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AI Upskilling Program

Learn AI.
Build systems that work.

Learn from AI fundamentals to real-world systems & tools, guided by mentors and built around hands-on projects.

Start LearningRead The Curriculum
Learners enrolled
6,000+Learners enrolled
Countries
56Countries
Months, part-time
6 - 9Months, part-time
Complete the capstone
92%Complete the capstone
PythonPandasRAGScikit-learnXGBoostPyTorchTensorFlowTransformersRetrievalSparkPower BIAgentsPythonPandasRAGScikit-learnXGBoostPyTorchTensorFlowTransformersRetrievalSparkPower BIAgents

The community

Six thousand learners, fifty-six countries

Drag the globe, or pick a city and it will spin to it. Every marker is a place with people currently working through the program.

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and 47 more countries6,661

The map

The World of AI

Every field nests inside the one before it. Click any of the 89 terms to open its explainer, each has its own page with a plain-language definition.

Artificial IntelligenceMachine LearningNeural NetworksDeep LearningGenerative AIReinforcementLearningSpeechRecognitionEmergentBehaviorAugmentedProgrammingAI EthicsExpert SystemsComputerVisionSymbolic AIAutomatedReasoningConstraintSatisfactionNatural LanguageProcessingRoboticsKnowledgeGraphsMulti-AgentSystemsEvolutionaryComputationSwarmIntelligenceSupervisedLearningUnsupervisedLearningK-MeansK-NearestNeighboursLogisticRegressionLinearRegressionPCAHypothesisTestingDecision TreesSupport VectorMachinesActiveLearningAnomalyDetectionNaive BayesRandom ForestsGradientBoostingXGBoostLightGBMCatBoostDBSCANHierarchicalClusteringt-SNEUMAPGaussianProcessesRecommendationSystemsPerceptronBackpropagationFeed ForwardHopfieldNetworkBoltzmannMachineSelf OrganisingMapsDeep BeliefNetworkLiquid StateMachinesWeights andBiasesActivationFunctionsGradientDescentAdamResidualConnectionsCNNRNNLSTMTransformersAuto EncodersDeep RLEpochsAttentionSelf-AttentionGated RecurrentUnitResNetU-NetVisionTransformersModel PruningQuantisationMixture ofExpertsLLMGPTBERTGANsRLHFQLoRAAgentsTransferLearningFoundationalModelN-Shot

The syllabus

Seven modules, taken in order

Twenty-six weeks full-time, thirty-six part-time. The first two modules are open to read in full — the rest unlock when you register.

Module I

Fundamentals

Weeks 1–5 · Open

Core PythonVariables, control flow, collections, comprehensions, classes and modules — written the way production code is written, not the way tutorials write it.
Python for Data ScienceNumPy and Pandas in depth: dataframes, joins, groupbys, descriptive statistics, distributions, and visualisation that actually answers a question.
SQLQuery, aggregate and window over relational data. Schema design, indexes, and the query patterns that come up in every analytics interview.
Excel & Power BITurn a messy sheet into a dashboard a stakeholder can read. Modelling, DAX basics, and the reporting layer most AI teams still run on.

Module II

Supervised Learning

Weeks 6–11 · Open

Model PreparationCleaning, encoding, scaling, leakage, train/test discipline and cross-validation. The unglamorous half that decides whether a model works.
ClassificationLogistic regression, decision trees, gradient boosting. Precision, recall, ROC-AUC, and choosing a threshold for a business, not a leaderboard.
RegressionPredicting continuous outcomes, regularisation, residual analysis, and reading what a coefficient really claims.
Similarity ModelsDistance metrics, k-nearest neighbours and the recommendation patterns behind "people also bought".
Random ForestsBagging, ensembles and feature importance — why a forest beats a tree and where it still falls over.
Support Vector MachinesMargins, kernels and high-dimensional data. When SVMs remain the sharper tool over a neural network.
Modules III–VII

Register to unlock the rest

Creating an account opens the full syllabus, the project briefs and the reading list. It takes a minute and costs nothing.

Unlock The Full Curriculum
Open the full curriculum page

Real World Projects

Six months from your first dataset
to an AI system you can defend.

Don’t just learn AI, ship systems that work. Every stage of the program ends with something you can demonstrate, explain and add to your portfolio.

github.com/aifolks/retail-intelligence-dashboard
Margin by region, refreshed nightly
PythonPandasPostgreSQLPower BI
Start Building →View Labs →

Stories

The people who finished

Six thousand learners, and these are the outcomes we hear about most: a first ML role, a promotion into a data team, or a career changed after a decade in something else.

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Writing

From the blog

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It is free, it is the real curriculum, and if it is not for you, you have lost nothing but an evening.

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