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
Machine Learning is a highly demanded skill in the 21st Century. ML is the application of Artificial Intelligence that provides systems with the ability to learn and improve from experience, without any explicit programming and human intervention. It is the study of computer algorithms that automatically improve through experience. ML has now become an integral part of our lives, and data science and AI professionals are looking to upskill in this. In Coursera’s Machine Learning training course, you will learn the most effective ML techniques and gain experience in their practical applications with precision.
The Coursera Machine Learning programme teaches the extensive theories behind Machine Learning so that you can quickly learn to apply the techniques to new problems. Besides Machine learning, this course also provides an introduction to data-mining, artificial neural networks, logistic regression, and statistical pattern recognition.
This Machine Learning certification course is offered by Stanford University and is taught by one of the top educators of Stanford. It takes approximately 60 hours to complete this course. It has 18 modules rife with pre-recorded online lectures, readings and practice exercises for self-evaluation.
The Highlights
- 100% Online
- Readings for every module
- Self-Paced Education
- Shareable Certificate by Coursera
- Practice exercises
- Flexible Deadlines
- Subtitles available in French, Chinese (Simplified), Russian, English, Hebrew, Spanish, Hindi, Japanese
- Financial Aid
- Tangible Career Benefits
Programme Offerings
- 100% online course
- Shareable Certificate
- Pre-recorded Video Lectures
- Exercises and Practice Tests
- Flexible Deadlines
- Self-paced learning
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
The Candidates can enrol in this course for free by opting for the “Enrol for Free” option. The course can be completed completely free of cost. However, certification will not be available for free.
Machine Learning Fees Structure
| Course | Fees |
| 1 Month | 4,087 |
| 3 Months | 2,725 Total ₹8,175 |
| 6 Months | 2,044/ Total ₹12,263 |
Eligibility Criteria
Machine Learning training programme is a beginner level course. Candidates with a background in Data Science and an interest in Artificial Intelligence should go for this course.
Certification Qualifying Details
To get a certification in the Machine Learning certification by Coursera, candidates need to complete all the modules by going through the readings, watching the video lectures, and taking the practice exercises at the end of each module. Candidates need to purchase the certificate, and that certificate can be attached to their LinkedIn profiles, CVs, and resumes. The certificate purchase also gives you access to all the study material and graded assignments.
What you will learn
After completing the Machine Learning certification syllabus from Coursera, the candidates will gain substantial knowledge and skills in the following fields:
- An introduction to Logistic regression, which is a method of classifying data into discrete outcomes
- Knowledge about Neural Networks and its applications in Artificial Intelligence
- Understanding the performance of a machine learning system with multiple parts and learning to deal with skewed data
- Learning how to apply machine learning algorithms with large datasets.
Who it is for
This course is mainly targeted towards people interested in Data Science and Artificial Intelligence. It is a very good course for people already in the AI profession as well. Students, both graduate and undergraduate, can pursue this course, and who want to become ML engineers and Data Scientists.
Admission Details
Candidates who wish to enrol for these Machine Learning classes can do so for free by following the given steps:
- Visit the website of Coursera via: https://www.coursera.org/
- Search “ machine learning” course at the search bar.
- Select the option named “join for free”, given on the top right corner.
- Create an account on Coursera. If you are already registered, then simply log in to your account and enroll.
Application Details
Candidates do not need to fill out a separate application form for enrolling in this course. They can simply access the study material by signing in with Google or Facebook.
The Syllabus
Videos
- Welcome to machine learning!
- Applications of machine learning
- What is machine learning?
- Supervised learning part 1
- Supervised learning part 2
- Unsupervised learning part 1
- Unsupervised learning part 2
- Jupyter Notebooks
- Linear regression model part 1
- Linear regression model part 2
- Cost function formula
- Cost function intuition
- Visualizing the cost function
- Visualization examples
- Gradient descent
- Implementing gradient descent
- Gradient descent intuition
- Learning rate
- Gradient descent for linear regression
- Running gradient descent
Reading
- [IMPORTANT] Have questions, issues or ideas? Join our Forum
Videos
- Multiple features
- Vectorization part 1
- Vectorization part 2
- Gradient descent for multiple linear regression
- Feature scaling part 1
- Feature scaling part 2
- Checking gradient descent for convergence
- Choosing the learning rate
- Feature engineering
- Polynomial regression
Quizzes
- Practice quiz: Multiple linear regression
- Practice quiz: Gradient descent in practice
Videos
- Motivations
- Logistic regression
- Decision boundary
- Cost function for logistic regression
- Simplified Cost Function for Logistic Regression
- Gradient Descent Implementation
- The problem of overfitting
- Addressing overfitting
- Cost function with regularization
- Regularized linear regression
- Regularized logistic regression
- Andrew Ng and Fei-Fei Li on Human-Centered AI
Readings
- [IMPORTANT] Reminder about end of access to Lab Notebooks
- Acknowledgments
Quizzes
- Practice quiz: Classification with logistic regression
- Practice quiz: Cost function for logistic regression
- Practice quiz: Gradient descent for logistic regression
- Practice quiz: The problem of overfitting
Student Reviews for Machine Learning
Excellent campus
Verified ReviewCollege Infrastructure
The college has facilities like a digital library, regular library, and free Wi-Fi for all the students and faculty. The food in the hostel is really hygienic. There is a hostel for girl students within the campus. We have a canteen separately for students and faculty.
Instructors
Stanford Frequently Asked Questions (FAQ's)
Upon purchasing the certificate, you can gain access to all the course materials, the exercises and graded assignments. After completion, an electronic certificate will be added to your accomplishments page, and it can be shared on your LinkedIn profile.
This is a self-paced course with flexible deadlines. It is a basic course in Machine Learning, and you can access it anytime before you start a career in the same line.
Yes, financial aid is available by Coursera to candidates who cannot afford to pay the course fee. To avail financial aid, click on the Financial Aid button below the Enrol button on the left. You will be redirected to an application, and you must complete and wait for notification within 15 days of the application.
The study materials for this course are all free and can be accessed by signing in to your Coursera account via Google, Facebook or Email.
Coursera’s Machine Learning course is completely online and comes with flexible deadlines and a self-paced learning system. Subtitles are available in a variety of languages, and it covers almost all important basic topics in Machine Learning.