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
Mathematical skill
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.
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.