Optimization Curriculum — Daily Study Material

10-week, 175-hour optimization program. 2.5 hours/day, 7 days/week.

Progress Tracker

Phase I: Mathematical Foundations (Weeks 1–2)

Week 1 — Linear Algebra + Calculus for Optimization

• [ ] Day 1: Vectors, Matrices, Transformations
• [ ] Day 2: Eigenvalues, PD, SVD
• [ ] Day 3: Gradients and Jacobians
• [ ] Day 4: Hessians and Taylor Expansion
• [ ] Day 5: Convexity
• [ ] Day 6: Optimality Conditions
• [ ] Day 7: Week 1 Review

Week 2 — Advanced Foundations + Iterative Methods

• [ ] Day 8: Matrix Decompositions
• [ ] Day 9: Sparse Matrices & Schur Complement
• [ ] Day 10: Numerical Differentiation
• [ ] Day 11: Automatic Differentiation
• [ ] Day 12: Conditioning & Preconditioning
• [ ] Day 13: Iterative Methods (CG)
• [ ] Day 14: Week 2 Review

Phase II: Unconstrained Optimization (Weeks 3–4)

Week 3 — Core Methods

• [ ] Day 15: Gradient Descent
• [ ] Day 16: Line Search & Wolfe
• [ ] Day 17: Newton's Method
• [ ] Day 18: Trust Region Methods
• [ ] Day 19: BFGS
• [ ] Day 20: Conjugate Gradient Optimization
• [ ] Day 21: Week 3 Review

Week 4 — Advanced Unconstrained

• [ ] Day 22: Convergence Theory
• [ ] Day 23: Momentum Methods
• [ ] Day 24: Stochastic Methods
• [ ] Day 25: Regularization
• [ ] Day 26: Global Optimization
• [ ] Day 27: scipy.optimize Deep Dive
• [ ] Day 28: Week 4 Review & Miniopt Capstone

Phase III: Nonlinear Least Squares + Ceres (Weeks 5–6)

Week 5 — NLS Theory & scipy

• [ ] Day 29: Linear Least Squares
• [ ] Day 30: Weighted & Generalized LS
• [ ] Day 31: Gauss-Newton
• [ ] Day 32: Levenberg-Marquardt
• [ ] Day 33: Robust Estimation
• [ ] Day 34: scipy least_squares
• [ ] Day 35: Fisher Info + Capstone

Week 6 — Ceres Solver (C++)

• [ ] Day 36: Ceres Introduction
• [ ] Day 37: Ceres AutoDiff
• [ ] Day 38: Ceres Loss Functions
• [ ] Day 39: Ceres Robotics
• [ ] Day 40: Solver Config & Debugging
• [ ] Day 41: Lie Groups & Manifolds
• [ ] Day 42: Multi-Sensor Calib Capstone

Phase IV: Constrained + Convex Optimization (Weeks 7–8)

Week 7 — Constrained Optimization

• [ ] Day 43: Lagrange Multipliers
• [ ] Day 44: KKT Conditions
• [ ] Day 45: Penalty & Barrier
• [ ] Day 46: Linear Programming
• [ ] Day 47: Quadratic Programming
• [ ] Day 48: Nonlinear Programming
• [ ] Day 49: Robot Arm Capstone

Week 8 — Convex Optimization + MPC

• [ ] Day 50: Convex Theory + SOCP/SDP
• [ ] Day 51: CVXPY
• [ ] Day 52: OSQP Real-Time
• [ ] Day 53: MPC Theory
• [ ] Day 54: MPC 2D Robot
• [ ] Day 55: NMPC + CasADi
• [ ] Day 56: Warehouse MPC Capstone

Phase V: Robotics Applications (Weeks 9–10)

Week 9 — SLAM & Factor Graphs

• [ ] Day 57: Factor Graphs
• [ ] Day 58: 1D Pose Graph
• [ ] Day 59: 2D Pose Graph
• [ ] Day 60: g2o
• [ ] Day 61: GTSAM + iSAM2
• [ ] Day 62: Robust SLAM
• [ ] Day 63: SLAM Pipeline Capstone

Week 10 — Advanced Applications

• [ ] Day 64: Calibration + Temporal
• [ ] Day 65: Trajectory Optimization
• [ ] Day 66: Numerical Debugging
• [ ] Day 67: Real-Time Optimization
• [ ] Day 68: Software Landscape + Distributed
• [ ] Day 69-70: Final Capstone

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Total: 70 days × 2.5 hours = 175 hours

How to use: Work through one day at a time. Check the box when complete. Each day links to a detailed study file with theory, code, exercises, and expert challenges.