Module 1
Introduction to Data Science & Analytical Thinking
Understand what Data Science is, how Data Scientists approach problems, and how data is used to solve real-world challenges.
Practical project: Data Science Problem & Opportunity Map
Data
Data Science
Build a practical foundation in Data Science: learn how to work with data, uncover patterns, communicate insight and develop the analytical thinking used across modern organisations.
What is Data Science?
Data Science combines statistics, programming, data analysis, machine learning and problem-solving to turn raw information into useful insights and intelligent solutions. Learners build technical and analytical foundations using Python, databases, statistics and machine learning, then bring those skills together in practical projects.
What you’ll
learn.
Explore the 12-module curriculum. Each stage builds toward practical application, with a project attached to every module so you develop evidence of what you can do.
Module 2
Python Foundations for Data Science
Learn the programming foundations required to work with data using Python.
Practical project: Python Data Exploration Notebook
Module 3
Statistics & Probability for Data Science
Develop the statistical foundation needed to understand patterns, relationships, and uncertainty in data.
Practical project: Statistical Data Investigation
Module 4
Data Cleaning, Preparation & Exploratory Analysis
Learn how to transform raw and messy datasets into reliable information ready for analysis and modelling.
Practical project: Exploratory Data Analysis Report
Module 5
Databases & SQL for Data Science
Understand how organisations store data and learn how to retrieve information from relational databases.
Practical project: SQL Data Investigation
Module 6
Data Visualisation & Storytelling
Learn how to communicate complex data and analytical findings clearly.
Practical project: Data Science Visual Story
Module 7
Machine Learning Fundamentals
Understand how machines learn from data and how predictive models are developed.
Practical project: First Machine Learning Model
Module 8
Supervised Machine Learning
Learn how models can use historical data to predict outcomes and classify information.
Practical project: Predictive Machine Learning Model
Module 9
Unsupervised Learning & Pattern Discovery
Learn how Machine Learning can uncover hidden patterns when the data does not already contain known outcomes.
Practical project: Customer Segmentation Model
Module 10
Feature Engineering, Model Evaluation & Improvement
Learn how to prepare better inputs, assess model performance, and improve Machine Learning solutions.
Practical project: Machine Learning Model Evaluation Report
Module 11
Applied Machine Learning, AI & Model Deployment
Learn how Data Science models move from experimentation toward practical use.
Practical project: Interactive Machine Learning Application
Module 12
Professional Data Science, Portfolio & Capstone
Bring your technical and analytical skills together into a complete professional Data Science project.
Practical project: Final Data Science Capstone Project
Who should
learn this?
You do not need to fit one exact profile. This programme can support different starting points and career goals.
This course may be right for you if…
- Beginners who enjoy working with information and patterns
- Professionals who want stronger analytical skills
- Business and operations teams
- Career switchers exploring data roles
- Entrepreneurs who want to make data-informed decisions
- Students building a practical digital skill
What you should bring
- Curiosity and willingness to practise consistently
- Access to a laptop and reliable internet
- Time to attend classes and complete practical work
- A willingness to build evidence of what you can do
- No advanced prior experience is required to begin
Roles this skill
can support.
Job titles vary by country and employer. These are examples of career, freelance and business directions where the skills can be relevant.
Data Analyst
Business Intelligence Analyst
Reporting Analyst
Operations Analyst
Marketing Analyst
Business Analyst
Junior BI Developer
Insights Associate
Data/Reporting Assistant
Completing a course does not guarantee a job or qualify every learner immediately for every role listed. Experience, portfolio quality, additional technical depth and employer requirements still matter.
A possible
progression.
This is an illustrative pathway, not a guaranteed promotion sequence. Your route will depend on your portfolio, experience, additional learning, market and the kind of work you pursue.
Stage 1Data Foundations
Stage 2Junior Data Analyst
Stage 3Data Analyst
Stage 4Data Scientist / BI Specialist
Stage 5Senior Data / Insights Professional
Why this skill matters now.
The World Economic Forum lists AI and big data as the fastest-growing skill area and Big Data Specialists among the fastest-growing roles globally.
Global labour-market context is informed by the World Economic Forum Future of Jobs Report 2025 and, where relevant, occupational outlook data. Career outcomes vary by market, experience and employer.
Want the full programme details?
Open the course brochure for the programme overview and additional information, then return here when you are ready to apply.
Frequently asked
questions.
Things prospective learners commonly want to know before applying.
Is this course suitable for a beginner?
Yes. The programme is structured to give beginners a foundation before moving into practical application. You will still need to practise consistently outside live sessions.
Is the programme virtual?
Yes. The cohort is delivered virtually, allowing learners to participate remotely.
How long does it run?
The cohort runs for 3 months with structured learning and practical work.
Will I receive a certificate?
Certification is tied to the Academy’s completion and graduation requirements, including the required participation and coursework standards.
Does completing the course guarantee employment?
No course can responsibly guarantee employment. The goal is to help you build relevant skills, practical evidence and a stronger foundation for employment, freelance work, entrepreneurship or further learning.
How do I apply?
Click “Join the Next Cohort” to open the official Witstart Academy application form.
Ready to start learning Data Science?
Take the next step and submit your application for the next Witstart Academy cohort.