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Machine Learning with Python

IBM Data Science,

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course.

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Rating 4.5 based on 792 ratings
Length 7 weeks
Effort 5-6 weeks of study, 3-6 hours per week
Starts Dec 14 (6 weeks ago)
Cost $38
From IBM via Coursera
Instructors SAEED AGHABOZORGI, Joseph Santarcangelo
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Algorithms Machine Learning

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What people are saying

final project

The final project needs some attention.

The final project, though simple, yet makes one understand the basic tenets of several ML algorithms.

Useful final project.

Concise presentation,brief and to-the -point explanations, great course for an intermediate ML developer looking to brush up their skills.Programming exercises should me more detailed.I liked the concept of peer graded final project allowing us to review the projects of other learners as well.

The part that I thought isn't great is the use of other students to "grade" the final project.

The final project was a good way to put everything we learn to practice.

Some frustration that the final project instructions were not completely clear.

Very informative and amazing Excellent overview in Machine Learning While the final project is again terrible (like so many other courses), the content of this course is great.

I am very frustrated with the course's final project.

Not every new-to-stats understands your misleading instruction of the final project or can be capable of grading according to what is actually correct.

The final project is nowhere near the actual course syllabus.

But you ask them in the final project.

The final project is ill-structured.

The final project will be a challenge for what we have learned.I strongly recommend this course.

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machine learning with python

This course is an excellent platform to understand the basics of Machine Learning with python.

Very good course for beginners looks to explore Machine Learning with Python.

Excellent course Very nice course...learned a lot Dear all.It would be grate if you will add roc-curver and ordinal regression examples into this corse.Sincerely, Sergey Kutenko A great introduction to Machine Learning with Python.

this is amazing course for machine learning with python Superb course for machine learning beginners It is one of the best introduction course to Machine Learning.The material is well explained to someone with a beginner level of understanding to Statistics and Machine Learning.All the material is presented in a way that is easy to understand, without leaving out the details.

A must enroll for getting a good start on machine learning with Python The peer-graded assignment is a mess - especially if you try resubmitting work.

An Excellent Course for Machine Learning with Python Good for beginners.

Recommending more emphasis on the coding behind the algorithm (reminders / links to references ...) A very nice hands-on tutorial in machine learning with Python.

Machine Learning with Python is highly informative and very well presented.

Machine Learning with python provided by IBM is very good and basic course for beginners and very helpful .

Very cool machine learning with Python.

Its nice to learn Machine Learning with python.

The Machine Learning with Python course was very challenging.

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very well explained

the tool for HW doesnt work The concepts are very well explained!

It's a great course, very well explained and with totally useful codes.

Very well explained with a pretty comprehensive course material.

Very good, the basics very well explained.

Very interesting subject, and very well explained.

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real world

I learned a lot of new things that can be applied to the real world.Thanks a lot.

under well designed syllabus , became easy to learn and solve real world examples,which keeps motivated through out the learning process .

Some of the lectures did not break down real world data sets or examples as much as I would have liked.

Additionally, it would be nice to have more real world data set examples or tutorials to study or analyze with Python.

It provides with Mathematical equations for all the algorithms taught and coding is done with real world cases as well.

For real world problems, this module is probably the most useful so it would be beneficial to include more practice on clustering for examples.

Very good I love this course because this course learn me a lot I think which will help me in making real world project.

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ibm data science

This has been the most intensive course, so far (course 8 of 9), in the IBM Data Science Professional Certificate.

very Informative course The parts on regression are previously covered in other courses that are part of the IBM Data Science professional certificate.

at the point someone takes this class, they've been through 7 other classes in the IBM Data Science track, and only 3 of them have presented enough and important enough info that I've even bothered to keep notes for future reference.

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easy to follow

Good course contents and the pace is easy to follow I really enjoyed the ML course.

The video explanations of the different statistical models are clear and easy to follow, and the topics are fascinating.

Well created and covers major aspects of Datascience Excellent course Wonderful course to learn several techniques and easy to follow Great Course!

Instructions were clear and easy to follow.

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really enjoyed

I really enjoyed doing this course !!

I really enjoyed the course and was happy to find that the information provided was broken down enough to make it simple to understand the concepts.

thank you so much for this course, I really enjoyed this course.

Good for beginners I really enjoyed taking this course.

Excellent course, going into plenty detail with regard to different modelling approaches, I really enjoyed it.

I will be doing Andrew NG's course on YouTube now.. awesome I really enjoyed this course.

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data analysis

I really liked the course content, way of teaching and assignments.This will definitely help a beginner in data analysis to start with Too complex course, some one will do not understand many things out of it.

Very useful overview Out of reach for individuals wanting to do just data analysis.

But if you're like me and have done the other (comparatively better) IBM data analysis courses i guess you have no choice but to do this one in order to get the final certificate.

The best way to learn data analysis is to implement or do the real stuff by ourselves.

But I personally suggest you to take the Data Analysis with Python course first.

Instead of 4 classes that effectively wasted all of our time, (including the two whole intro classes) if the background mathematics is important, (again, I would venture that, to a non-expert-level general practitioner, which this class is aimed at, it's just not) move some of it out of this class and into some of the others so that we don't end up with effectively two important classes out of 9 - the Data Analysis with Python class, for being the most challenging mechanically, (i.e.

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get started

Very Thorough and Practical Course to get started with Machine Learning!!!

I started with data science 3 years ago and it was very difficult to get started without any programming or statistics background.

well design the course Although not extremely detailed in the model optimisation part of the work, it is a very useful way to get started on applied ML.

Strongly recommended for people who know Python and want to get started on machine learning.

Great Course to get started in machine learning A lot of ground is covered here.

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well designed

Well designed course with hands-on coding tutorials and assignments The course content is excellent and everything has been very nicely explained.

A well designed course and it was an amazing experience.

However, the labs and final exam are not well designed.

Overall, this is a great course The course was very well designed and the content was very precise and easy to understand.

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definitely recommend

Great course for beginners, definitely recommend.

I definitely recommend it Great course to learn Machine Learning.

I definitely recommend taking the course.

I would definitely recommend this course to my friend.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Research Scientist-Machine Learning $55k

Cloud Architect - Azure / Machine Learning $75k

Watson Machine Learning Engineer $81k

Machine Learning Software Developer $103k

Software Engineer (Machine Learning) $116k

Applied Scientist, Machine Learning $130k

Autonomy and Machine Learning Solutions Architect $131k

Applied Scientist - Machine Learning -... $136k

RESEARCH SCIENTIST (MACHINE LEARNING) $147k

Machine Learning Engineer 2 $161k

Machine Learning Scientist Manager $170k

Machine Learning Scientist, Personalization $213k

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Rating 4.5 based on 792 ratings
Length 7 weeks
Effort 5-6 weeks of study, 3-6 hours per week
Starts Dec 14 (6 weeks ago)
Cost $38
From IBM via Coursera
Instructors SAEED AGHABOZORGI, Joseph Santarcangelo
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Algorithms Machine Learning

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