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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Mathematics for Machine Learning: Multivariate Calculus course provides a brief introduction to multivariate calculus which is necessary for constructing several popular techniques for machine learning. The aim of the course is to provide an intuitive understanding of calculus, as well as the language required to look up concepts when candidates get lost. Candidates can still come away with the courage to dive into some more oriented machine learning courses in the future without going into too much detail.
The Mathematics for Machine Learning: Multivariate Calculus course is the second one of the 3 courses in mathematics for machine learning specialisation. The goal of this specialisation is to bridge the gap then bring candidates up to speed in the underlying mathematics, develop an intuitive understanding, and relate it to data science and machine learning. The specialisation is pointed at what linear algebra is and how it applies to data in the first course on Linear Algebra. It will then draw attention to what exactly are matrices and vectors and how one can operate them.
The Highlights
- 100 percent online course
- Flexible deadlines
- Beginner level
- The approximate course duration is 17 hours to complete
- Shareable certificate
- Offered by Imperial college of London
Programme Offerings
- Shareable Certificate
- self paced learning options
- course videos and readings
- practice quizzes
- Graded Assignments with peer feedback
- graded Quizzes with feedback
- Graded Programming Assignments.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
Mathematics for Machine Learning: Multivariate Calculus Fees details :
Particulars | Amount |
1 Month (16 hours/week) | Rs. 1,676 |
3 Month (5 hours/week) | Rs. 3,369 |
6 Month (3 hours/week) | Rs. 5,029 |
Eligibility Criteria
Certification Qualifying Details
For getting certified for the Mathematics for Machine Learning: Multivariate Calculus course candidates should complete the whole 6 weeks of training. If a candidate is enrolled for free auditing he/she will not get a certificate of completion. Only candidates who subscribed by paying the fee will be awarded a certificate.
What you will learn
After the completion of the Mathematics for Machine Learning: Multivariate Calculus course candidates will learn these:
- Candidates will gain skills like linear regression, multivariable calculus, vector calculus, and gradient descent.
- Candidates will learn and gain exposure to problem-solving skills.
- This will make the candidate prepare for real-life challenges and complexities faced in a business environment.
Who it is for
Application Details
The Mathematics for Machine Learning: Multivariate Calculus classes admissions can be applied by:
Step 1: The candidate should click https://www.coursera.org/learn/multivariate-calculus-machine-learning to access the programme
Step 2: There will be an ‘Enroll for free’ Tab. Once clicked, it will direct to Sign Up Page
Step 3: Once the sign up process has been completed, then candidates can try this programme for 7 days free.
Step 4: Once 7 days are over, the programme fee needs to be paid.
The Syllabus
Videos
- Welcome to Multivariate Calculus
- Welcome to Module 1!
- Functions
- Rise Over Run
- Definition of a derivative
- Differentiation examples & special cases
- Product rule
- Chain rule
- Taming a beast
- See you next module!
Readings
- About Imperial College & the team
- How to be successful in this course
- Grading Policy
- Additional Readings & Helpful References
Assignments
- Matching functions visually
- Matching the graph of a function to the graph of its derivative
- Let's differentiate some functions
- Practicing the product rule
- Practicing the chain rule
- Unleashing the toolbox
Discussion Prompt
- Nice to meet you!
Plugin
- Pre-course Survey
Videos
- Welcome to Module 2!
- Variables, constants & context
- Differentiate with respect to anything
- The Jacobian
- Jacobian applied
- The Sandpit
- The Hessian
- Reality is hard
- See you next module!
Assignments
- Practicing partial differentiation
- Calculating the Jacobian
- Bigger Jacobians!
- Calculating Hessians
- Assessment: Jacobians and Hessians
Ungraded Labs
- The Sandpit
- The Sandpit
Videos
- Welcome to Module 3!
- Multivariate chain rule
- More multivariate chain rule
- Simple neural networks
- More simple neural networks
- See you next module!
Assignments
- Multivariate chain rule exercise
- Simple Artificial Neural Networks
- Training Neural Networks
Programming Assignment
- Backpropagation
Discussion Prompt
- Backpropagation
Ungraded Lab
- Backpropagation
Videos
- Welcome to Module 4!
- Building approximate functions
- Power series
- Power series derivation
- Power series details
- Examples
- Linearisation
- Multivariate Taylor
- See you next module!
Assignments
- Matching functions and approximations
- Applying the Taylor series
- Taylor series - Special cases
- 2D Taylor series
- Taylor Series Assessment
Plugin
- Visualising Taylor Series
Videos
- Welcome to Module 5!
- Gradient Descent
- Constrained optimisation
- See you next module!
Assignments
- Newton-Raphson in one dimension
- Checking Newton-Raphson
- Lagrange multipliers
- Optimisation scenarios
Discussion Prompt
- Steepest strategies
Ungraded Lab
- Gradient descent in a sandpit
Videos
- Simple linear regression
- General non linear least squares
- Doing least squares regression analysis in practice
- Wrap up of this course
Readings
Did you like the course? Let us know!
Assignments
- Linear regression
- Fitting a non-linear function
Programming Assignment
- Fitting the distribution of height data
Ungraded Lab
- Fitting the distribution of heights data
Plugin
- Post-course Survey
Evaluation process
To get certified in the Mathematics for Machine Learning: Multivariate Calculus course first candidates should do subscribe. Then after the successful completion of the course, each candidate will be awarded a shareable valid certificate.