how useful is stanfords machine learning course

With machine learning, computer programs can use data to make reasonably accurate predictions, cutting out the cost and time required by physical surveying. The new Stanford course Data for Sustainable Development introduces Stanford students to these new methods.

Full Answer

What is the best online course for machine learning?

“ Machine Learning ” on Coursera is a legendary machine learning course. It’s led by Stanford University and Andrew Ng, and it’s THE course that sparked the whole platform. “ AI & Machine Learning Career Track ” on Springboard is the best expert-level ML course.

Where should I start learning machine learning?

• Learn python - thare are plenty of youtube channels teaching you python. ...
• Learn math - I am coming wih mathematics background, but if you are not familiar first of all learn some math. ...
• Coursera Machine learning first course - Start with this to get basic understanding of ML
• Coursera AI for everyone - Get the non technical understand

What should I learn for machine learning?

• Pick a project, something you like and ideally, somthing you have knowledge in. It could be music, movie recommandation, NLP, chatbots, an AI that plays supermario perfectly hah, anything!
• Read … A lot! ...
• Go step by step. ...
• Do not stop trying to get better result, a research project is a project that never ends.

How good is Cornell at machine learning?

Cornell’s Machine Learning certificate program equips you to implement machine learning algorithms using Python. Using a combination of math and intuition, you will practice framing machine learning problems and construct a mental model to understand how data scientists approach these problems programmatically. Through investigation and ...

Is it worth paying for Andrew Ng's machine learning course on Coursera?

Obviously, It is an approach worth paying for Andrew NG's Machine Learning Course that is offered by coursera. But if you have knowledge about basics of data science, machine learning and artificial intelligence at that point you can join this course then it is beneficial for you.

How good is ML by Andrew Ng?

Excellent course, highly mathematical overview of how introductory machine learning models work. Thanks to Andrew Ng for putting together a lot of great material and challenging quizzes and exercises. Helpful? I've learned a lot from this machine learning course.

Is Andrew Ng course relevant?

8 years after publication, Andrew Ng's course is still ranked as one of the top machine learning courses. This has become a staple course of Coursera and, to be honest, in machine learning. As of this article, it has had 2,632,122 users enroll in the course.

Is machine learning course on Coursera useful?

I highly recommend this course as this was very beneficial for me. I learned a lot of new things and most of all, it cleared a lot of confusions and misconceptions that I had about some learning algorithms. I knew how to use those algorithms but I didn't understand how they were working.

Is Andrew Ng course difficult?

If you have maths background, then with little focus you can understand it very well. But if you have difficulty in maths then this course is very difficult for you. Machine learning and deep learning is all about maths. Linear algebra, calculus, stats are very important for ML.

Is machine learning by Andrew Ng for beginners?

Machine Learning course by Andrew Ng & Stanford review As I will say later, this course is the best choice for beginners, but everything in our world has drawbacks. I tried to notice some of them and attach links to sources, studying which you should have a more complete picture of Machine Learning and Data Science.

Are Coursera certificates worth it?

Are Coursera Certificates worth it? On the whole, yes. If you're seeking promotion, looking for a career change, or the skills you are learning are highly sought after, then a Coursera Certificate is definitely worth the investment. Coursera partners and course providers are world class.

What can you learn after Andrew Ng machine learning course?

You should have good knowledge of calculus,linear algebra, stats and probability. But this deep learning course just needs a little bit knowledge of linear algebra and calculus. Probability is not much used.

How good is Andrew Ng machine learning Quora?

Its certainly one of the best courses to get started with. [Very few people start practicing Machine Learning just after Andrew Ng's course, but they get a good perspective about Machine Learning from this course definitely].

Can I get job with Coursera certificate?

If you don't know, Coursera launched Professional Certificates recently which can help you get job-ready for an in-demand career field in less than a year. You can earn a career credential, apply your knowledge to hands-on projects that showcase your skills for employers and get access to career support resources.

Can I get job after completing course from Coursera?

That's all about whether course certificates from Udemy, Coursera, edX, and Udacity are valuable or not. They are definitely valuable in terms of providing recognition, adding the keyword in your resume, and providing initial boots, but you just cannot get a job or start a career by using them.

Which is the best ml course in Coursera?

10 Best Coursera Machine Learning and Deep Learning Courses & Certifications to Join in 2022IBM Applied AI [Professional Certificate] ... Deep Learning [specialization] ... Machine Learning [Free Course] ... Advanced Machine Learning. ... Facial Expression Recognition with Keras [Project] ... IBM AI Engineering [Professional Certification]More items...•

What you need to know before taking the Machine Learning course by Stanford

In this article, I will state my opinion about the course Machine Learning by Stanford. If you don’t know about this course yet, this is one of the most popular machine learning courses created by Andrew Ng, co-founder of Coursera and founder of deeplearning.ai.

Use Python Instead of Octave or MATLAB

As far as you may know, another major disadvantage of this course is that it does not use Python. Assignments must be completed only using Octave or MATLAB.

My articles that may be useful to you

You can also use my cheat sheet articles as lists of data science concepts just to understand that every task has several ways to solve:

Summary

Despite all these disadvantages, this course is still the best choice to start learning Data Science and Machine Learning. Advantages of this course overlap all the disadvantages:

Thank you for reading!

I hope these materials were useful to you. Follow me on Medium to get more articles like this.

Description

In this era of big data, there is an increasing need to develop and deploy algorithms that can analyze and identify connections in that data. Using machine learning (a subset of artificial intelligence) it is now possible to create computer systems that automatically improve with experience.

How is this different from the machine learning course on Coursera?

The Machine Learning MOOC offered on Coursera covers a few of the most commonly used machine learning techniques. XCS229 explores these concepts in greater depth and complexity, in addition to several other concepts.

Time Commitment

Expect to commit 10-14 hours/week for the duration of the 10-week program.

Certificate

Upon completing this course, you will earn a Certificate of Achievement in Machine Learning from the Stanford Center for Professional Development.

Grading and Continuing Education Units

This course is graded Pass/Fail, and letter grades are not awarded. By completing this course, you'll earn 10 Continuing Education Units (CEUs). CEUs cannot be applied toward any Stanford degree. CEU transferability is subject to the receiving institution’s policies.

Application

Prior to enrolling in your first course in the AI Professional Program, you must complete a short application (15-20 minutes). The application allows you to share more about your interest in joining this cohort-based course, as well as verify that you meet the prerequisite requirements needed to make the most of the experience.

Questions?

Note: Previously, the professional offering of the Stanford graduate course CS229 was split into two parts—Machine Learning (XCS229i) and Machine Learning Strategy and Reinforcement Learning (XCS229ii). As of October 4, 2021, material from CS229 is now offered as a single professional course (XCS229).

What is machine learning?

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens ...

What is neural network?

Neural networks is a model inspired by how the brain works. It is widely used today in many applications: when your phone interprets and understand your voice commands, it is likely that a neural network is helping to understand your speech; when you cash a check, the machines that automatically read the digits also use neural networks.

What is linear regression?

Linear regression predicts a real-valued output based on an input value. We discuss the application of linear regression to housing price prediction, present the notion of a cost function, and introduce the gradient descent method for learning.

How big is Stanford University?

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.

Course Description

This course provides a broad introduction to machine learning and statistical pattern recognition.

Instructor

Ng's research is in the areas of machine learning and artificial intelligence. He leads the STAIR (STanford Artificial Intelligence Robot) project, whose goal is to develop a home assistant robot that can perform tasks such as tidy up a room, load/unload a dishwasher, fetch and deliver items, and prepare meals using a kitchen.

Resources

Slides from Andrew's lecture on getting machine learning algorithms to work in practice can be found here.

The Main Disadvantage — What Should Be Understood

Use Python Instead of Octave Or MATLAB

What The Course Won’T Teach You

My Articles That May Be Useful to You

Summary

• Despite all these disadvantages, this course is still the best choice to start learning Data Science and Machine Learning. Advantages of this course overlap all the disadvantages: 1. Andrew Ng’s talent and teaching experiencemake it possible to explain complex things in simple words. In particular, this course is, in my opinion, the best explanatio...

See more on towardsdatascience.com

Description

How Is This Different from The Machine Learning Course on Coursera?

Guest Lecturers

Certificate

• Upon completing this course, you will earn a digital Certificate of Achievement in Machine Learning from the Stanford Center for Professional Development. You may also earn a digital Professional Certificate in Artificial Intelligence by completing three courses in theArtificial Intelligence Professional Program.

See more on online.stanford.edu

Grading and Continuing Education Units

Application