Online Courses

Self-paced courses with video lectures, hands-on projects, and comprehensive learning paths.

> make an AI agentclass Agent:  def run(self, task):    return self.think(task)
Agentic Engineering

Agentic Engineering

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Learn to build and ship full-stack web applications using agentic AI coding tools. From first mockup to deployed product — master prompting, spec-driven design, databases, auth, and CI/CD with AI as your co-pilot.

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▸Prompt
◆Agent
◫RAG
◓Memory
⌕Search
</>Code
⇄API
⚙Planner
✔Output
AI Agents

AI Agents

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Understand generative AI, NLP, prompting techniques, and how to build intelligent AI agents.

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β = (XᵀX)⁻¹Xᵀyθ = θ − α∇J(θ)σ(x) = 1 / (1 + e⁻ˣ)L = ¹⁄ₙ Σ(ŷ − y)²m = β₁m + (1−β₁)ga · b = Σ aᵢbᵢD = √((x−μ)ᵀΣ⁻¹(x−μ))P(y) = eᶻ / ΣeᶻH = −Σ y log(ŷ)P(A|B) = P(B|A)P(A) / P(B)G = 1 − Σ pᵢ²J + λ‖w‖²
Foundational Machine Learning

Foundational Machine Learning

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50+ video hours, 6+ projects covering ~50 ML topics. From data cleaning to model explainability.

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from sklearn.ensemble import RandomForestClassifierclf = RandomForestClassifier()clf.fit(X_train, y_train)clf.score(X_test, y_test)▸ 0.94
Applied Machine Learning

Applied Machine Learning

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A practical introduction to machine learning: Python environments, core ML concepts, and hands-on projects.

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