Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The online program offered by edX imparts wisdom to the participants in the concepts like preconditioning, linearity, newton's local method, modeling, transformations, solving equations, newton's method, descent methods, optimality conditions, formulation, convexity, differentiability, one variable, several variables, inexact line search, preconditioned the steepest descent, conditioning, and quadratic functions.
The certificate is offered to the successful participants on course completion. The certificate has the signature of the instructor and it is verified by the institution. The Optimization: principles and algorithms - Unconstrained nonlinear optimization online course is offered by edX in association with EPFL. The candidates can easily complete the Optimization: principles and algorithms - Unconstrained nonlinear optimization certification course with only 6 to 8 hours of effort needed on a weekly basis.
Optimization: principles and algorithms - Unconstrained nonlinear optimization training is a self-paced course, meaning that it allows its candidates to learn and grow at their own pace and time. The introductory level course also includes the facility of financial aid so that any candidate’s financial instability doesn't come in their way to a promising career.
The Highlights
- Self-paced programme
- Introductory level course
- The programme offered by EPFLx institution
- 6 weeks course duration
- Shareable certificate provided by edX
- Requires just 6 to 8 hours of weekly effort
- Online programme
Programme Offerings
- Video sessions
- discussions
- assignments
- quizzes
Courses and Certificate Fees
| Fees Informations | Certificate Availability | Certificate Providing Authority |
|---|---|---|
| INR 4923 | yes | Swiss Federal Institute of Technology Lausanne |
- The cost of the verified program is Rs. 4,923
- The audit tracks can be attempted free of cost
Optimization: principles and algorithms - Unconstrained nonlinear optimization fee
Fee category | Amount |
Certification fee | Rs. 4,923 |
Note: The learner can apply coupons provided on the website to avail discount on the fee.
Eligibility Criteria
Education
The participants of Optimization: principles and algorithms - Unconstrained nonlinear optimization online course must have basic knowledge in Analysis, Linear algebra, and Calculus. The participants should also have knowledge of a python programming language. But the participants can also pursue the course without the knowledge of programming.
Certification Qualifying Details
The learner must enrol themselves in the verified track of the online course and must maintain more than 60% marks in their final exam average score to avail Optimization: principles and algorithms - Unconstrained nonlinear optimization certification. The candidate can track their progress on the progress page.
What you will learn
The participants will learn the following concepts by pursuing the programme by edX.
- The participants will learn simple examples to characterize, transform, and formulate the optimization problem.
- The participant will understand the importance of optimization.
- The candidate will also learn necessary and sufficient conditions for the optimal solution
- They will also understand concepts that would help them to solve the nonlinear equations.
- The learner will understand the family of the descent methods and their connection with Newton’s method in the programme
- Concepts like differentiability and preconditioning are briefly discussed in the Optimization: principles and algorithms - Unconstrained nonlinear optimization programme.
- Under the course, the candidates will learn to adapt and interpret newton’s method in optimization
- The candidate will learn about exact and inexact line search in Optimization: principles and algorithms - Unconstrained nonlinear optimization certification syllabus
- The participants will learn to solve optimality conditions.
- They will also learn sufficient and necessary optimality conditions.
Who it is for
The program is specially developed for the following candidates.
- All participants who want to understand non-linear polarisation can take up the Optimization: principles and algorithms - Unconstrained nonlinear optimization program
Admission Details
The users can follow the simple registration steps which are mentioned below to get admission.
Step 1: The learner shall visit the link https://www.edx.org/learn/algorithms/ecole-polytechnique-federale-de-lausanne-optimization-principles-and-algorithms-unconstrained-nonlinear-optimization
Step 2: If the learner has an account they can directly sign in and register, else they can create an account using their Google or Facebook or email account.
Step 3: After creating an account, the learner must sign in and search for the required course
Step 4: Then, they should click “Enrol” to get admission to the audio track of the programme.
Step 5: If the learner requires a certificate, then they can upgrade to verified track by clicking “Upgrade Now”
Step 6: Then, the learner shall enter all the personal and billing details and click “Place order”
Step 7: They can also use coupons while making payments
Step 8: When the payment is approved, the candidate will be moved to the verified track of Optimization: principles and algorithms - Unconstrained nonlinear optimization programme.
The Syllabus
- Welcome
- What this course is about
- Practical information
- Introduction
- Modeling
- Transformations
- Problem definition
- Introduction
- Convexity
- Differentiability: the first order
- Differentiability: the second order
- Linearity and non-linearity
- Conditioning and preconditioning
- Introduction
- Necessary optimality conditions
- Sufficient optimality conditions
- Quadratic functions
- Introduction
- One variable
- Several variables
- Introduction
- Solving optimality conditions
- Geometric interpretation
- Introduction
- Preconditioned steepest descent
- Exact line search: quadratic interpolation
- Exact line search: Golden section
- Inexact line search
- Newton with line search
- Questions
- Formulation
- Objective function
- Optimality conditions
- Solving equations: Newton
- Newton's local method
- Descent methods
- Questions
- Formulation
- Objective function
- Optimality conditions
- Solving equations: Newton
- Newton's local method
- Descent methods