Probability and Probability Distributions for Machine Learning Free Course
Probability and Probability Distributions for Machine Learning
4.49
Beginner level
2.25 learning hrs
Take up free Probability for Machine learning course and forecast the variability of occurrence.
Instructor:
Dr. Abhinanda Sarkar
About this course
Probability is a branch of mathematics that teaches us to deal with the occurrence of an event after specific repeated trials. The value here is expressed from zero to one. It aids us in understanding exactly how a particular event is going to behave in a given set of variables. It also aids us in predicting possible variations in the behavior of the variable in a fluctuating environment.
This free course on Probability in Machine Learning provides basic foundations for probability and various distributions such as Normal, Binomial, and Poisson. It will make you familiar with the concept of Marginal probability and the Bayes theorem. Lastly, you will work with a demo on distributions calculations using Python.
Several world-class universities, such as the UT Austin and SRM Institute of Science and Technology, have formed a collaboration with Great Learning. They designed various post-graduate artificial intelligence courses and degree programs, which are India’s #1 ranked programs in the industry. An extensive curriculum has been prepared by top-class faculty so that the learners could develop advanced AIML skills. Various industry experts from top-notch organizations offer personalized mentorship to our learners, providing guidance to become successful in their careers.
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Course outline
Probability - Meaning and Concepts
You will learn what probability means and its concepts in this module through some examples. The instructor will discuss what an experiment is with an example and define and thoroughly explain the formula to determine the likelihood of an event. Later, a diagram will assist you in comprehending the extreme probability values and mutually exclusive events.
Normal Distribution and its Example
This section explains normal distribution for continuous functions and the association between mean, median, and mode in a normal distribution with solved examples and also discusses its properties and practical applications. You will also understand density function and standard distribution with solved example problems.
Get access to the complete curriculum once you enroll in the course
4.49
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India
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What our learners enjoyed the most
Skill & tools
60% of learners found all the desired skills & tools
Our course instructor
Dr. Abhinanda Sarkar
Senior Faculty & Director Academics, Great Learning
Machine Learning Expert
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What are the prerequisites to learn probability for machine learning?
Probability is one of the essential skills one must possess to have a good hold on machine learning concepts, and it is helpful in prediction and decision-making processes. Other prerequisites to learning machine learning include: Algebra, Linear Algebra, Trigonometry, Statistics, Calculus(for advanced topics), Python Programming, Terminal or Cloud Console.
How do beginners learn probability in machine learning?
Probability is not a challenging concept to learn, but it involves more than a few basic concepts to deal with while working with domains like machine learning. You will have to apply other concepts such as linear algebra, statistics, and calculus and also be able to work with python programming comfortably. You can start by learning Probability and Machine learning before diving into this Probability for Machine Learning course.
How long does it take to learn probability for machine learning?
The probability for machine learning course is a 2.5 hours long course, but you can learn it at your pace since the course is self-paced. With all the prerequisites mastered, it will not take much time to understand the concepts in this course. If you are supposed to start with learning all the basics such as statistics, calculus, python programming, and other such topics, you will take anywhere from 3 to 6 months before you are good at probability for machine learning.
Will I get a certificate after completing this course?
Probability for machine learning is a free course. You will be assigned with a few tasks after you complete the course to test your understanding. You can take this course in your leisure to learn and understand the subject since it is self-paced. You will be given with a certificate of completion after you successfully complete the course, and you can put it on your LinkedIn and other such platforms.
What are my career opportunities in probability in machine learning?
Machine Learning Engineer, Data Scientist, NLP Scientist, Business Intelligence Developer, and Human-Centered Machine Learning Designers are a few of the many career opportunities if you have mastered probability for machine learning. However, it is not just sufficient to learn probability; but you must also basket other skills such as statistics, linear algebra, calculus, python programming, and other concepts to be a top professional in machine learning.
Will I get a certificate after completing this Probability Distributions for Machine Learning free course?
Yes, you will get a certificate of completion for Probability Distributions for Machine Learning after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.
How much does this Probability Distributions for Machine Learning course cost?
It is an entirely free course from Great Learning Academy. Anyone interested in learning the basics of Probability Distributions for Machine Learning can get started with this course.
Is there any limit on how many times I can take this free course?
Once you enroll in the Probability Distributions for Machine Learning course, you have lifetime access to it. So, you can log in anytime and learn it for free online.
Can I sign up for multiple courses from Great Learning Academy at the same time?
Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.
Why choose Great Learning Academy for this free Probability Distributions for Machine Learning course?
Great Learning Academy provides this Probability Distributions for Machine Learning course for free online. The course is self-paced and helps you understand various topics that fall under the subject with solved problems and demonstrated examples. The course is carefully designed, keeping in mind to cater to both beginners and professionals, and is delivered by subject experts.
Great Learning is a global ed-tech platform dedicated to developing competent professionals. Great Learning Academy is an initiative by Great Learning that offers in-demand free online courses to help people advance in their jobs. More than 5 million learners from 140 countries have benefited from Great Learning Academy's free online courses with certificates. It is a one-stop place for all of a learner's goals.
What are the steps to enroll in this Probability Distributions for Machine Learning course?
Enrolling in any of the Great Learning Academy’s courses is just one step process. Sign-up for the course, you are interested in learning through your E-mail ID and start learning them for free online.
Will I have lifetime access to this free Probability Distributions for Machine Learning course?
Yes, once you enroll in the course, you will have lifetime access, where you can log in and learn whenever you want to.
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