Live, guided learning
Study data science, machine learning and ai through structured sessions, demos, labs and practical implementation.
Build practical data science, machine learning and ai skills
PythonJupyterNumPypandasSQLPower BIscikit-learnTensorFlow
Live
Mentor-Led Training
12 months
Structured Programme
10
Portfolio Projects
Included
UK Career Support
Training built around practical work
Project-first practice
Build 10 portfolio projects that turn concepts into visible proof for interviews and applications.
Career readiness
Shape your CV, LinkedIn, portfolio story and interview confidence around the roles you want.
The right learning path for your data science, machine learning and ai outcomes
Python, Data Foundations and Visualisation
Build the foundations and vocabulary for practical work.
Statistics, SQL and Business Analytics
Connect tools, workflows and business problem solving.
Machine Learning Foundations
Apply the skills through guided builds and review.
Advanced ML, NLP and Deep Learning
Turn your work into a portfolio-ready career story.
Define your target
Map your background to Data Scientist and Machine Learning Engineer opportunities.
Build visible proof
Create practical outputs such as Exploratory Analysis Notebook and Prediction Model Benchmark.
Apply with support
Prepare your CV, LinkedIn, portfolio walkthroughs and interview stories.
The proof stack for career change.
Live
Mentor-Led Training
12 months
Structured Programme
10
Portfolio Projects
Included
UK Career Support
A 12 months roadmap from learning to portfolio proof
Phase 1 · Stage 1
Python, Data Foundations and Visualisation
View phase
Learn
Core concepts, tools and applied workflows for python, data foundations and visualisation.
Build
Exploratory Analysis Notebook
Phase 2 · Stage 2
Statistics, SQL and Business Analytics
View phase
Learn
Core concepts, tools and applied workflows for statistics, sql and business analytics.
Build
Prediction Model Benchmark
Phase 3 · Stage 3
Machine Learning Foundations
View phase
Learn
Core concepts, tools and applied workflows for machine learning foundations.
Build
Customer or Behaviour Segmentation
Phase 4 · Stage 4
Advanced ML, NLP and Deep Learning
View phase
Learn
Core concepts, tools and applied workflows for advanced ml, nlp and deep learning.
Build
Explainable ML Report
Phase 5 · Stage 5
Applied GenAI, LLMs and RAG
View phase
Learn
Core concepts, tools and applied workflows for applied genai, llms and rag.
Build
Time Series Forecasting Dashboard
Phase 6 · Stage 6
MLOps, Deployment, Capstone and Career Prep
View phase
Learn
Core concepts, tools and applied workflows for mlops, deployment, capstone and career prep.
Build
Natural Language Processing Classifier
Build portfolio projects that show real data science, machine learning and ai capability
Exploratory Analysis Notebook
Tools used
Python, Jupyter, NumPy
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Exploratory Analysis Notebook deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Prediction Model Benchmark
Tools used
Jupyter, NumPy, pandas
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Prediction Model Benchmark deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Customer or Behaviour Segmentation
Tools used
NumPy, pandas, SQL
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Customer or Behaviour Segmentation deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Explainable ML Report
Tools used
pandas, SQL, Power BI
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Explainable ML Report deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Time Series Forecasting Dashboard
Tools used
SQL, Power BI, scikit-learn
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Time Series Forecasting Dashboard deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Natural Language Processing Classifier
Tools used
Power BI, scikit-learn, TensorFlow
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Natural Language Processing Classifier deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Computer Vision Application
Tools used
scikit-learn, TensorFlow, OpenAI API
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Computer Vision Application deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
LLM Data Science Assistant
Tools used
TensorFlow, OpenAI API, GitHub
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: LLM Data Science Assistant deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
Production ML Deployment Pipeline
Tools used
OpenAI API, GitHub, Streamlit / Flask
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: Production ML Deployment Pipeline deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
End-to-End Data Science Capstone
Tools used
GitHub, Streamlit / Flask
Business problem: Solve a realistic data science, machine learning and ai problem with a clear business or portfolio outcome.
Final output: End-to-End Data Science Capstone deliverable + walkthrough notes
Portfolio value: Shows practical capability, tool confidence and communication.
From Training to Interviews and Placement Support
Feature 1
Turn learning into portfolio proof
Every stage connects learning to a tangible project, case study or workflow you can explain clearly.
- Exploratory Analysis Notebook
- Prediction Model Benchmark
- Customer or Behaviour Segmentation
Feature 2
Study with structure, not guesswork
Follow a clear roadmap with guided practice, checkpoints and practical expectations.
- Python, Data Foundations and Visualisation
- Statistics, SQL and Business Analytics
- Machine Learning Foundations
Feature 3
Prepare for the roles you actually want
Position yourself for roles such as Data Scientist, Machine Learning Engineer, AI Analyst.
- Data science CV and LinkedIn positioning
- ML, statistics, and project interview prep
- GitHub portfolio and capstone review
Start your data science, machine learning and ai journey with a clear learning plan.
Book a free counselling call and understand the right path based on your background, goals and current skill level.
The best investment is skill you can prove.
Brit 2026
10Portfolio Projects
Brit 2026
12 monthsStructured Program
Brit 2026
CareerSupport Included
Frequently Asked Questions
Can beginners join this course?+
Yes, if you are ready for a structured intermediate programme with regular practice and project work.
What will I learn?+
You will work through Python, Data Foundations and Visualisation, Statistics, SQL and Business Analytics, Machine Learning Foundations, Advanced ML, NLP and Deep Learning and related portfolio projects.
Will I build portfolio projects?+
Yes. The programme includes projects such as Exploratory Analysis Notebook, Prediction Model Benchmark, Customer or Behaviour Segmentation.
Will I receive career support?+
Yes. Support includes Data science CV and LinkedIn positioning, ML, statistics, and project interview prep, GitHub portfolio and capstone review.
What tools are covered?+
Tools and workflows include Python, Jupyter, NumPy, pandas, SQL, Power BI, scikit-learn, TensorFlow.
Will I get a certificate?+
Yes. Learners receive a certificate of completion after meeting the programme requirements.