Your Work
Build Your Portfolio Page
Share Your Work on LinkedIn

Courses marked "In preparation" join the programme when they're ready. If you've already earned the programme badge by then, you keep it.