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Video Production with Adobe
4 Courses123 TasksBeginner
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UI/UX Design Tools
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Essential Office Skills
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Business AI Toolkit
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course
Latent Space Geometry in LLMs
A concept-driven, upper-intermediate course exploring how large language models encode, organize, and manipulate information within high-dimensional latent spaces. Emphasis is placed on geometric intuition, manifold structure, linearity, and the relationship between geometry and model behavior.
2 hours
9 chaptersAdvanced
course
Linear Algebra and Calculus Foundations
Gain a solid understanding of the mathematical foundations that power machine learning, data science, and engineering. Master vectors, matrices, linear transformations, and multivariate calculus – from dot products and eigenvalues to gradients, Jacobians, and multiple integrals – building the intuition and skills needed to tackle real-world computational problems.
2 hours 21 chaptersBeginner
course
Logging and Monitoring in Spring Applications
A beginner-friendly course designed to introduce and deepen your understanding of logging and monitoring in real-world Spring Boot applications. Learn the essentials of logging frameworks, best practices, and how to monitor your applications for reliability and performance.
1 hour 11 chaptersIntermediate
course
Mapbox Vector Maps in React Apps
Integrate Mapbox vector maps into React applications. Render interactive maps, customize styles and layers, and implement advanced interactivity such as events and geolocation.
2 hours 15 chaptersIntermediate
project
Markdown to HTML Converter
A beginner-friendly Java project that guides learners through building a simple Markdown to HTML converter, introducing core Java concepts such as string manipulation, classes, and basic parsing.
Only for Ultimate
1 hour 6 chaptersBeginner
course
Mean Field Theory for Neural Networks
Explore the mathematical foundations of mean field theory as applied to neural networks in the large-width limit. Gain a rigorous understanding of distributional perspectives, training dynamics, and the theoretical implications for deep learning.
2 hours 9 chaptersAdvanced
course
Mermaid.js Diagrams with JavaScript
Create clear, text driven diagrams using Mermaid.js and JavaScript friendly workflows. Learn how to write and embed diagrams, work with multiple diagram types, and customise their appearance for real documentation and web projects.
1 hour 12 chaptersBeginner
course
Meta-Learning Fundamentals
A theory-first exploration of meta-learning, focusing on mathematical intuition, optimization dynamics, and learning theory. Understand how models learn to learn, the foundations of MAML, and the conceptual landscape of meta-learning methods.
2 hours 9 chaptersAdvanced
course
Model Calibration with Python
Master the principles and practical techniques for measuring, interpreting, and improving the probabilistic calibration of machine learning models. Learn to use reliability diagrams, calibration metrics, and modern calibration methods to ensure your models produce trustworthy probability estimates.
2 hours 15 chaptersIntermediate
project
Mushroom Edibility Classification
A hands-on, end-to-end data science project using Python to classify mushrooms as edible or poisonous based on their characteristics. This project guides you through data loading, cleaning, exploratory analysis, preprocessing, model building, and evaluation using the mushrooms.csv dataset.
Only for Ultimate
1 hour 5 chaptersBeginner
course
Neural Network Attention Mechanisms
A comprehensive, fully theoretical exploration of attention mechanisms in modern neural architectures. This course builds intuition, mathematical understanding, and conceptual clarity around attention, self-attention, multi-head attention, masking, and their role in transformers — without any programming or code.
2 hours 10 chaptersAdvanced
course
Neural Tangent Kernel Theory
A rigorous, theory-driven exploration of Neural Tangent Kernel (NTK) theory: infinite-width limits, Gaussian process correspondence, linearized training, kernel dynamics, and the explanatory boundaries of NTK in deep learning.
2 hours 9 chaptersAdvanced
course
Observability Fundamentals in DevOps
A beginner-friendly course introducing the essential concepts and practical applications of observability in DevOps. Learn how logs, metrics, and traces provide visibility into systems, how to use dashboards and alerts, and how to interpret service health using SLIs and SLOs. Each chapter combines clear explanations with real-world text-based examples to build foundational skills for modern DevOps workflows.
1 hour 11 chaptersBeginner
1 STUDYING NOW
course
Operating Systems for DevOps
A comprehensive course designed for DevOps engineers and backend professionals to master the core concepts of operating systems, understand their impact on system performance and reliability, and apply this knowledge to modern infrastructure, including containers and cloud environments.
1 hour 12 chaptersBeginner
1 STUDYING NOW
course
Outlier and Novelty Detection in Python
A comprehensive, hands-on course exploring the theory, intuition, and practical implementation of outlier and novelty detection algorithms in Python. Learn to identify anomalies using statistical, isolation, density, and kernel-based methods, interpret results, and compare approaches for real-world applications.
3 hours 22 chaptersIntermediate
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Unsure where
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Career tracks
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Only for UltimateGame Development with Unity
4 Courses214 TasksBeginner
4.4
(362)
track
Only for UltimateVideo Production with Adobe
4 Courses123 TasksBeginner
5.0
(15)
track
Only for UltimateUI/UX Design Tools
4 Courses161 TasksBeginner
4.6
(34)
track
Only for UltimateEssential Office Skills
3 Courses75 TasksBeginner
4.5
(1022)
track
Only for UltimateBusiness AI Toolkit
3 Courses42 TasksBeginner
4.1
(121)
track
Only for Ultimate
Game Development with Unity
4 Courses214 Tasks 4.4
track
Only for Ultimate
Video Production with Adobe
4 Courses123 Tasks 5.0
track
Only for Ultimate
UI/UX Design Tools
4 Courses161 Tasks 4.6
track
Only for Ultimate
Essential Office Skills
3 Courses75 Tasks 4.5
track
Only for Ultimate
Business AI Toolkit
3 Courses42 Tasks 4.1
Courses & Projects
Technologies
course
Latent Space Geometry in LLMs
A concept-driven, upper-intermediate course exploring how large language models encode, organize, and manipulate information within high-dimensional latent spaces. Emphasis is placed on geometric intuition, manifold structure, linearity, and the relationship between geometry and model behavior.
2 hours 9 chaptersAdvanced
course
Linear Algebra and Calculus Foundations
Gain a solid understanding of the mathematical foundations that power machine learning, data science, and engineering. Master vectors, matrices, linear transformations, and multivariate calculus – from dot products and eigenvalues to gradients, Jacobians, and multiple integrals – building the intuition and skills needed to tackle real-world computational problems.
2 hours 21 chaptersBeginner
course
Logging and Monitoring in Spring Applications
A beginner-friendly course designed to introduce and deepen your understanding of logging and monitoring in real-world Spring Boot applications. Learn the essentials of logging frameworks, best practices, and how to monitor your applications for reliability and performance.
1 hour 11 chaptersIntermediate
course
Mapbox Vector Maps in React Apps
Integrate Mapbox vector maps into React applications. Render interactive maps, customize styles and layers, and implement advanced interactivity such as events and geolocation.
2 hours 15 chaptersIntermediate
project
Markdown to HTML Converter
A beginner-friendly Java project that guides learners through building a simple Markdown to HTML converter, introducing core Java concepts such as string manipulation, classes, and basic parsing.
Only for Ultimate
1 hour 6 chaptersBeginner
course
Mean Field Theory for Neural Networks
Explore the mathematical foundations of mean field theory as applied to neural networks in the large-width limit. Gain a rigorous understanding of distributional perspectives, training dynamics, and the theoretical implications for deep learning.
2 hours 9 chaptersAdvanced
course
Mermaid.js Diagrams with JavaScript
Create clear, text driven diagrams using Mermaid.js and JavaScript friendly workflows. Learn how to write and embed diagrams, work with multiple diagram types, and customise their appearance for real documentation and web projects.
1 hour 12 chaptersBeginner
course
Meta-Learning Fundamentals
A theory-first exploration of meta-learning, focusing on mathematical intuition, optimization dynamics, and learning theory. Understand how models learn to learn, the foundations of MAML, and the conceptual landscape of meta-learning methods.
2 hours 9 chaptersAdvanced
course
Model Calibration with Python
Master the principles and practical techniques for measuring, interpreting, and improving the probabilistic calibration of machine learning models. Learn to use reliability diagrams, calibration metrics, and modern calibration methods to ensure your models produce trustworthy probability estimates.
2 hours 15 chaptersIntermediate
project
Mushroom Edibility Classification
A hands-on, end-to-end data science project using Python to classify mushrooms as edible or poisonous based on their characteristics. This project guides you through data loading, cleaning, exploratory analysis, preprocessing, model building, and evaluation using the mushrooms.csv dataset.
Only for Ultimate
1 hour 5 chaptersBeginner
course
Neural Network Attention Mechanisms
A comprehensive, fully theoretical exploration of attention mechanisms in modern neural architectures. This course builds intuition, mathematical understanding, and conceptual clarity around attention, self-attention, multi-head attention, masking, and their role in transformers — without any programming or code.
2 hours 10 chaptersAdvanced
course
Neural Tangent Kernel Theory
A rigorous, theory-driven exploration of Neural Tangent Kernel (NTK) theory: infinite-width limits, Gaussian process correspondence, linearized training, kernel dynamics, and the explanatory boundaries of NTK in deep learning.
2 hours 9 chaptersAdvanced
course
Observability Fundamentals in DevOps
A beginner-friendly course introducing the essential concepts and practical applications of observability in DevOps. Learn how logs, metrics, and traces provide visibility into systems, how to use dashboards and alerts, and how to interpret service health using SLIs and SLOs. Each chapter combines clear explanations with real-world text-based examples to build foundational skills for modern DevOps workflows.
1 hour 11 chaptersBeginner
1 STUDYING NOW
course
Operating Systems for DevOps
A comprehensive course designed for DevOps engineers and backend professionals to master the core concepts of operating systems, understand their impact on system performance and reliability, and apply this knowledge to modern infrastructure, including containers and cloud environments.
1 hour 12 chaptersBeginner
1 STUDYING NOW
course
Outlier and Novelty Detection in Python
A comprehensive, hands-on course exploring the theory, intuition, and practical implementation of outlier and novelty detection algorithms in Python. Learn to identify anomalies using statistical, isolation, density, and kernel-based methods, interpret results, and compare approaches for real-world applications.
3 hours 22 chaptersIntermediate
course
Latent Space Geometry in LLMs
A concept-driven, upper-intermediate course exploring how large language models encode, organize, and manipulate information within high-dimensional latent spaces. Emphasis is placed on geometric intuition, manifold structure, linearity, and the relationship between geometry and model behavior.
2 hours 9 chaptersAdvanced
course
Linear Algebra and Calculus Foundations
Gain a solid understanding of the mathematical foundations that power machine learning, data science, and engineering. Master vectors, matrices, linear transformations, and multivariate calculus – from dot products and eigenvalues to gradients, Jacobians, and multiple integrals – building the intuition and skills needed to tackle real-world computational problems.
2 hours 21 chaptersBeginner
course
Logging and Monitoring in Spring Applications
A beginner-friendly course designed to introduce and deepen your understanding of logging and monitoring in real-world Spring Boot applications. Learn the essentials of logging frameworks, best practices, and how to monitor your applications for reliability and performance.
1 hour 11 chaptersIntermediate
course
Mapbox Vector Maps in React Apps
Integrate Mapbox vector maps into React applications. Render interactive maps, customize styles and layers, and implement advanced interactivity such as events and geolocation.
2 hours 15 chaptersIntermediate
project
Markdown to HTML Converter
A beginner-friendly Java project that guides learners through building a simple Markdown to HTML converter, introducing core Java concepts such as string manipulation, classes, and basic parsing.
Only for Ultimate
1 hour 6 chaptersBeginner
course
Mean Field Theory for Neural Networks
Explore the mathematical foundations of mean field theory as applied to neural networks in the large-width limit. Gain a rigorous understanding of distributional perspectives, training dynamics, and the theoretical implications for deep learning.
2 hours 9 chaptersAdvanced
course
Mermaid.js Diagrams with JavaScript
Create clear, text driven diagrams using Mermaid.js and JavaScript friendly workflows. Learn how to write and embed diagrams, work with multiple diagram types, and customise their appearance for real documentation and web projects.
1 hour 12 chaptersBeginner
course
Meta-Learning Fundamentals
A theory-first exploration of meta-learning, focusing on mathematical intuition, optimization dynamics, and learning theory. Understand how models learn to learn, the foundations of MAML, and the conceptual landscape of meta-learning methods.
2 hours 9 chaptersAdvanced
course
Model Calibration with Python
Master the principles and practical techniques for measuring, interpreting, and improving the probabilistic calibration of machine learning models. Learn to use reliability diagrams, calibration metrics, and modern calibration methods to ensure your models produce trustworthy probability estimates.
2 hours 15 chaptersIntermediate
project
Mushroom Edibility Classification
A hands-on, end-to-end data science project using Python to classify mushrooms as edible or poisonous based on their characteristics. This project guides you through data loading, cleaning, exploratory analysis, preprocessing, model building, and evaluation using the mushrooms.csv dataset.
Only for Ultimate
1 hour 5 chaptersBeginner
course
Neural Network Attention Mechanisms
A comprehensive, fully theoretical exploration of attention mechanisms in modern neural architectures. This course builds intuition, mathematical understanding, and conceptual clarity around attention, self-attention, multi-head attention, masking, and their role in transformers — without any programming or code.
2 hours 10 chaptersAdvanced
course
Neural Tangent Kernel Theory
A rigorous, theory-driven exploration of Neural Tangent Kernel (NTK) theory: infinite-width limits, Gaussian process correspondence, linearized training, kernel dynamics, and the explanatory boundaries of NTK in deep learning.
2 hours 9 chaptersAdvanced
course
Observability Fundamentals in DevOps
A beginner-friendly course introducing the essential concepts and practical applications of observability in DevOps. Learn how logs, metrics, and traces provide visibility into systems, how to use dashboards and alerts, and how to interpret service health using SLIs and SLOs. Each chapter combines clear explanations with real-world text-based examples to build foundational skills for modern DevOps workflows.
1 hour 11 chaptersBeginner
1 STUDYING NOW
course
Operating Systems for DevOps
A comprehensive course designed for DevOps engineers and backend professionals to master the core concepts of operating systems, understand their impact on system performance and reliability, and apply this knowledge to modern infrastructure, including containers and cloud environments.
1 hour 12 chaptersBeginner
1 STUDYING NOW
course
Outlier and Novelty Detection in Python
A comprehensive, hands-on course exploring the theory, intuition, and practical implementation of outlier and novelty detection algorithms in Python. Learn to identify anomalies using statistical, isolation, density, and kernel-based methods, interpret results, and compare approaches for real-world applications.
3 hours 22 chaptersIntermediate
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