Turn "Knows Some Python"
Into Real Data Scientist.
Knowing Python syntax is a start. Data science is a structured discipline combining statistics, machine learning and deployment that employers expect you to know. This 10-week programme builds all three, and you leave with an end-to-end ML project, deployed and on GitHub.
10 weeks · 100% remote · Certificate + internship on completion · 1,400+ students already trained at VAA Global
More Than a Certificate
Your training comes with practical experience, progress support, and career tools in your student portal.
A course completion certificate and an internship certificate.
No Background Experience Required
You don't need any prior experience to start — the course builds you up from the fundamentals.
Live Instructor-Led Classes
Every class is live on Google Meet, recorded and available for replay anytime in your student portal.
Hands-On Projects & Feedback
Real project work with direct instructor feedback you can add straight to your CV.
Remote Internship
Apply what you learn in a real internship and build genuine portfolio experience.
Student Dashboard
Track attendance, lessons, assignments, quizzes, exams and progress, with badges for milestones.
Course Resource Library
Recordings, sample CVs, project materials and a full student handbook, yours to keep.
Career Bloom Job Matching
Verified job opportunities matched to your exact skill set.
CV Review
One-on-one review and rewrite support for your CV.
LinkedIn Optimisation
A profile rebuild that gets you found by recruiters.
Cover Letter Writing Support
Learn to write cover letters that get you to the interview stage.
Interview Preparation
Mock interviews and coaching before the real thing.
Upwork Proposal Writing
Proposal templates and coaching built specifically for Upwork.
Portfolio Builder Access
A dedicated portfolio builder for eligible certified students.
Job Placement Application
Apply for placement through VAA Global Talent once your internship ends.
VAA Lounge Community
Direct messages, instructor support, voice notes and live calls with your cohort.
Peer Accountability
Built-in structure to help you stay consistent with your own learning goals.
Referral Rewards
Earn rewards for every student you refer who enrolls.
Personalised Matriculation Image
A custom image marking your enrollment, yours to keep and share.
Now I'm Ready to Enrol
You've seen everything that's included. Applications are reviewed in the order they're received.
Apply nowWhy most people who "know some Python" never become real data scientists
Writing Python isn't the problem. These four gaps are what actually keep self-taught learners out of data science roles.
Knows Python but not statistics
Many self-taught learners can write Python but never build the statistical foundation real data science requires.
Never deployed a real model
Knowing how to train a model in a notebook is not the same as deploying it as a real, usable API.
No end-to-end project
Without a complete project from raw data to deployed model, it's hard to prove real data science skill.
No portfolio that gets interviews
Without a structured GitHub portfolio, even skilled candidates get overlooked by hiring managers.
This course closes all four gaps in one connected 10 weeks — and ends with a deployed ML project employers actually want to see.
Graduates who went from "knows Python" to "ships models"
"I knew basic Python but had never built a real model. By week 5 I was training and evaluating real machine learning models. I got hired remotely as a junior data scientist."
Chukwuka E.
Graduate, Lagos
"The MLOps module taught me to actually deploy a model as an API, not just leave it in a notebook. That single project became the centrepiece of my portfolio."
Halimah R.
Graduate, Kano
"I was doing data analysis and wanted to go deeper into machine learning. The statistics and ML fundamentals modules gave me exactly the foundation I needed."
Ikenna V.
Graduate, Enugu
"My sentiment analysis capstone project was the first thing every interviewer wanted to talk about. It directly led to my first data science offer."
Oluwadamilare A.
Graduate, Ibadan
"I had a finance background with zero coding experience. The Python and statistics modules built me up from nothing, and I now work as a data analyst-turned-data-scientist remotely."
Patricia N.
Graduate, Port Harcourt
"I knew basic Python but had never built a real model. By week 5 I was training and evaluating real machine learning models. I got hired remotely as a junior data scientist."
Chukwuka E.
Graduate, Lagos
"The MLOps module taught me to actually deploy a model as an API, not just leave it in a notebook. That single project became the centrepiece of my portfolio."
Halimah R.
Graduate, Kano
"I was doing data analysis and wanted to go deeper into machine learning. The statistics and ML fundamentals modules gave me exactly the foundation I needed."
Ikenna V.
Graduate, Enugu
"My sentiment analysis capstone project was the first thing every interviewer wanted to talk about. It directly led to my first data science offer."
Oluwadamilare A.
Graduate, Ibadan
"I had a finance background with zero coding experience. The Python and statistics modules built me up from nothing, and I now work as a data analyst-turned-data-scientist remotely."
Patricia N.
Graduate, Port Harcourt
"I never thought I would compete on Kaggle. The capstone module walked me through my first real competition, and I placed in the top 30%."
Abiodun F.
Graduate, Lagos
"The supervised learning week on random forests and XGBoost was exactly what I needed. I was hired specifically to build a customer churn model for a fintech startup."
Musa I.
Graduate, Kaduna
"My GitHub portfolio from the capstone project now gets me freelance machine learning contracts on top of my full-time job."
Comfort E.
Graduate, Abuja
"I was a QA tester with no ML background. The structured 10-week path meant I actually understood the math, not just the code."
Chinedu O.
Graduate, Owerri
"The deep learning module gave me enough TensorFlow experience to confidently answer technical interview questions. A European startup hired me remotely two months after graduating."
Ruth M.
Graduate, Jos
"I never thought I would compete on Kaggle. The capstone module walked me through my first real competition, and I placed in the top 30%."
Abiodun F.
Graduate, Lagos
"The supervised learning week on random forests and XGBoost was exactly what I needed. I was hired specifically to build a customer churn model for a fintech startup."
Musa I.
Graduate, Kaduna
"My GitHub portfolio from the capstone project now gets me freelance machine learning contracts on top of my full-time job."
Comfort E.
Graduate, Abuja
"I was a QA tester with no ML background. The structured 10-week path meant I actually understood the math, not just the code."
Chinedu O.
Graduate, Owerri
"The deep learning module gave me enough TensorFlow experience to confidently answer technical interview questions. A European startup hired me remotely two months after graduating."
Ruth M.
Graduate, Jos
I Want Results Like These
Every graduate above started exactly where you are now — the only difference is they applied.
Apply nowTen weeks, in order, with a deployed model at the end
Every week builds on the last — from Python and statistics to a real end-to-end machine learning project you can show employers.
- —What data scientists do
- —The data science process
- —Python environment setup
- —Jupyter notebooks
Teaching yourself vs. ten structured weeks
Teaching yourself
- Structure: Scattered tutorials, no order
- Statistical foundation: Often skipped
- Deep learning and NLP: Rarely covered together
- Model deployment: Notebooks only, never shipped
- Portfolio outcome: Disconnected practice files
Data Science course
- Structure: 10-week structured data science path
- Statistical foundation: Full week on statistics and probability
- Deep learning and NLP: Dedicated weeks on both
- Model deployment: Full week on Flask APIs and Docker
- Portfolio outcome: End-to-end ML project and GitHub portfolio
Built for people ready to build real machine learning models
Graduates and NYSC corpers
You want a high-paying, in-demand technical career with strong remote opportunities.
Data analysts
You already work with data and want to move into machine learning and predictive modelling.
Career switchers from STEM fields
You have a quantitative background and want a structured path into data science.
Aspiring AI and ML engineers
You want the foundational data science skills that AI and ML engineering careers are built on.
This Sounds Like Me — Let's Go
If you recognised yourself in one of those, the next step is simple.
Apply nowEverything included when you enroll
One fee. No hidden add-ons. Built to get you modelling — and hired.
Full Data Science Curriculum
Python, statistics, machine learning and deep learning — 10 structured weeks.
Certificate + Internship
A course completion certificate, an internship placement, and an internship completion certificate — two certificates in total.
End-to-End ML Project and GitHub Portfolio
Build a complete project from raw data to a deployed model for your portfolio.
Access to 100,000+ Remote Job Listings
Curated, regularly updated board with verified remote data science roles worldwide.
1-on-1 Job Assistance and Mentorship
CV review, interview prep and portfolio feedback until you are placed.
VAA Global Talent Job Matching
Top graduates are referred directly to VAA Global Talent's vetted employer network.
Lifetime Access to Course Materials
All recordings, notebooks and frameworks — yours to revisit as your career grows.
Alumni Community Access
Join 1,400+ VAA Global graduates — job leads, rate advice and peer support.
Course fee
₦450,000
One price. Split it into up to 3 payments if that works better for you.
How you can split payment — arranged with the team when you apply
Pay in full
₦450,000
2 parts (most common)
₦315,000 + ₦135,000
3 parts
₦225,000 + ₦112,500 ×2
Money-back if not satisfied in the first week
- Internship starts on enrolment
- Live classes — not pre-recorded
- Lifetime community and material access
- Direct referral to vetted employers
Roles You Can Take as a Data Scientist
Your deployed ML project and certificate aren't just for one job title — they open the door to any of these.
Data Scientist
Builds, trains and evaluates machine learning models to answer real business questions.
Machine Learning Engineer
Takes models from notebook to production, building APIs and pipelines that actually ship.
NLP Engineer
Builds systems that process and understand text — sentiment analysis, chatbots and language models.
Data Science Consultant
Advises companies on where predictive modelling can actually move the needle on revenue or cost.
Analytics Engineer
Bridges data engineering and data science, preparing clean data pipelines models can be trained on.
Applied ML Researcher
Explores and tests new modelling approaches before they go into production systems.
Frequently asked questions
Start your data science career today
Learn from professionals, build a real end-to-end ML project, and walk away with a certificate and access to internships and remote job opportunities worldwide.
Apply now
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