Data Analysis
Understand, clean and explore data to uncover meaningful patterns.
Data Science brings together statistics, programming, analytical thinking, machine learning, and domain knowledge to uncover patterns and support better decisions. Our programs are designed to help learners move from foundational data concepts to advanced analytics, machine learning, AI, and real-world data applications.
Understand, clean and explore data to uncover meaningful patterns.
Build the analytical foundation required for data-driven problem solving.
Develop predictive models and intelligent systems from real-world datasets.
Turn complex datasets into clear, actionable visual stories.
Six routes through the category, each built for a different starting point and outcome.
For beginners building a strong foundation in data science.
PythonStatisticsData AnalysisSQLData VisualizationExplore Path 02Build programming and analytical skills using Python.
PythonNumPyPandasMatplotlibData CleaningExploratory AnalysisExplore Path 03Turn business data into actionable insights.
SQLExcelPower BITableauData VisualizationBusiness AnalyticsExplore Path 04Build predictive models and intelligent data-driven applications.
Supervised LearningUnsupervised LearningFeature EngineeringModel EvaluationExplore Path 05Explore the intersection of Data Science, AI and modern intelligent systems.
Deep LearningGenerative AINLPComputer VisionAI ApplicationsExplore Path 06Learn how data is collected, processed, stored and prepared for analytics at scale.
Data PipelinesETLCloud Data PlatformsBig DataData WarehousingExplore PathA representative selection across the category — from first principles to deep learning, generative AI and data engineering.
Python, statistics and the analytical thinking every data role rests on.
Python + StatisticsNumPy, Pandas and the day-to-day craft of working with messy data.
Python + Data AnalysisTurn business data into dashboards decision-makers actually use.
BI + VisualizationQuery, join and aggregate real databases with confidence.
Databases + AnalyticsBuild, tune and evaluate predictive models on real datasets.
ML + Predictive ModelsNeural architectures for vision, language and sequence data.
AI + Deep LearningLLMs, embeddings and retrieval applied to analytical work.
GenAI + DataPipelines, warehousing and the plumbing behind reliable analytics.
Pipelines + CloudLearn how organizations use data to understand problems and make better decisions.
Build skills applicable across technology, finance, healthcare, retail, marketing, manufacturing and more.
Develop capabilities across analytics, machine learning, AI and automation.
Apply data science principles across industries, business functions and technical roles.
You work through the complete data science lifecycle rather than watching tutorials about it.
Organised by their role in the data lifecycle — from sources and engineering through analytics and machine learning to AI-driven decisions.
A realistic progression, from first dataset to analytics leadership.
Modern Data Science is evolving beyond traditional analytics. AI and machine learning are enabling organizations to extract deeper insights, automate analysis and build intelligent products.
Use historical data to identify patterns and forecast future outcomes.
Use modern AI models to interact with datasets and generate useful insights.
Combine analytics, machine learning and AI to accelerate decision-making.
Build applications that use data, models and AI to solve real-world problems.
Analyze customer behavior and build a model to identify potential churn.
Python + Pandas + Machine Learning + VisualizationAnalyze historical sales data and develop forecasting models.
Python + Statistics + Time Series + VisualizationIdentify unusual transaction patterns using machine learning.
Data Analysis + Feature Engineering + MLTransform business data into an interactive decision-making dashboard.
SQL + Power BI + Data VisualizationBuild a system that recommends products or content based on user behavior.
Python + Machine Learning + Data ModelingBuild an application that allows users to interact with datasets using natural language.
LLM + Data + Python + AI ApplicationBuild a strong foundation in data analysis, programming and machine learning.
Develop the skills needed to work with business and operational data.
Add data science, machine learning and AI capabilities to existing development skills.
Follow a structured learning path toward data-focused technology careers.
Use data and analytics to improve decision-making within their existing roles.
Upskill teams in analytics, BI, machine learning and AI.
Equip your teams with practical data skills that help transform business information into measurable insights and better decisions.
Partner with TEVVO to provide students with practical data science education, modern technology exposure and industry-oriented projects.
The lifecycle every programme follows, so the way you learn matches the way data teams actually work.
Gather data from relevant sources.
Clean, transform and structure it.
Find patterns, relationships and anomalies.
Apply statistical techniques.
Build and evaluate predictive models.
Communicate through dashboards.
Turn insights into business action.
Issued for each completed course, with a verification ID.
Awarded once your analysis or model passes practitioner review.
Granted on finishing a full learning path and its assessments.
For advanced programmes, subject to partner availability.
Industry and academic credentials are shown where a partner programme applies.
Build the skills to analyze data, uncover insights and create intelligent solutions for the future.