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AI & Deep Learning

Math & Statistics for AI and Deep Learning

A practical math track connecting the foundations of linear algebra, calculus, probability, and statistics directly to machine-learning and deep-learning practice.

๐Ÿ“š 4 units ๐Ÿชœ 20 steps / lessons โฑ๏ธ Self-paced
This course / diploma is coming soon
This course is coming soon โ€” register your details and we'll notify you when it launches.
Expected launch: Q3 2026
Pricing on launch

Available as part of AI diploma bundles

ุงู„ูƒูˆุฑุณ ุฏู‡ ู‚ูŠุฏ ุงู„ุชุญุถูŠุฑ โ€” ุณุฌู„ ุจูŠุงู†ุงุชูƒ ูˆู‡ู†ุจู„ุบูƒ ุฃูˆู„ ู…ุง ูŠู†ุฒู„.

๐Ÿš€ Enrollment opens soon ๐Ÿ”” Sign up to be notified
Outcomes3
Tools0
Projects0
CertificateVerified

What you will learn

  • โœ… Understand vectors, matrices, and dimensionality reduction
  • โœ… Reason about gradients and optimization
  • โœ… Use probability and statistics to evaluate models correctly

Curriculum & units

๐Ÿ“š 4 units ๐Ÿชœ 20 steps โฑ๏ธ Flexible
Unit 0: Introduction and Logistics 1 topics ยท Flexible pace
  • Introduction โ€” Motivation, course overview, logistics.
Unit 1: Linear Algebra 13 topics ยท Flexible pace
  • Vectors & Matrices โ€” Vector definition, notation, and geometric interpretation
  • Vectors & Matrices โ€” Matrices as data tables (Rows=Samples, Cols=Features)
  • Vectors & Matrices โ€” Basic operations: Transpose, Addition, Scalar Multiplication
  • Vectors & Matrices โ€” Matrix Inversion: Concept and conditions for invertibility
  • Similarity & Distances โ€” Dot Product (Inner Product) mechanics and implementation
  • Similarity & Distances โ€” Geometric meaning of Dot Product (Angles & Orthogonality)
  • Similarity & Distances โ€” Vector Norms: L1 (Manhattan) vs L2 (Euclidean)
  • Linear Mappings โ€” Matrix-Vector multiplication as a transformation
  • Linear Mappings โ€” Understanding Neural Net layers as Linear Maps
  • Linear Mappings โ€” Determinants: Geometric interpretation (Volume scaling)
  • Dimensionality Reduction โ€” Eigenvalues and Eigenvectors (Intuition & Geometric meaning)
  • Dimensionality Reduction โ€” Singular Value Decomposition (SVD) basics
  • Dimensionality Reduction โ€” PCA concept: Directions of maximum variance
Unit 2: Calculus 11 topics ยท Flexible pace
  • Derivatives & Gradients โ€” Partial Derivatives: Measuring sensitivity of one variable
  • Derivatives & Gradients โ€” The Gradient Vector ($\nabla$): Direction of steepest ascent
  • Derivatives & Gradients โ€” The Jacobian Matrix: Gradients for multi-output functions
  • Derivatives & Gradients โ€” The Hessian Matrix: Curvature and Second Derivatives
  • Derivatives & Gradients โ€” Taylor Series: Local approximation of functions
  • Backpropagation โ€” The Chain Rule for composite functions
  • Backpropagation โ€” Backpropagation algorithm on a computation graph
  • Optimization Algorithms โ€” Gradient Descent: The update rule
  • Optimization Algorithms โ€” Learning Rate effects (Overshooting vs Slow convergence)
  • Optimization Algorithms โ€” Momentum & Adam (Intuition & Update formulas)
  • Optimization Algorithms โ€” Convex vs Non-convex optimization landscapes (Local Minima)
Unit 3: Probability 9 topics ยท Flexible pace
  • Fundamentals โ€” Random Variables: Discrete vs Continuous
  • Fundamentals โ€” Joint, Marginal, and Conditional Probability definitions
  • Fundamentals โ€” Sum & Product Rules of Probability
  • Fundamentals โ€” Information Theory: Entropy and Information Content
  • Fundamentals โ€” Information Theory: KL Divergence and Cross-Entropy
  • Distributions โ€” Common Distributions: Gaussian (Normal), Bernoulli
  • Distributions โ€” Expectation (Mean) and Variance: Calculation & Meaning
  • Bayes Rule โ€” Bayes' Theorem: Prior, Likelihood, Posterior
  • Bayes Rule โ€” Updating model beliefs with new data
Unit 4: Statistics & Metrics 8 topics ยท Flexible pace
  • Parameter Estimation โ€” Maximum Likelihood Estimation (MLE)
  • Inference โ€” Sampling: Empirical Means vs True Means
  • Inference โ€” Confidence Intervals & Variance
  • Inference โ€” A/B Testing: Comparing two distributions (Model Selection)
  • Loss Functions โ€” Regression Losses: MSE (Mean Squared Error), MAE
  • Loss Functions โ€” Classification Losses: Log-Loss (Cross-Entropy)
  • Model Evaluation โ€” Regularization: L1 (Lasso) vs L2 (Ridge) penalties
  • Model Evaluation โ€” Cross-Validation techniques

Projects you will build

Tools & platforms

Target audience

  • Students who want a solid AI foundation
  • Engineers weak in math prerequisites
  • ML learners who want intuition before formulas

Career paths

What you receive after finishing

Verification-ready certificates and HR-friendly training letters.

๐Ÿ†

Verified Certificate

Official Learn in Depth completion certificate with QR verification.

Verifiable on the public verification page.

๐Ÿ‡ฌ๐Ÿ‡ง

English Training Letter

For international companies and overseas employment.

On official Learn in Depth letterhead, signed by the instructor.

๐Ÿ‡ช๐Ÿ‡ฌ

Arabic Training Letter

For local employers in MENA and university coordination.

Bilingual stamped letter ready for HR submission.

๐Ÿข

Company-Stamped Certificate

Company-stamped, for academic credit. Request it by contacting +20 155 876 5064 via WhatsApp or phone.

Issued upon request after successful completion.

Course FAQ

The current target is Q3 2026. Register via the form and we will send launch and pricing updates first.

ุงู„ู…ุณุชู‡ุฏู ุงู„ุญุงู„ูŠ ู‡ูˆ Q3 2026. ุณุฌู‘ู„ ุจูŠุงู†ุงุชูƒ ููŠ ุงู„ููˆุฑู… ูˆุณู†ุฑุณู„ ู„ูƒ ุฃูˆู„ ุชุญุฏูŠุซุงุช ุงู„ุฅุทู„ุงู‚ ูˆุงู„ุฃุณุนุงุฑ.

These tracks are currently marked Coming Soon. You can browse the curriculum and leave your details to be notified when registration opens.

ุญุงู„ูŠู‹ุง ุงู„ู…ุณุงุฑุงุช ููŠ ุญุงู„ุฉ Coming Soon. ุชู‚ุฏุฑ ุชุชุตูุญ ุงู„ู…ุญุชูˆู‰ ูˆุชุณุฌู„ ุงู‡ุชู…ุงู…ูƒ ู„ู†ุจู„ุบูƒ ุนู†ุฏ ูุชุญ ุงู„ุชุณุฌูŠู„.

Yes โ€” every track is designed around a verified certificate and hands-on project review.

ุฃูŠูˆุฉ โ€” ูƒู„ ู…ุณุงุฑ ู…ุตู…ู… ุจุดู‡ุงุฏุฉ ู…ูˆุซู‚ุฉ ูˆู…ุฑุงุฌุนุฉ ุนู…ู„ูŠุฉ ู„ู„ู…ุดุงุฑูŠุน ุงู„ุฑุฆูŠุณูŠุฉ.

Yes. The positioning, support, and project design target engineers in the Egyptian and Gulf markets with a strong practical hiring focus.

ุฃูŠูˆุฉุŒ ุงู„ุชุณูˆูŠู‚ ูˆุงู„ุฏุนู… ูˆุจู†ุงุก ุงู„ู…ุดุงุฑูŠุน ู…ุนู…ูˆู„ูŠู† ุฎุตูŠุตู‹ุง ู„ู…ู‡ู†ุฏุณูŠู† ุงู„ุณูˆู‚ ุงู„ู…ุตุฑูŠ ูˆุงู„ุฎู„ูŠุฌูŠ ู…ุน ุชุฑูƒูŠุฒ ุนู„ู‰ ุงู„ุชูˆุธูŠู ุงู„ุนู…ู„ูŠ.

Create your account, add the course to cart, and follow the payment steps.

ุณุฌู„ ุญุณุงุจูƒ ูˆุฃุถู ุงู„ูƒูˆุฑุณ ู„ู„ุณู„ุฉ ูˆุงุชุจุน ุฎุทูˆุงุช ุงู„ุฏูุน.

Yes โ€” students get an automatic discount shown at checkout.

ุฃูŠูˆู‡ โ€” ุงู„ุทู„ุจุฉ ู„ูŠู‡ู… ุฎุตู… ุฎุงุต ุจูŠุธู‡ุฑ ุฃูˆุชูˆู…ุงุชูŠูƒ.

All courses are recorded so you can learn at your own pace.

ูƒู„ ุงู„ูƒูˆุฑุณุงุช ู…ุณุฌู„ุฉ ุนุดุงู† ุชุชุนู„ู… ููŠ ุฃูŠ ูˆู‚ุช ูŠู†ุงุณุจูƒ.

Yes โ€” all courses are free for people from Palestine.

ุฃูŠูˆู‡ โ€” ูƒู„ ุงู„ูƒูˆุฑุณุงุช ู…ุฌุงู†ูŠุฉ ู„ุฃู‡ู„ ูู„ุณุทูŠู†.

Bank transfer, Vodafone Cash, InstaPay.

ุชุญูˆูŠู„ ุจู†ูƒูŠุŒ ููˆุฏุงููˆู† ูƒุงุดุŒ ุฅู†ุณุชุงุจุงูŠ.

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